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1. Introduction Many of pelvic floor disorders, including prolapse, stress urinary incontinence, sexual dysfunction, congenital anomalies and others, are clearly manifested in the mechanical properties of pelvic organs. Therefore, mapping a response to applied pressure or load within the pelvic floor opens new possibilities in biomechanical assessment and monitoring of pelvic floor conditions. When the human finger palpates soft tissue, the brain tries to estimate the pressure response versus the finger motion. While different tissue characteristics may be detectable with side-by-side palpation, the human finger cannot distinguish even substantial deviations in tissue elasticity for two locations if they are separated in time or space. The brain cannot remember the finer aspects of tissue elasticity reliably. We also rely on visual assessments to augment palpated properties, such as the visually perceived tissue distention with Valsalva or coughing, in order to gather functional information of the vaginal tissue. The tactile imaging device, on the other hand, offers recordable and reproducible measurements for tissue evaluation [1]. Earlier, we designed a prototype of the Vaginal Tactile Imager (VTI) for visualization and assessment of the elastic properties of pelvic floor tissues [1]–[4]. The objective of this study is to identify specific tactile imaging and muscle contraction markers to characterize female pelvic floor conditions.

When the human finger palpates soft tissue, the brain tries to estimate the pressure response versus the finger motion. While different tissue characteristics may be detectable with side-by-side palpation, the human finger cannot distinguish even substantial deviations in tissue elasticity for two locations if they are separated in time or space. The brain cannot remember the finer aspects of tissue elasticity reliably. We also rely on visual assessments to augment palpated properties, such as the visually perceived tissue distention with Valsalva or coughing, in order to gather functional information of the vaginal tissue. The tactile imaging device, on the other hand, offers recordable and reproducible measurements for tissue evaluation [1]. Earlier, we designed a prototype of the Vaginal Tactile Imager (VTI) for visualization and assessment of the elastic properties of pelvic floor tissues [1]–[4]. The objective of this study is to identify specific tactile imaging and muscle contraction markers to characterize female pelvic floor conditions. 2. Materials and Methods 2.1. Tactile Imaging We define tactile imaging as a medical imaging modality that translates the sense of touch into a digital image. The tactile image is a function of P(x, y, z), where P is the pressure on soft tissue surface under applied deformation and x, y, z are coordinates where pressure P was measured. Tactile imaging closely mimics manual palpation, since the probe of the device with a pressure sensor array mounted on its face acts similarly to human fingers during clinical examination, slightly deforming soft tissue by the probe and detecting resulting changes in the pressure pattern. The tactile image is a pressure map on which the direction of tissue deformation must be specified. We calculated within the acquired tactile images the spatial gradients ∂P(x, y)/∂y directed to anterior/posterior (y-coordinate) from the vaginal channel (x-coordinate) at the regions of interest. The solid vaginal probe with pressure sensors along its two opposite sides allows high-resolution recording of dynamic response from pelvic floor muscles during muscle contractions.

al gradients ∂P(x, y)/∂y directed to anterior/posterior (y-coordinate) from the vaginal channel (x-coordinate) at the regions of interest. The solid vaginal probe with pressure sensors along its two opposite sides allows high-resolution recording of dynamic response from pelvic floor muscles during muscle contractions. 2.2. Vaginal Tactile Imager The VTI probe, as shown in Figure 1, is equipped with 96 pressure (tactile) sensors positioning every 2.5 mm along the both sides of the probe, an orientation sensor (accelerometer) and temperature sensors with micro-heaters. During the clinical procedure, the probe is used to acquire pressure responses from the vaginal walls. The VTI examination procedure includes data collection from all of the segments of the vagina. During an examination, data are sampled from the probe sensors and displayed on the VTI monitor in real time. The resulting pressure maps (tactile images) of the vagina integrate all of the acquired pressure and positioning data for each of the pressure sensing elements. In addition, the VTI records the dynamic contraction for pelvic floor muscles. The probe surfaces that contact the vaginal walls are preheated to human body temperature. A lubricating jelly is used for patient comfort and to provide reproducible boundary/contact conditions with deformed tissue; these conditions are classified as slip boundary conditions. The tactile probe measures an applied pressure, but not force. Force is a vector and by definition has amplitude and direction. The pressure sensors designed for VTI probe are not sensitive to tangential component of a force which may arise during probe motion and the sensors measure Pressure = Force (orthogonal component)/Area. This probe can be used not only for tissue compression in orthogonal direction to the tissue surface during the probe insertion (Tests 1), but it can be used for tissue compression during probe elevation (Test 2), for pressure pattern acquisition during probe rotation (Test 3) and pelvic floor muscle contraction (Test 4). The probe maneuvers in Tests 1 – 3 allow accumulation of multiple pressure patterns from the tissue surface to compose an integrated tactile image for the investigated area using a proprietary image composition algorithm like we developed for the breast and prostate [5] [6].

nd pelvic floor muscle contraction (Test 4). The probe maneuvers in Tests 1 – 3 allow accumulation of multiple pressure patterns from the tissue surface to compose an integrated tactile image for the investigated area using a proprietary image composition algorithm like we developed for the breast and prostate [5] [6]. The VTI software includes data analysis tools and reporting functions. It visualizes the anatomy of the vagina incorporating spatial measurements, pressure levels, calculated pressure gradients within the pressure maps, and assesses the pelvic floor muscle contraction capability (muscle strength). The examination procedure allows 4 tests: 1) probe insertion, 2) elevation, 3) rotation, and 4) voluntary muscle contraction. These tests provide the following information: Test 1: Tactile image for vaginal anterior and posterior compartments along the entire vagina; pressure gradients and anatomical sizes can be calculated. Test 2: Tactile image for apical anterior and posterior compartments which related to pelvic floor support structures; pressure gradients and anatomical sizes can be calculated. Test 3: Tactile images for left and right sides of vagina (circumferential tactile image from vaginal walls); anatomical sizes can be calculated. Test 4: Dynamic pressure response from voluntary PFM contractions recorded from for the opposite sides along the entire vagina; static and dynamic components can be separated.

Test 2: Tactile image for apical anterior and posterior compartments which related to pelvic floor support structures; pressure gradients and anatomical sizes can be calculated. Test 3: Tactile images for left and right sides of vagina (circumferential tactile image from vaginal walls); anatomical sizes can be calculated. Test 4: Dynamic pressure response from voluntary PFM contractions recorded from for the opposite sides along the entire vagina; static and dynamic components can be separated. The VTI measurement accuracy established with tissue models: ±3 mmHg for pressure, ±0.5 degree for probe orientation and ±0.1°C for measuring the temperature inside the probe on the surface of the micro-heaters. The probe was calibrated before every examination; it was cleaned and disinfected between patients. Because of the angled tip probe design (Figure 1), it is possible to translate the probe’s linear motion during Test 1 into vaginal wall deformation from the center of vaginal channel. Tests 1 – 3 reflect passive tissue measurements (no PFM contraction).

ery examination; it was cleaned and disinfected between patients. Because of the angled tip probe design (Figure 1), it is possible to translate the probe’s linear motion during Test 1 into vaginal wall deformation from the center of vaginal channel. Tests 1 – 3 reflect passive tissue measurements (no PFM contraction). 2.3. Population Description Twenty two women were enrolled in an observational study (clinical trials identifier NCT01848626 at http://clinicaltrials.gov) and underwent VTI examination. The analyzed data set included 20 subjects aged from 41 to 70 years. Prior to the VTI examination, a standard physical examination was performed including a bimanual pelvic examination and Pelvic Organ Prolapse Quantification (POP-Q) [7]. The pelvic floor conditions were categorized by prolapse staging based of maximum stage from anterior, posterior and uterine prolapse. Using this approach we found that 4 subjects had normal pelvic floor conditions, 4 with pelvic organ prolapse Stage I, 7 with Stage II, 4 with Stage 3 and 1 with Stage IV. Two subjects were excluded from analyzed data set because they have had a prior pelvic floor surgery. The clinical protocol was approved by the local Institutional Review Board and all women gave written informed consent. The study was done in compliance with the Health Insurance Portability and Accountability Act. The VTI images were obtained and recorded at the time of scheduled routine urogynecologic visits.

urgery. The clinical protocol was approved by the local Institutional Review Board and all women gave written informed consent. The study was done in compliance with the Health Insurance Portability and Accountability Act. The VTI images were obtained and recorded at the time of scheduled routine urogynecologic visits. Total study workflow comprised of the following steps: 1) Recruiting women who routinely undergo vaginal examination as a part of their diagnostic treatment of concerned areas; 2) Acquisition of clinical diagnostic information related to the studied cases by standard clinical means; 3) Performing a VTI examination in lithotomic position; 4) Analyzing tactile images and assessment of potential markers such pressure, pressure gradients and muscle contracting responses suitable for pelvic floor characterization. Additionally, the patients were asked to assess pain and comfort level of VTI examination relative to manual palpation. 2.4. Statistical Analysis The tactile imaging data from all the examinations were consolidated into a single dataset. Image reviewers had no knowledge of the subject’s pelvic floor conditions to avoid bias in the data processing. The clinical information (staging, age and parity) was then added to this dataset after the tactile imaging data (pressure, pressure gradients, muscle contracting response) were finalized.

o a single dataset. Image reviewers had no knowledge of the subject’s pelvic floor conditions to avoid bias in the data processing. The clinical information (staging, age and parity) was then added to this dataset after the tactile imaging data (pressure, pressure gradients, muscle contracting response) were finalized. One-way analysis of variance (ANOVA), paired t-test (normal plus State 1 vs States 2 – 4), and Pearson’s correlation coefficients were calculated to determine whether the various parameters showed dependence on the pelvic floor conditions using MATLAB 6.1 (Math Works, Natick, MA). For visual evaluation of the analyzed clinical data distributions we used the notched boxplots [8] showing a confidence interval for the median value (central horizontal line), 25% and 75% quartiles. The spacing between the different parts of the box helps to compare variance. The boxplot also identifies skewness (asymmetry) and outlier (small cross). The intersection or divergence of confidence intervals for two patient samples is a visual analog of the paired t-test. 3. Results All 22 enrolled women were successfully examined with the VTI and tactile images of vagina were recorded and stored. A typical examination consisting of four steps takes 1 to 2 minutes and the acquired data is used to generate a patient examination report.

One-way analysis of variance (ANOVA), paired t-test (normal plus State 1 vs States 2 – 4), and Pearson’s correlation coefficients were calculated to determine whether the various parameters showed dependence on the pelvic floor conditions using MATLAB 6.1 (Math Works, Natick, MA). For visual evaluation of the analyzed clinical data distributions we used the notched boxplots [8] showing a confidence interval for the median value (central horizontal line), 25% and 75% quartiles. The spacing between the different parts of the box helps to compare variance. The boxplot also identifies skewness (asymmetry) and outlier (small cross). The intersection or divergence of confidence intervals for two patient samples is a visual analog of the paired t-test. 3. Results All 22 enrolled women were successfully examined with the VTI and tactile images of vagina were recorded and stored. A typical examination consisting of four steps takes 1 to 2 minutes and the acquired data is used to generate a patient examination report. Upon reviewing the images, several areas were identified with consistently observed pressure peaks across VTI scans. They were selected as the marker sites for analysis. Specifically, the following locations along the pelvic floor were used for marker calculations: A1—anterior in the vicinity of hymen with maximum pressure feedback; A2—the second pressure peak along to anterior toward to proximal part; P1—posterior in the vicinity of hymen with maximum pressure feedback; P2—the second pressure peak along to posterior toward to proximal part; L1—vaginal sides with maximum pressure peaks in the vicinity of hymen. Figure 2 illustrates the listed locations. The pressure peaks used for A1, A2, etc. are not fixed (e.g. 2 cm from the introits), but varied among the patients.

ressure feedback; P2—the second pressure peak along to posterior toward to proximal part; L1—vaginal sides with maximum pressure peaks in the vicinity of hymen. Figure 2 illustrates the listed locations. The pressure peaks used for A1, A2, etc. are not fixed (e.g. 2 cm from the introits), but varied among the patients. During Test 1 (Probe Insertion) we have identified four (4) parameters that are potential markers for pelvic floor conditions (see Figure 3). They demonstrate correlation from −0.73 to −0.61 with pelvic floor conditions (normal and stage I-IV). These 4 parameters for A1 and P1 locations show a mild correlation from −0.40 to −0.13 with patient age and a mild correlation from −0.37 to −0.22 with parity. No significant correlations were found for other locations in this test. Figure 4 presents our findings for Test 2 (Probe Elevation). We have identified two (2) parameters for P1 and P2 locations that are potential markers for pelvic floor conditions. They demonstrate a correlation from −0.63 to −0.40 with pelvic floor conditions (normal, Stages I-IV). These parameters showed a mild-moderate correlation with patient age (−0.52 and 0.26) and parity (−0.26 and 0.13). No significant correlations were found for other locations in this test. Figure 5 presents our findings for Test 3 (Probe Rotation). We have identified one (1) parameter that is potential marker for pelvic floor conditions. It demonstrates correlation 0.66 with pelvic floor conditions (normal and stage I-IV) and weak or no correlation with patient age and parity.

Figure 4 presents our findings for Test 2 (Probe Elevation). We have identified two (2) parameters for P1 and P2 locations that are potential markers for pelvic floor conditions. They demonstrate a correlation from −0.63 to −0.40 with pelvic floor conditions (normal, Stages I-IV). These parameters showed a mild-moderate correlation with patient age (−0.52 and 0.26) and parity (−0.26 and 0.13). No significant correlations were found for other locations in this test. Figure 5 presents our findings for Test 3 (Probe Rotation). We have identified one (1) parameter that is potential marker for pelvic floor conditions. It demonstrates correlation 0.66 with pelvic floor conditions (normal and stage I-IV) and weak or no correlation with patient age and parity. Figure 6 presents our findings for Test 4 (Muscle Contraction). We have identified four (4) parameters that are potential markers for pelvic floor conditions. They demonstrate correlation from −0.61 to −0.39 with pelvic floor conditions (normal and stage I-IV). These parameters show weak correlation with patient age and parity. In Test 4 (Voluntary PFM Contractions) we observed 5 peaks as shown in Figure 6. Four of them (MS1-MS4) were identified as potential markers for pelvic floor characterization, as they demonstrate a correlation with pelvic floor conditions. The peak MS5 demonstrated variability from patient to patient and in this subset of patients, did not show any correlation with degree of prolapse.

in Figure 6. Four of them (MS1-MS4) were identified as potential markers for pelvic floor characterization, as they demonstrate a correlation with pelvic floor conditions. The peak MS5 demonstrated variability from patient to patient and in this subset of patients, did not show any correlation with degree of prolapse. Seventy three percents (73%) of the patients classified the VTI pain as none, 24% as mildly painful and 3% as a painful, on a 4-degree scale: none, mildly painful, painful, and severely painful. The patients were asked also to assess comfort level of VTI examination relative to manual palpation: 54% stated the VTI procedure was more comfortable, 36% the same and 10% less comfortable than manual palpation. No adverse events were reported.

on a 4-degree scale: none, mildly painful, painful, and severely painful. The patients were asked also to assess comfort level of VTI examination relative to manual palpation: 54% stated the VTI procedure was more comfortable, 36% the same and 10% less comfortable than manual palpation. No adverse events were reported. 4. Discussion We report a new approach to image and measure the behavior of the pelvic floor support system under vaginal tissue deformation and muscle contraction in women with and without prolapse. Using tactile imaging probe as shown in Figure 1, we found that patients with prolapse have pressure gradient measurements decreased 2 – 4 fold (200% – 400%) at specific locations (see Figure 3(b), Figure 3(d)) which can be interpreted as 2 – 4 fold softer than in patients with normal support and pelvic floor muscle contractive capabilities (muscle strengths) decrease up to 5 times (500%) (see Figure 6). These results clearly demonstrate that women with prolapse have significantly mechanical differences within the vaginal and surrounding pelvic floor supportive systems. While this is not new or surprising clinical finding [9] [10], biomechanical values of these changes with prolapse are acquired in vivo for the first time (Figure 3–Figure 6) which may add a valuable dimension to our current assessment of pelvic floor disorders.

vaginal and surrounding pelvic floor supportive systems. While this is not new or surprising clinical finding [9] [10], biomechanical values of these changes with prolapse are acquired in vivo for the first time (Figure 3–Figure 6) which may add a valuable dimension to our current assessment of pelvic floor disorders. In the current study, we have identified 11 parameters as potential markers for pelvic floor characterization with VTI use. We found that 9 of 11 parameters show statistically significant differences for prolapse conditions with p < 0.05 for one-way ANOVA and/or p < 0.05 for t-test. These 9 parameters have correlation factor (r) from −0.73 to −0.56. These parameters demonstrate a mild-moderate correlation with women age and parity for specified sample size. The results of this study demonstrate that the vaginal tactile images can be acquired and coupled with functional pelvic muscle assessment in one VTI examination.

ave correlation factor (r) from −0.73 to −0.56. These parameters demonstrate a mild-moderate correlation with women age and parity for specified sample size. The results of this study demonstrate that the vaginal tactile images can be acquired and coupled with functional pelvic muscle assessment in one VTI examination. In addition to recording tactile feedback during the tissue deformation, the VTI obtains measurement of muscle strength and allows evaluation of the relative functional impact of muscle contraction on measured biomechanical properties. The ability to assess and map pelvic floor muscles along entire vagina with the resolution of 2.5 mm is a novel measurement in pelvic floor assessment. The VTI pressure graphs for Test 4 (see Figure 6) are smoothed to 0.5 mm for better visual perception understanding that sharp pressure transitions in the tissue are not possible. To our knowledge, it is the first time the five pressure peaks were observed during pelvic floor muscle squeezing (see Figure 6(e)). One of the sites measured (A1) (see Figure 6(e)), is potentially exaggerated or an artifact because of the pubic bone, but this peak does have a lateral component which contradict sole resistance from the static structure. These peaks have a complex, dynamic pattern and require further investigation. One potential limitation is that the measurements were taken only with the probe in an anterior-posterior plane. Future evaluation with the probe in varied positions may better assess and document asymmetrical findings and provide a circumferential assessment of muscle function.

ttern and require further investigation. One potential limitation is that the measurements were taken only with the probe in an anterior-posterior plane. Future evaluation with the probe in varied positions may better assess and document asymmetrical findings and provide a circumferential assessment of muscle function. To fully characterize tissue as a mechanical system a great number of parameters are needed including the shear and Young’s moduli, bulk compressional modulus, nonlinearity, Poisson’s ratio, viscosity, poroelastic parameters, anisotropy and heterogeneity indices, etc. However, in most practical cases, there is no need to have a comprehensive mechanical characterization of the tissue of interest and even just one elasticity parameter, such as Young’s modulus (E), may be sufficient to address diagnostic tasks. Detection of a mechanical heterogeneity by manual palpation is based exclusively on sensing the variations of the Young’s modulus of tissue [11] [12], which may change by hundreds of percents from tissue to tissue and due to pathological or physiological conditions [11]–[15].

be sufficient to address diagnostic tasks. Detection of a mechanical heterogeneity by manual palpation is based exclusively on sensing the variations of the Young’s modulus of tissue [11] [12], which may change by hundreds of percents from tissue to tissue and due to pathological or physiological conditions [11]–[15]. Generally, inverse problem solution for 3-D tactile image P(x, y, z), would allow reconstruction of tissue elasticity distribution (E) as function of the same coordinates E(x, y, z). Unfortunately, the inverse problem solution is hardly possible for most real objects because it is non-linear and ill posed problem. But it seemed out that Tactile Image per se, P(x, y, z) reveals tissue or organ anatomy and elasticity distribution [5] [6] because it keeps the stress-strain relationship for deformed tissue. It is an interesting fact that the 3-D tactile image can be transformed into an elasticity image with the use a linear transformation for a region of interest. That means, in general, the spatial gradients ∂P(x, y, z)/∂x, ∂P(x, y, z)/∂y and ∂P(x, y, z)/∂z can be used in practical purposes for quantitative assessment of tissue elasticity because they have a validated background [1]–[6], [11]–[15] allowing quantitative comparison and analysis for different patients with anatomical variations.

general, the spatial gradients ∂P(x, y, z)/∂x, ∂P(x, y, z)/∂y and ∂P(x, y, z)/∂z can be used in practical purposes for quantitative assessment of tissue elasticity because they have a validated background [1]–[6], [11]–[15] allowing quantitative comparison and analysis for different patients with anatomical variations. The direct measurement of in vivo tissues presents a number of challenges. One of these challenges is that the tissue studies (such as the vaginal wall) cannot be isolated in vivo and the pelvic structures must be measured as a system, including the vaginal wall and underlying structures. With this in mind, it is thought that the addition of a functional muscle assessment is needed as part of the tactile image assessment to better evaluate the pelvic floor tissues and potential relative contributions of the underlying muscles. Nevertheless, the analysis of the muscle rest tone contribution into acquired parameters in Tests 1 – 3 is beyond of this study.

of a functional muscle assessment is needed as part of the tactile image assessment to better evaluate the pelvic floor tissues and potential relative contributions of the underlying muscles. Nevertheless, the analysis of the muscle rest tone contribution into acquired parameters in Tests 1 – 3 is beyond of this study. Currently, the most widely used assessment of pelvic organ prolapse (POP) is limited to documenting surface anatomy, such as the POP Quantification system developed by the International Continence Society [7]. More sophisticated technology, such as functional MRI and 3-D ultrasound, offer insight into anatomy with applied forces as well. And while the resulting measurements are a consequence of changes in the mechanical pelvic floor properties, they do not specifically measure the individual, mechanical properties of pelvic floor tissue [16]. These individual differences are often appreciated on a clinical exam, such as the ease that tissue descends or balloons with applied pressure, the palpable tissue properties on exam, asymmetrical defects, prior scarring, etc. The impression of the tissue quality demonstrated on an exam and the impression of what areas are affected by visual and palpated cues factor into a physician’s assessment of a patient’s condition, but are challenging to document or translate for outcomes by quantitative metrics. The terminology that describes the details of these differences is now largely descriptive and not quantified or standardized for a better comparison of baseline characteristics or a normal support conditions. A measured, reproducible soft tissue assessment by VTI may offer insight into the differences of these baseline characteristics and allow for a clearer process for determining the most effective treatment options with predictable response/outcome, with goals for optimal support as well as the maintenance of functional outcomes for underlying organ condition and function.

I may offer insight into the differences of these baseline characteristics and allow for a clearer process for determining the most effective treatment options with predictable response/outcome, with goals for optimal support as well as the maintenance of functional outcomes for underlying organ condition and function. It is possible, that if we could make further differentiations in the biomechanical qualities of the tissues behind pelvic floor conditions, that we could offer more effective treatments. For example, better identifying compartments with “pre-prolapse” defects that may benefit from additional repair at the time of reconstructive surgery to prevent recurrent prolapse, guidance for what patients benefit from a more aggressive repair or a more limited site-specific repair, which patients may benefit from a graft material, and which patients may benefit from pelvic floor physical therapy as a conservative or peri-operative approach. Currently, the majority of these judgments rely on years of experience, resources that are available to the surgeon, surgical training backgrounds and biases and treatment preferences that the patients brings to the table. Perhaps, the VTI may offer standardized measurements to help tailor our judgments beyond the current in-office tools and to assess over time with both conservative and surgical management of pelvic floor conditions.

urgical training backgrounds and biases and treatment preferences that the patients brings to the table. Perhaps, the VTI may offer standardized measurements to help tailor our judgments beyond the current in-office tools and to assess over time with both conservative and surgical management of pelvic floor conditions. To date, it is challenging and important to combine functional anatomy with in vivo tissue properties. It would also be extremely useful to correlate mechanical properties measured by the VTI with anatomical measurements from 3-D imaging such as MRI or ultrasound. The combination of these tools, image fusions, anatomic and functional valuation may provide us the best assessment of pelvic floor conditions or a needed insight into complicated pelvic floor conditions. Another potential use for VTI data is to provide individual biomechanical data to use in the predicative modeling [17] [18] and to investigate the relationship between anatomical disruptions with the muscle function [19]–[21].

ment of pelvic floor conditions or a needed insight into complicated pelvic floor conditions. Another potential use for VTI data is to provide individual biomechanical data to use in the predicative modeling [17] [18] and to investigate the relationship between anatomical disruptions with the muscle function [19]–[21]. As part of the soft tissue assessment, functional imaging of the pelvic floor muscles offers a needed insight into the biomechanics of the functional pelvic floor and to help understand the relative contribution of pelvic floor muscle function to soft tissue characteristics. While urodynamics is used for the assessment of SUI conditions, there are no standardized tools to accurately acquire in vivo stress-strain data to evaluate the female PF for POP and SUI patients. There is a need to develop new technologies, analogous to urodynamic tests, to enable the evaluation of PF function that is quantitative, anatomically sensitive and specific. As practiced during routine pelvic floor examination for SUI, the technical need for PF diagnostics are based primarily in the sensing and measurement of the force and movement produced by musculature of the levator ani during contraction. Clearly, for a biomechanically correct delineation of PF function, it is useful to have information that is directionally sensitive and constructed to measure PF closure [22]. Earlier, the development of a vaginal probe with four force sensors for the evaluation of the dynamics of pelvic floor function was described [22]. Nevertheless, in current practice, the manual muscle testing per vagina or rectum is the technique used by most clinicians to evaluate the PF muscles. Unfortunately, due to the location of the PF muscles defining its normal function in a noninvasive way is clinically and technically challenging but possible. It is expected that by understanding the processes and, the mechanisms involved in the functioning of the PF we can better identify more sensitive clinical diagnoses and have treatment outcomes in the management of incontinence [23].

function in a noninvasive way is clinically and technically challenging but possible. It is expected that by understanding the processes and, the mechanisms involved in the functioning of the PF we can better identify more sensitive clinical diagnoses and have treatment outcomes in the management of incontinence [23]. A strength of this study is that the current VTI offers an opportunity to assess the vaginal support along the entire length of the anterior, posterior and lateral walls at rest, with manually applied deflection pressures and with voluntary pelvic floor muscle contraction. This allows us a large body of measurements to evaluate individual variations in support defects as well as identify specific potential markers to measure tissue properties as they correlate to pelvic floor support. In addition, the technology gives the ability to measure pelvic floor muscle strength at specific locations along the vaginal wall and help correlate the relative contributions to measured tissue properties. These measurements may provide insight into the functional contribution or relationships between support tissue and underlying muscle support. Because VTI testing is relatively easy and inexpensive to obtain, post-treatment follow-up is obtainable to evaluate the surgical impact on functional tissue properties and pelvic floor muscles. This may provide valuable outcome measurements for evaluating our current and future treatments.

d underlying muscle support. Because VTI testing is relatively easy and inexpensive to obtain, post-treatment follow-up is obtainable to evaluate the surgical impact on functional tissue properties and pelvic floor muscles. This may provide valuable outcome measurements for evaluating our current and future treatments. A weakness of this study is a small sample size. Further studies with larger patient population, investigating a variety of other pelvic floor conditions, and use in the evaluation of interventions including physical therapy, conservative management options and surgical correction are needed at this point to further explore diagnostic values of tactile imaging. Another weakness is the lack of data to correlate pelvic floor muscle assessment with the site of prolapse, degree of symptom severity for detected prolapse or associated urinary or fecal continence symptoms. It was thought a sub-analysis may be misleading given the limited sample size and should be reserved for future studies. There may be very important differences in functional PFM recordings between a patient with a large distention defect of the vaginal wall versus a primary apical defect, symptomatic versus asymptomatic prolapse or among patients with associated urinary or rectal complaints. For future studies, it would be important to evaluate symptom severity for pelvic floor disorders to determine whether there is a correlation between pelvic floor muscles evaluation, resting tone and associated elasticity measurements of the underlying tissue. This may help us further differentiate types of pelvic floor conditions, their underlying severity and how to tailor treatments to best care for the individual patient. An additional weakness is that the clinician obtaining the VTI measurements was not blinded to the POP-Q measurements. The procedure for VTI recording was standardized and would be difficult to bias the recording based on expectations of the measurements, however this does remain a potential bias. To diminish the potential influence of this bias, the images were evaluated and parameter values were extracted by another observer that did not have the clinical information available until the data scaling vs prolapse stage, age and parity.

expectations of the measurements, however this does remain a potential bias. To diminish the potential influence of this bias, the images were evaluated and parameter values were extracted by another observer that did not have the clinical information available until the data scaling vs prolapse stage, age and parity. 5. Conclusion Tactile imaging markers such as pressure, pressure gradient and dynamic pressure response during voluntary muscle contraction can be used for biomechanical characterization of female pelvic floor conditions to aid in the diagnosis and evaluation of the female pelvic floor conditions. Acknowledgements The authors would like to thank Alison Cooke, LPN, for clinical research coordination and data management, Randy Wood, MSTM, RDMS, RT, for study monitoring, and Milind Patel, MS, for technical assistance with the device. Research reported in this publication was supported by the NIH/NIA under Award Number AG034714. The content is solely the responsibility of the authors and does not represent the official views of the NIH/NIA. Disclosure Summary H. van Raalte: shareholder of Advanced Tactile Imaging, Inc. V. Egorov: CEO and shareholder of Advanced Tactile Imaging, Inc. Abbreviations ANOVAOne-Way Analysis of Variance NIANational Institute on Aging NIHNational Institutes of Health HPZVaginal High Pressure Zone PFPelvic Floor PFMPelvic Floor Muscle POPPelvic Organ Prolapse POP-QPelvic Organ Prolapse Quantification System SUIStress Urinary Incontinence VTIVaginal Tactile Imager Figure 1 Vaginal probe. Pressure sensors are aligned on the outer surface of the probe (highlighted on the image).

NIHNational Institutes of Health HPZVaginal High Pressure Zone PFPelvic Floor PFMPelvic Floor Muscle POPPelvic Organ Prolapse POP-QPelvic Organ Prolapse Quantification System SUIStress Urinary Incontinence VTIVaginal Tactile Imager Figure 1 Vaginal probe. Pressure sensors are aligned on the outer surface of the probe (highlighted on the image). Figure 2 Locations of the VTI markers identified within the pelvic floor. A1 and A2 are within the anterior compartment, P1 and P2 in the posterior compartment and L1 in the lateral compartments (left and right sides). Figure 3 Test 1—probe insertion results. Tactile imaging markers at distal anterior (panels (a) and (b)) and distal posterior (panels (c) and (d)) which are sensitive to varying degrees of prolapse. Panel (e) shows a typical pressure response map (tactile image) for this test. Figure 4 Test 2—probe elevation results. Tactile imaging markers at posterior (panels (a) and (b)) which are sensitive to varying degrees of prolapse. Panel (c) shows a typical pressure response map (tactile image) for this test. Figure 5 Test 3—probe rotation results. Tactile imaging marker at distal lateral location (panel (b) which is sensitive to varying degrees of prolapse. Panel (a) shows a typical pressure response map (tactile image) for this test. Figure 6 Test 4—voluntary PFM contractions. Muscle contraction capabilities at anterior (panels (a) and (b)) and posterior (panels (c) and (d)) which are sensitive to varying degrees of prolapse. Panel (e) shows distribution of maximum pressure response for anterior and posterior compartments for this test.

1. Introduction In the last two decades there has been a fundamental shift in global connectivity and awareness. Parallel to this shift, and likely fuelled by increased connectivity, there has also been a marked growth in global health programs and initiatives, in particular an expansion of academic partnerships between high and low-income countries. These have emerged to fulfill dual needs; the desire and interest for students and faculty from higher income countries to have exposure to some of the conditions and diseases more prevalent in low income countries and a mutual desire to use the resources and expertise available in academic institutions to reduce some of the stark disparities in health care outcomes seen globally.

st for students and faculty from higher income countries to have exposure to some of the conditions and diseases more prevalent in low income countries and a mutual desire to use the resources and expertise available in academic institutions to reduce some of the stark disparities in health care outcomes seen globally. Addressing the disparity in the availability of medical specialists is often a major component of such partnerships. The World Health Organization estimates a shortfall of 4.3 million medical providers globally, with the deficit overwhelmingly concentrated in low income countries [1]. Stark disparities also exist in access to physicians with specialty and sub-specialty training; only 12% of the world’s specialist surgical workforce, including surgeons, anesthesiologists and obstetrician gynecologists reside in sub-Saharan Africa, where over a third of the world’s population lives [2]. This shortfall in providers not only compromises current access to care in areas with deficits, but also impacts the ability to continue and expand future access by making it extremely challenging to train the next generation of providers. A sole obstetrician-gynecologist responsible for thousands of women and attending to one complication after another will be hard pressed to find the time and, perhaps mental energy required to provide quality training to their junior or assistants. Relying on the apprenticeship model historically employed by surgical specialties will thus be insufficient to expand the workforce to the numbers required for safe access.

after another will be hard pressed to find the time and, perhaps mental energy required to provide quality training to their junior or assistants. Relying on the apprenticeship model historically employed by surgical specialties will thus be insufficient to expand the workforce to the numbers required for safe access. Technology is now an established component of health care provision and training. Distance learning or tele-learning has been used widely to expand access to medical education. Teleconferencing for education has been defined as using real-time and live programming with participants at two or more sites [3]. Most published experience with such distance education programs is limited to participants at remote sites within the same country [4]–[7]. Using distance learning to facilitate education between countries and across academic partnerships is a relatively new use, though results have been promising [8]. In this report we present our experience in building a low cost teleconference as a way to facilitate the ability of an academic partnership to expand access to sub-specialty obstetrics and gynecology training.

Technology is now an established component of health care provision and training. Distance learning or tele-learning has been used widely to expand access to medical education. Teleconferencing for education has been defined as using real-time and live programming with participants at two or more sites [3]. Most published experience with such distance education programs is limited to participants at remote sites within the same country [4]–[7]. Using distance learning to facilitate education between countries and across academic partnerships is a relatively new use, though results have been promising [8]. In this report we present our experience in building a low cost teleconference as a way to facilitate the ability of an academic partnership to expand access to sub-specialty obstetrics and gynecology training. 2. Methods 2.1. The Partnership In 2012 an academic partnership was formed between the Departments of Obstetrics and Gynecology (OB/GYN) at the Mbarara Regional Referral Hospital (MRRH) in Mbarara, Uganda, and the Massachusetts General Hospital (MGH) in Boston, USA. Both institutions are referral centers and provide tertiary level obstetric and gynecologic care to a large surrounding population. The goals of this partnership were to foster bilateral education of residents in both departments, thus increasing capacity, and to increase the quality of care provision and promote research.

institutions are referral centers and provide tertiary level obstetric and gynecologic care to a large surrounding population. The goals of this partnership were to foster bilateral education of residents in both departments, thus increasing capacity, and to increase the quality of care provision and promote research. With only 10 faculty and no fellowship-trained subspecialists, the MRRH Department of OB/GYN faces the challenge of increasing capacity and depth of knowledge amongst its faculty and residents without easy access to sub-specialty obstetric and gynecologic training and expertise. A needs assessment conducted early in our partnership identified this educational gap as a key area of need. Through several face-to-face meetings, observation of clinical rounds and didactics, the concept of a teleconference evolved as a low cost strategy to facilitate distance learning for MRRH residents and to promote interaction between trainees at both institutions. The specific objectives of the teleconference were to 1) increase the breadth and depth of the didactic portion of bilateral resident education through case-based discussion 2) spur interaction with clinicians from different training and work environments to prompt new insights into the management of disease and systems of care across both institutions and 3) demonstrate that teleconferencing is an effective teaching tool for members of both a local and remote audience.

se-based discussion 2) spur interaction with clinicians from different training and work environments to prompt new insights into the management of disease and systems of care across both institutions and 3) demonstrate that teleconferencing is an effective teaching tool for members of both a local and remote audience. 2.2. Building the Teleconference Program Though the initial conception of the program occurred with face-to-face meetings of involved partners, implementation and execution largely occurred electronically. Email communication was used to plan the curriculum and select monthly teaching topics. To encourage bilateral involvement each lecture had speakers from both institutions. Typically a case presentation relevant to the selected topic was prepared and presented by a resident from MRRH. The didactic portion to the lecture was prepared and presented by fellows in training or faculty from MGH. The lectures lasted 60 minutes. The content of the lectures is listed in Table 1. Each lecture started with a case report, was followed by a didactic lecture, and finished with a 15-minute discussion period. All ten Ugandan faculty participated in the teleconferences. The ages of the participants ranged from 21 to 60 years of age. The genders of the participants were evenly divided between men and women. The educational level of the participants ranged from being in medical school, in the obstetrics and gynecology residency program, or on medical faculty of the respective Boston and Ugandan departments of Obstetrics and Gynecology. PowerPoint lectures were HIPAA compliant and prepared ahead of time so they could be shared via email or cloud storage (Dropbox™) for personal access and download. These lectures were sent ahead of scheduled teleconferences. The effectiveness of the conference was evaluated through email feedback.

trics and Gynecology. PowerPoint lectures were HIPAA compliant and prepared ahead of time so they could be shared via email or cloud storage (Dropbox™) for personal access and download. These lectures were sent ahead of scheduled teleconferences. The effectiveness of the conference was evaluated through email feedback. Teleconferences were planned to recur every third Tuesday of the month at 7 am Eastern Standard Time (EST) and 2 or 3 pm Eastern African Time (EAT) depending on daylight savings in the US. Communication via web conferencing was the primary mode of teleconferencing. Each planned conference would begin with an international phone call between organizers on each end to establish contact prior to web conferencing.

rd Time (EST) and 2 or 3 pm Eastern African Time (EAT) depending on daylight savings in the US. Communication via web conferencing was the primary mode of teleconferencing. Each planned conference would begin with an international phone call between organizers on each end to establish contact prior to web conferencing. Web conferencing tools used included Ventrilo™ and Skype™, through a number of interfaces: personal and hospital computer and smart phones. An international call using mobile phone was available as a back up if Internet connectivity failed. In Boston, free Wi-Fi connections were available through network systems. At times personal cellular data networks were used though such use incurred no additional cost to the end user. In Mbarara, no Wi-Fi networks were available. Internet access was obtained by purchasing cellular data through established commercial networks. On average 1 GB of data costs USD12. Approximately 100 MB and 300 – 500 MB of data is typically required for an hour of continuous audio and video web-conferencing respectively. In Boston, lectures were displayed to residents on projector equipment on site at MGH. In Mbarara, similar projection of lectures was performed and audio or video from the web conference provided through personal laptop computer (PC). In the event of electricity outages in Mbarara, slides were viewed via personal computer. 3. Funding Funding for the project came from an endowed women’s healthcare global health fund held in the Department of Obstetrics and Gynecology at MGH.

Web conferencing tools used included Ventrilo™ and Skype™, through a number of interfaces: personal and hospital computer and smart phones. An international call using mobile phone was available as a back up if Internet connectivity failed. In Boston, free Wi-Fi connections were available through network systems. At times personal cellular data networks were used though such use incurred no additional cost to the end user. In Mbarara, no Wi-Fi networks were available. Internet access was obtained by purchasing cellular data through established commercial networks. On average 1 GB of data costs USD12. Approximately 100 MB and 300 – 500 MB of data is typically required for an hour of continuous audio and video web-conferencing respectively. In Boston, lectures were displayed to residents on projector equipment on site at MGH. In Mbarara, similar projection of lectures was performed and audio or video from the web conference provided through personal laptop computer (PC). In the event of electricity outages in Mbarara, slides were viewed via personal computer. 3. Funding Funding for the project came from an endowed women’s healthcare global health fund held in the Department of Obstetrics and Gynecology at MGH. 4. Results From June 2012 through January 2015, thirty teleconferenced lectures were planned and given (Table 1 and Table 2). The conferences were progressively streamlined using the email feedback.

3. Funding Funding for the project came from an endowed women’s healthcare global health fund held in the Department of Obstetrics and Gynecology at MGH. 4. Results From June 2012 through January 2015, thirty teleconferenced lectures were planned and given (Table 1 and Table 2). The conferences were progressively streamlined using the email feedback. Topics covered the breadth of obstetrics and gynecology with some emphasis given to sub-specialty areas of gynecology oncology and maternal fetal medicine given the demonstrated need. There were an average of twelve attendees at MGH (students, residents, fellows, and faculty) and 20 at Mbarara (Figure 1 and Figure 2). The meetings were unrestricted and open to all members of the Boston and Mbarara departments. Though primarily targeted to residents, at times other members of the care team including midwives, nurses and nursing students attended particularly for lectures aimed at strengthening teams and providing overarching care principles.

ings were unrestricted and open to all members of the Boston and Mbarara departments. Though primarily targeted to residents, at times other members of the care team including midwives, nurses and nursing students attended particularly for lectures aimed at strengthening teams and providing overarching care principles. Internet connectivity was the biggest challenge to successfully sharing lectures bilaterally. Table 2 summarizes the connectivity challenges and outcomes for the first 18 months of conferencing. Problems in connectivity were mostly commonly manifested as delayed transmission of audio or video, freezing of transmission and dropping of connections requiring redialing and reconnection. Five of the nineteen lectures were given without interruption. Skype™ became the modality of choice for web conference. Ventrilo™ was dropped after several lectures because of the difficulty in real time conversations. Disruptions in Internet connectivity occurred from access at both institutions. Early in the development of the program we transitioned from hospital Wi-Fi networks at MGH, which proved unreliable, to more robust personal cellular data networks accessed via Smartphone. In Mbarara, cellular data networks worked well for the most part, but also contributed to interruptions as described above. Initial attempts at including video conferencing led to many interruptions in connectivity, thus this was also eliminated early in the development of the program and audio alone relied upon for conferencing.

cellular data networks worked well for the most part, but also contributed to interruptions as described above. Initial attempts at including video conferencing led to many interruptions in connectivity, thus this was also eliminated early in the development of the program and audio alone relied upon for conferencing. 5. Discussion Meeting the health demands of a population requires access to skilled, well-trained health providers. Current shortages in such skilled providers calls for multiple and innovative strategies to increase the work force and in particular to increase the numbers of providers with specialized training. We present a simple and low cost model for education that harnesses academic partnerships and easily available resources to promote bilateral resident education and increase access to sub-specialty expertise in settings typically excluded. Our experience adds to modest literature examining distance education across countries and provides encouraging preliminary findings for the development and expansion of such programs.

ilable resources to promote bilateral resident education and increase access to sub-specialty expertise in settings typically excluded. Our experience adds to modest literature examining distance education across countries and provides encouraging preliminary findings for the development and expansion of such programs. Commitment from both partner institutions was critical for this program to develop and become sustainable. An identifiable advocate from each institution with the responsibility of facilitating communication was extremely important in the planning of lectures and execution of teleconferences. We also found that during the lecture having faculty familiar with the environment and culture of both settings played an important role in facilitating discussion. This was particular relevant when presenting fellows or faculty from MGH had no familiarity with the clinical environment at MRRH. It was also helpful for cultural reasons, for example to facilitate the translation of used idioms, language patterns and even accents specific to each geographical setting.

ing discussion. This was particular relevant when presenting fellows or faculty from MGH had no familiarity with the clinical environment at MRRH. It was also helpful for cultural reasons, for example to facilitate the translation of used idioms, language patterns and even accents specific to each geographical setting. Internet connectivity remained the biggest challenge to successful conferencing though relatively few-six of thirty lectures, had to be cancelled due to failed connections or technical issues. Relying on cellular data at both institutions and eliminating video dramatically improved the quality of connection. In such partnerships it is often assumed that infrastructure at the low-income institution will be the limiting factor; therefore it was an important lesson to consider connectivity issues at MGH and actively address those. Advance planning and sharing of lecture materials provided both sides with the tools to proceed as a back up in instances of failed Internet connectivity. This was important to ensure that information exchange still occurred and facilitated separate learning in those few instances when web conferencing was unsuccessful.

dvance planning and sharing of lecture materials provided both sides with the tools to proceed as a back up in instances of failed Internet connectivity. This was important to ensure that information exchange still occurred and facilitated separate learning in those few instances when web conferencing was unsuccessful. The ability to have real-time interaction and discussion is a major attraction for distance learning programs based on teleconferencing over e-learning and web-based learning that is self directed or asynchronous. Videoconferencing greatly facilitates this, and yet early in our program we had to eliminate this due to constraints in bandwidth speed. We found that audio conferencing did continue to provide some level of interaction, however, face-to-face interaction would likely have stimulated more interaction between groups of residents and faculty who have never met in person. Requiring case presentations from residents at the distance site-MRRH became an important method to deliberately encourage active participation from both sites. Locally chosen case presentations prompted more interaction from those residents and required faculty and fellow from MGH to consider differences in clinical environment that may be present. This not only facilitated bilateral engagement but also provided the platform for bilateral learning opportunities and discussion. Introducing other deliberate strategies such as technology based user participation may further increase interaction and learning opportunities.

in clinical environment that may be present. This not only facilitated bilateral engagement but also provided the platform for bilateral learning opportunities and discussion. Introducing other deliberate strategies such as technology based user participation may further increase interaction and learning opportunities. Video-conferencing has been performed successfully in other examples of distance learning though with higher costs. As a voluntary program with limited funding we sought to introduce this program with little to no costs. We achieved this on a budget of under $500. Current available methods for data transmission during teleconferencing are satellite communication, Internet Protocol (IP), Integrated Services Digital Network (ISDN) and cellular networks [3]. Satellite communication costs tend to be prohibitive, with start-up costs averaging USD 30,000 and rental costs of USD 500 – 1000/month. ISDN requires access to public switched telephone networks over wired telephone systems. These are currently unavailable in many areas of low-income countries and with current widespread use of mobile phones unlikely to be applied. IP and cellular networks are therefore most relevant for use in this type of program.

h. ISDN requires access to public switched telephone networks over wired telephone systems. These are currently unavailable in many areas of low-income countries and with current widespread use of mobile phones unlikely to be applied. IP and cellular networks are therefore most relevant for use in this type of program. We relied on Skype™ as free software available to facilitate conferencing via IP and cellular networks. This was used with similar success in a distance education program facilitating access to anesthesia subspecialty education [8]. Ventrillo was abandoned because it required PCs on both sides and required holding down the keyboard key to talk. This led to confusion when there was a question from the other side. Other distance learning programs have had success using alternative software, of which Polycom®, has been most commonly described [4] [5] [9] [10]. Costs for using this software average 2 million USD for a large corporation (http://www.bradreese.com/blog/polycom-6-8-2010.htm).

there was a question from the other side. Other distance learning programs have had success using alternative software, of which Polycom®, has been most commonly described [4] [5] [9] [10]. Costs for using this software average 2 million USD for a large corporation (http://www.bradreese.com/blog/polycom-6-8-2010.htm). A future and important step in our program will be to evaluate the effectiveness and acceptability of the teleconference to residents at both institutions. Evidence from other programs is encouraging with high acceptability and comparable efficacy for students both on site and off site [5] [9]–[13]. This evidence is limited to programs that offer distance learning within the same country and often with participants from the same institutions at different sites. Evaluations of programs such as ours, where there are substantial differences in culture, clinical environments and across much larger distances will be important to determine if findings will be similar. 6. Conclusion In summary, despite some challenges in connectivity we were able to develop and sustain a distance education program across two continents and two institutions for over two years at little cost. This program facilitated access to subspecialty education for residents in-training in a country where such access has been unavailable. It also provided the opportunity to spur interaction and clinical discussion among faculty, fellows, and residents from dramatically different clinical environments creating bilateral learning opportunities. Figure 1 Teleconference setting in Boston

6. Conclusion In summary, despite some challenges in connectivity we were able to develop and sustain a distance education program across two continents and two institutions for over two years at little cost. This program facilitated access to subspecialty education for residents in-training in a country where such access has been unavailable. It also provided the opportunity to spur interaction and clinical discussion among faculty, fellows, and residents from dramatically different clinical environments creating bilateral learning opportunities. Figure 1 Teleconference setting in Boston Figure 2 Teleconference in Mbarara, Uganda. Table 1 Lecture topics. Gynecology Oncology Loop Electricalsurgical Excisiion Procedure (LEEP) versus cryotherapy Cervical dysplasia Cervical cancer staging Basic principles of radiation oncology Basics of Colposcopy Human Papilloma Virus (HPV)-related diseases HPV and HPV vaccination Palliative care in low resource countries Management of a complex adnexal mass Maternal Fetal Medicine Electronic fetal monitoring Meconium Malaria in pregnancy Fetal Monitoring Management of Psychiatric Disease in Pregnancy General Obstetrics and Gynecology Surgical Anatomy Management of ectopic pregnancy Management of postpartum hemorrhage Vulvar diseases Laparoscopic surgery Management of incomplete abortion Urogyencology Management of vesicovaginal fistula Other Basic Obstetric Anesthesiology Building Stronger Teams in OB/GYN Simulation for Medical Education and Critical Care Table 2 Boston to Mbarara teleconferences: technology and challenges.

orrhage Vulvar diseases Laparoscopic surgery Management of incomplete abortion Urogyencology Management of vesicovaginal fistula Other Basic Obstetric Anesthesiology Building Stronger Teams in OB/GYN Simulation for Medical Education and Critical Care Table 2 Boston to Mbarara teleconferences: technology and challenges. Date Connection Device interface Problem Outcome

orrhage Vulvar diseases Laparoscopic surgery Management of incomplete abortion Urogyencology Management of vesicovaginal fistula Other Basic Obstetric Anesthesiology Building Stronger Teams in OB/GYN Simulation for Medical Education and Critical Care Table 2 Boston to Mbarara teleconferences: technology and challenges. Date Connection Device interface Problem Outcome MGH MRRH 06/2012 Skype Hospital PC Personal PC None No interruptions-full lecture 07/2012 Skype Hospital PC Personal PC Uganda Internet Interruptions-partial lecture 08/2012 Skype Personal PC Personal PC Uganda Internet Interruptions-full lecture 09/2012 Ventrillo Hospital PC Personal PC None No interruptions-Full lecture 10/2012 Ventrillo Hospital PC Personal PC None No interruptions-Full lecture 11/2012 Ventrillo Hospital PC Personal PC Unable to connect Separate lectures given 12/2012 Skype Smartphone Personal PC None Interruptions-full lecture 01/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 02/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 03/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 04/2013 Skype Personal PC Personal PC Internet connectivity Interruptions-full lecture 05/2013 Skype Personal PC Personal PC None Interruptions-full lecture 06/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 07/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 08/2013 Skype Smartphone Personal PC Internet connectivity Separate lectures 09/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 10/2013 Skype Smartphone Personal PC Internet connectivity Separate lectures 11/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 12/2013 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 1/2014 Skype Smartphone Personal PC none Interruptions-full lecture 2/2014 Skype Smartphone Personal PC Internet connectivity Separate lectures 4/2014 Skype Smartphone Personal PC Unable to connect Separate lectures 5/2014 Skype Smartphone Personal PC None No interruptions-full lecture 6/2014 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 7/2014 Skype Smartphone Personal PC None No interruptions-full lecture 9/2014 Skype Smartphone Personal PC None No interruptions-full lecture 10/2014 Skype Smartphone Personal PC None No interruptions-full lecture 11/2014 Skype Smartphone Personal PC None No interruptions-fu

rnet connectivity Interruptions-full lecture 7/2014 Skype Smartphone Personal PC None No interruptions-full lecture 9/2014 Skype Smartphone Personal PC None No interruptions-full lecture 10/2014 Skype Smartphone Personal PC None No interruptions-full lecture 11/2014 Skype Smartphone Personal PC None No interruptions-fu ll lecture 12/2014 Skype Smartphone Personal PC Internet connectivity Interruptions-full lecture 1/2015 Skype Smartphone Personal PC None No interruptions-full lecture

1. Introduction Recent survey identified the highest priority research questions pertaining to pathophysiology and treatments of pelvic organ prolapse (POP); according to it, mechanistic research on pelvic supportive structures, clinical trials to optimize outcomes after POP surgery and evidence-based quality measures for POP outcomes are among the major focus areas [1]. In vaginal prolapse surgery, about 20% of procedures are performed for recurrent POP. There are not many other fields with such poor surgical outcomes [2]. Many pelvic floor disorders, including POP, stress urinary incontinence (SUI), sexual dysfunction, congenital anomalies, and others, are clearly manifested in the mechanical properties of pelvic organs. Therefore, biomechanical mapping of a response to applied pressure or load within the pelvic floor opens new possibilities in biomechanical assessment and monitoring of pelvic floor conditions. The newly developed vaginal tactile imaging allows biomechanical mapping of the female pelvic floor including assessment of tissue elasticity, pelvic support, and pelvic muscle functions in high definition [3] [4] [5] [6]. Previously, we reported the intra- and inter-observer reproducibility of vaginal tactile imaging [7] and proposed interpretation of biomechanical mapping of the female pelvic floor [8]. The new mechanistic parameters were introduced for assessment of the vaginal [9] and pelvic floor conditions [10].

Many pelvic floor disorders, including POP, stress urinary incontinence (SUI), sexual dysfunction, congenital anomalies, and others, are clearly manifested in the mechanical properties of pelvic organs. Therefore, biomechanical mapping of a response to applied pressure or load within the pelvic floor opens new possibilities in biomechanical assessment and monitoring of pelvic floor conditions. The newly developed vaginal tactile imaging allows biomechanical mapping of the female pelvic floor including assessment of tissue elasticity, pelvic support, and pelvic muscle functions in high definition [3] [4] [5] [6]. Previously, we reported the intra- and inter-observer reproducibility of vaginal tactile imaging [7] and proposed interpretation of biomechanical mapping of the female pelvic floor [8]. The new mechanistic parameters were introduced for assessment of the vaginal [9] and pelvic floor conditions [10]. The objective of this study is to identify an extended set of Vaginal Tactile Imager (VTI) parameters which would comprehensively characterize the pelvic floor tissues, support structures and functions contributing to the POP development, and to establish their ranges for visualization of every biomechanical parameter acquired for specific patient conditions.

y an extended set of Vaginal Tactile Imager (VTI) parameters which would comprehensively characterize the pelvic floor tissues, support structures and functions contributing to the POP development, and to establish their ranges for visualization of every biomechanical parameter acquired for specific patient conditions. 2. Materials and Methods 2.1. Definitions Tactile Imaging is a medical imaging modality translating the sense of touch into a digital image [10]. The tactile image is a function of P (x, y, z), where P is the pressure on soft tissue surface under applied deformation and x, y and z are the coordinates where P was measured. The tactile image is a pressure map on which the direction of tissue deformation must be specified. Functional Tactile Imaging translates muscle activity into dynamic pressure pattern P (x, y, t) for an area of interest, where t is time and x and y are coordinates where pressure P was measured. It may include: 1) muscle voluntary contraction, 2) involuntary reflex contraction, 3) involuntary relaxation, and 4) specific maneuvers.

ctile Imaging translates muscle activity into dynamic pressure pattern P (x, y, t) for an area of interest, where t is time and x and y are coordinates where pressure P was measured. It may include: 1) muscle voluntary contraction, 2) involuntary reflex contraction, 3) involuntary relaxation, and 4) specific maneuvers. BiomechanicalMapping=TactileImaging+FunctionalTactileImaging A tactile imaging probe has a pressure sensor array mounted on its face that acts similar to human fingers during a clinical examination, deforming the soft tissue and detecting the resulting changes in the pressure pattern on the surface. The sensor head is moved over the surface of the tissue to be studied, and the pressure response is evaluated at multiple locations along the tissue. The results are used to generate 2D/3D images showing pressure distribution over the area of the tissue under study. Generally, an inverse problem solution for tactile image P (x, y, z) would allow the reconstruction of tissue elasticity distribution (E) as a function of the same coordinates E (x, y, z). Unfortunately, the inverse problem solution is hardly possible for most real objects because it is a non-linear and ill-posed problem. However, the tactile image P (x, y, z) per se reveals tissue or organ anatomy and elasticity distribution because it maintains the stress-strain relationship for deformed tissue [11] [12]. Thus the spatial gradients ∂P (x, y, z)/∂x, ∂P (x, y, z)/∂y, and ∂P (x, y, z)/∂z can be used in practice for soft tissue elasticity mapping, despite structural and anatomical variations [3].

e or organ anatomy and elasticity distribution because it maintains the stress-strain relationship for deformed tissue [11] [12]. Thus the spatial gradients ∂P (x, y, z)/∂x, ∂P (x, y, z)/∂y, and ∂P (x, y, z)/∂z can be used in practice for soft tissue elasticity mapping, despite structural and anatomical variations [3]. 2.2. Vaginal Tactile Imager The VTI, model 2S (Advanced Tactile Imaging, Inc., NJ), was used in all test procedures. The VTI probe, as shown in Figure 1, is equipped with 96 pressure (tactile) sensors spaced at 2.5 mm consecutively on both sides of the probe, an orientation sensor, and temperature controllers to provide the probe temperature close to a human body before the examination. During the clinical procedure, the probe is used to acquire pressure responses from two opposite vaginal walls along the vagina. The VTI data are sampled from the probe sensors and displayed on the VTI monitor in real time. The resulting pressure maps (tactile images) of the vagina integrate all the acquired pressure and positioning data for each of the pressure sensing elements. Additionally, the VTI records the dynamic contraction for pelvic floor muscles with resolution of 1 mm. A lubricating jelly is used for patient comfort and to provide reproducible boundary/contact conditions with deformed tissues.

all the acquired pressure and positioning data for each of the pressure sensing elements. Additionally, the VTI records the dynamic contraction for pelvic floor muscles with resolution of 1 mm. A lubricating jelly is used for patient comfort and to provide reproducible boundary/contact conditions with deformed tissues. This VTI probe allows 3 – 15 mm tissue deformation at the probe insertion (Tests 1), 20 – 45 mm tissue deformation at the probe elevation (Test 2), 5 – 7mm deformation at the probe rotation (Test 3) and recording of dynamic responses at pelvic muscle contractions (Tests 4 – 8). The probe maneuvers in Tests 1 – 3 allow accumulation of multiple pressure patterns from the tissue surface to compose an integrated tactile image for the investigated area using a proprietary image composition algorithm similar to the imaging of the prostate and breast [11] [12]. The spatial gradients ∂P (x, y)/∂y for anterior and posterior compartments are calculated within the acquired tactile images in test 1 and 2; y-coordinate is directed orthogonally from the vaginal channel, x-coordinate is located on the vaginal channel. The VTI software includes data analysis tools and reporting functions. It visualizes the anatomy, pressure maps, and calculates (automatically) 52 VTI parameters for eight test procedures. The VTI examination procedure consists of eight tests: 1) probe insertion, 2) elevation, 3) rotation, and 4) Valsalva maneuver, 5) voluntary muscle contraction, 6) voluntary muscle contraction (left versus right side), 7) involuntary relaxation, and 8) reflex muscle contraction (cough). Tests 1 – 5 and 7 – 8 provide data for anterior/posterior compartments; test 6 provides data for left/right sides (see Table 1).

tion, and 4) Valsalva maneuver, 5) voluntary muscle contraction, 6) voluntary muscle contraction (left versus right side), 7) involuntary relaxation, and 8) reflex muscle contraction (cough). Tests 1 – 5 and 7 – 8 provide data for anterior/posterior compartments; test 6 provides data for left/right sides (see Table 1). The VTI absolute measurement accuracy is as follows: ±0.2 kPa within 10 kPa range, ±0.5 kPa at 25 kPa, ±1.0 kPa at 60 kPa. The VTI relative pressure measurement accuracy lies in the range between ±0.05 kPa to ±0.1 kPa. The VTI pressure measurement resolution is 0.001 kPa. The VTI absolute measurement accuracy for probe orientation is ±0.5 degree and ±0.1˚C for measuring the temperature inside the probe on the surface of the pressure sensors. The VTI probe was calibrated immediately before every subject examination; it was cleaned and disinfected between the patients. 2.3. Biomechanical Mapping Parameters Table 2 lists 52 biomechanical parameters being calculated for every 96 participating subject based on VTI data recorded in tests 1 – 8. Anatomical assignment of the targeting/contributing pelvic structures into the specified parameters is based on already published data [8] [13] [14] [15] [16] [17].

Mapping Parameters Table 2 lists 52 biomechanical parameters being calculated for every 96 participating subject based on VTI data recorded in tests 1 – 8. Anatomical assignment of the targeting/contributing pelvic structures into the specified parameters is based on already published data [8] [13] [14] [15] [16] [17]. Figure 2 shows the locations of the measured VTI parameters for test 2 and 3 in mid-sagittal plane of the female pelvic floor. Location A1 represents pubic bone, A2 urethra, A3 anterior part connected with cervix, P1 perineal body (Level III support), P2 mid posterior part (Level II support), P3 upper posterior part (Level I support), S1 distal part, and S2 mid-vaginal part.

rs for test 2 and 3 in mid-sagittal plane of the female pelvic floor. Location A1 represents pubic bone, A2 urethra, A3 anterior part connected with cervix, P1 perineal body (Level III support), P2 mid posterior part (Level II support), P3 upper posterior part (Level I support), S1 distal part, and S2 mid-vaginal part. 2.4. Population Description 96 subjects with normal and POP conditions were included in the data analysis from multi-site observational, case-controlled studies with 243 enrolled subjects to date (clinical trials identifiers NCT02294383 and NCT02925585). Inclusion criteria: subject is female of 21 years or older, no prior pelvic floor surgery, and normal pelvic floor conditions or POP (any stage). Additional inclusion criteria for the analyzed data set were: all 8 VTI tests were completed, and case report and VTI data were verified. Exclusion criteria: active skin infection or ulceration within the vagina; presence of a vaginal septum; active cancer of the colon, rectum wall, cervix, vaginal, uterus or bladder; ongoing radiation therapy for pelvic cancer; impacted stool; significant pre-existing pelvic pain including levator ani syndrome, severe vaginismus or vulvadynia; severe hemorrhoids; significant circulatory or cardiac conditions that could cause excessive risk from the examination as determined by attending physician; and current pregnancy. The subject age, height, weight, and parity distribution data are present in Table 3. Prior to the VTI examination, a standard physical examination was performed, including a bimanual pelvic examination and Pelvic Organ Prolapse Quantification (POP-Q) [18]. The pelvic floor conditions were categorized by prolapse staging based on maximum stage from anterior, posterior, and uterine prolapse. Employing this approach, we found that 42 subjects had normal pelvic floor conditions (no POP, no SUI) and 54 had POP conditions (two with pelvic organ prolapse Stage I, 23 with Stage II, and 29 with Stage III). Among subjects with POP conditions we found 29 suffered from SUI, 10 had urinary urgency, and three had fecal incontinence. None of the analyzed subjects had a prior history of pelvic floor surgery. The basic demograpphic data (age, parity, weight) for both normal and POP groups are presented in Table 3. The clinical protocol was approved by the Institutional Review Board (Western IRB and local where required) and all women provided written informed consent to be enrolled into the study.

y of pelvic floor surgery. The basic demograpphic data (age, parity, weight) for both normal and POP groups are presented in Table 3. The clinical protocol was approved by the Institutional Review Board (Western IRB and local where required) and all women provided written informed consent to be enrolled into the study. This clinical research was done in compliance with the Health Insurance Portability and Accountability Act. The VTI examination data for eight ests (see Table 1) were obtained and recorded at the time of the scheduled routine urogynecologic visits. Total study workflow comprised of the following steps: 1) Recruiting women who routinely undergo vaginal examination as a part of their diagnostic treatment of concerned areas; 2) Acquisition of clinical diagnostic information related to the studied cases by standard clinical means; 3) Performing a VTI examination in lithotomic position; 4) Analyzing VTI data and assessment of the VTI parameters for pelvic floor characterization for normal versus POP conditions.

treatment of concerned areas; 2) Acquisition of clinical diagnostic information related to the studied cases by standard clinical means; 3) Performing a VTI examination in lithotomic position; 4) Analyzing VTI data and assessment of the VTI parameters for pelvic floor characterization for normal versus POP conditions. 2.5. Statistical Analysis 52 biomechanical parameters were calculated automatically per each of the 96 analyzed VTI examinations or cases (one VTI examination per each subjects). In some rare cases the parameter calculation required a manual correction of the anatomical location where the parameters must be calculated. Unpaired t-test (normal versus POP group) was completed per parameter to determine whether the parameter showed dependence on the pelvic floor conditions. For visual evaluation of the analyzed clinical data distributions we used notched boxplots [19] showing a confidence interval for the median value (central horizontal line), 25% and 75% quartiles. The spacing between the different parts of the box helps to compare variance. The boxplot also determines skewness (asymmetry) and outlier (cross). The intersection or divergence of confidence intervals for two patient samples is a visual analog of the t-test. The MATLAB (MathWorks, MA) statistical functions were used for the data analysis. 3. Results First, the VTI visual data for all eight tests are displayed in Figures 3–10 to illustrate the approach and location used in calculating the biomechanical parameters.

2.5. Statistical Analysis 52 biomechanical parameters were calculated automatically per each of the 96 analyzed VTI examinations or cases (one VTI examination per each subjects). In some rare cases the parameter calculation required a manual correction of the anatomical location where the parameters must be calculated. Unpaired t-test (normal versus POP group) was completed per parameter to determine whether the parameter showed dependence on the pelvic floor conditions. For visual evaluation of the analyzed clinical data distributions we used notched boxplots [19] showing a confidence interval for the median value (central horizontal line), 25% and 75% quartiles. The spacing between the different parts of the box helps to compare variance. The boxplot also determines skewness (asymmetry) and outlier (cross). The intersection or divergence of confidence intervals for two patient samples is a visual analog of the t-test. The MATLAB (MathWorks, MA) statistical functions were used for the data analysis. 3. Results First, the VTI visual data for all eight tests are displayed in Figures 3–10 to illustrate the approach and location used in calculating the biomechanical parameters. Figure 3 provides an example of VTI Test 1 results. Figure 4 presents Test 2 results for another subject. The same locations specified in Test 2 for capturing pressure values (parameters 7 – 12 in Table 2) are used for calculation of pressure gradients (parameters 13 – 18 in Table 2). Figure 5 presents Test 3 results for another subject. Test 3 provides 6 pressure values (parameters 19 – 24 in Table 2).

Figure 3 provides an example of VTI Test 1 results. Figure 4 presents Test 2 results for another subject. The same locations specified in Test 2 for capturing pressure values (parameters 7 – 12 in Table 2) are used for calculation of pressure gradients (parameters 13 – 18 in Table 2). Figure 5 presents Test 3 results for another subject. Test 3 provides 6 pressure values (parameters 19 – 24 in Table 2). Figure 6 shows the approach for VTI capturing parameter dL_a (see parameter 27 in Table 2) and dL_p (see parameter 30 in Table 2)—displacements of the maximum pressure peaks in anterior and posterior compartments in Test 4. It also illustrates the approach for VTI capturing parameter dPmax_a (see parameter 26 in Table 2) and dPmax_p (see parameter 29 in Table 2)—changes of maximum pressure peaks at Valsalva maneuver. Please pay attention to the measured dL_a and dL_p which have different sign/direction for this specific subject. Figure 7 illustrates the approach for VTI capturing parameter dPmax_a (see parameter 32 in Table 2) and dPmax_p (see parameter 35 in Table 2)—changes of maximum pressure peaks at voluntary muscles contractions in Test 7. Three contractive peaks are observed in the posterior compartment which are described as originating from puboperineal, puborectal, and pubovaginal muscles. The contractive changes for these 3 posterior peaks have different value and separated along the vagina for this specific subject.

muscles contractions in Test 7. Three contractive peaks are observed in the posterior compartment which are described as originating from puboperineal, puborectal, and pubovaginal muscles. The contractive changes for these 3 posterior peaks have different value and separated along the vagina for this specific subject. Figure 8 illustrates the approach for VTI capturing parameter dPmax_r (see parameter 38 in Table 2) and dPmax_l (see parameter 41 in Table 2)—changes of maximum pressure peaks at voluntary muscles contractions in the right and left vaginal compartments in Test 6. Two contractive peaks are observed per compartment which are identified as puborectal and pubovaginal muscle contractions. The contractive changes for the two sides have differences and are separated along the vagina in the left compartment for this specific subject. Figure 9 illustrates the approach for VTI capturing parameters dPdt_a, dpcdt_a (see parameter 43, 44 in Table 2) and dPdt_p, dpcdt_p (see parameter 45, 46 in Table 2)—absolute and relative (in %) slopes approximated by the white dashed lines for anterior and posterior compartments within three seconds in Test 7. The VTI software captures the relaxation at a location with maximum pressure and calculates the slope in time for this fixed location in the vagina.

meter 45, 46 in Table 2)—absolute and relative (in %) slopes approximated by the white dashed lines for anterior and posterior compartments within three seconds in Test 7. The VTI software captures the relaxation at a location with maximum pressure and calculates the slope in time for this fixed location in the vagina. Figure 10 shows the approach for VTI capturing parameter dL_a (see parameter 49 in Table 2) and dL_p (see parameter 52 in Table 2)—displacement of the maximum pressure peaks in anterior and posterior compartments during the reflex (involuntary) muscle contraction (cough) in Test 8. It also illustrates the approach for VTI capturing parameter dPmax_a (see parameter 48 in Table 2) and dPmax_p (see parameter 51 in Table 2)—changes of maximum pressure peaks at the reflex contraction. Please note that the measured dL_a = 0 mm and dL_p = +15 mm for this specific subject. Table 3 displays the calculated statistics (hypothesis testing outcome H- and p-value) for POP versus normal (Norm) conditions, average (Aver) values for 52 biomechanical parameters, standard deviations (SD), and the ranges (Min, Max) for both POP group (54 subjects) and normal group (42 subjects). Table 4 presents the calculated statistics (hypothesis testing outcome H- and p-value) for POP versus normal (Norm) conditions, average (Aver) values for 52 biomechanical parameters, standard deviations (SD), and the ranges (Min, Max) for both POP group (44 subjects) and normal group (39 subjects) post the age equalization (alignment) of the groups.

statistics (hypothesis testing outcome H- and p-value) for POP versus normal (Norm) conditions, average (Aver) values for 52 biomechanical parameters, standard deviations (SD), and the ranges (Min, Max) for both POP group (44 subjects) and normal group (39 subjects) post the age equalization (alignment) of the groups. Table 5 presents the calculated statistics (hypothesis testing outcome H- and p-value) for POP versus normal (Norm) conditions, average (Aver) values for 52 biomechanical parameters, standard deviations (SD), and the ranges (Min, Max) for both POP group (42 subjects), and normal group (31 subjects) after the parity and age equalization of the groups.

statistics (hypothesis testing outcome H- and p-value) for POP versus normal (Norm) conditions, average (Aver) values for 52 biomechanical parameters, standard deviations (SD), and the ranges (Min, Max) for both POP group (42 subjects), and normal group (31 subjects) after the parity and age equalization of the groups. The t-tests for the POP group of 54 subjects versus a normal group of 42 subjects demonstrate that 33 out of 52 parameters have statistically significant differences between the groups and these parameters have the potential to be used for detection and description of POP conditions. The analyzed groups have the same subject height and weight distributions. At the same time, these primary analyzed groups have differences in age and parity (see Table 3). To explore the possible influence of these differences, both groups were equalized by age. The t-tests outcomes and the accompanying data for the POP group of 44 subjects versus the normal group of 39 subjects demonstrate that 30 of 52 parameters have statistically significant differences for the groups equalized by age (see Table 4). Furthermore, the primary groups were equalized by parity and age. The t-tests outcomes and the accompanying data for the POP group of 42 subjects versus the normal group of 31 subjects demonstrates that 29 of 52 parameters have statistically significant differences for the groups equalized by parity and age (see Table 5). Figure 11 displays the boxplots for selected parameters for POP versus Normal groups presented in Table 3.

The t-tests for the POP group of 54 subjects versus a normal group of 42 subjects demonstrate that 33 out of 52 parameters have statistically significant differences between the groups and these parameters have the potential to be used for detection and description of POP conditions. The analyzed groups have the same subject height and weight distributions. At the same time, these primary analyzed groups have differences in age and parity (see Table 3). To explore the possible influence of these differences, both groups were equalized by age. The t-tests outcomes and the accompanying data for the POP group of 44 subjects versus the normal group of 39 subjects demonstrate that 30 of 52 parameters have statistically significant differences for the groups equalized by age (see Table 4). Furthermore, the primary groups were equalized by parity and age. The t-tests outcomes and the accompanying data for the POP group of 42 subjects versus the normal group of 31 subjects demonstrates that 29 of 52 parameters have statistically significant differences for the groups equalized by parity and age (see Table 5). Figure 11 displays the boxplots for selected parameters for POP versus Normal groups presented in Table 3. 4. Discussion The results of this research are in agreement with previously reported data [3]-[10]; however, the current analysis includes the biggest VTI parameter set ever considered. 33 of 52 biomechanical parameters are identified as statistically significant sensitivity to POP versus normal pelvic conditions (see Table 3). Their average changes from 39.7% to 145% (82% in average). These changes with POP clearly outperform possible deviations related to VTI intra- and inter-operator variability which were found on an average of ±15.1% (intra-observer error) and ±18.4 (inter-observer error) [7]. These reproducibility errors have intrinsically value and sign by a chance, but we have identified statistically systematical parameter changes with the POP.

iations related to VTI intra- and inter-operator variability which were found on an average of ±15.1% (intra-observer error) and ±18.4 (inter-observer error) [7]. These reproducibility errors have intrinsically value and sign by a chance, but we have identified statistically systematical parameter changes with the POP. Test 1 provides six identified parameters (1, 2, 3, 4, 5, 6) related to tissue elasticity; their average values change from 40.8% to 145% for normal relative to POP conditions. Test 2 provides eight identified parameters (7, 8, 10, 11, 14, 15, 16, 17) related to the pelvic support structure; their average values change from 52.3% to 110.8% for normal relative to POP conditions. Test 3 provides five identified parameters (19, 20, 22, 23, 24) related to tissue elasticity; their average values change from 57.2% to 113.2% for normal relative to POP conditions. Test 4 provides one identified parameters (26) related to pelvic function; its value changes by 67.7 for normal relative to POP conditions. Test 5 provides six identified parameters (31, 32, 33, 34, 35, 36) related to pelvic function; their average values change from 39.7% to 82.1% for normal relative to POP conditions. Test 6 provides four identified parameters (38, 39, 41, 42) related to pelvic function; their average values change from 76.3% to 100.3% for normal relative to POP conditions. Test 7 provides two identified parameters (44, 46) related to pelvic function; their average values change from 50.2% to 103.0% for POP relative to normal conditions. Test 8 provides 1 identified parameter (48) related to pelvic function; its value changes by 69.6% for POP relative to normal conditions. In total, among the 33 identified POP diagnostic parameters, 11 parameters are related to tissue elasticity, 8 parameters are related to pelvic support structures, and 14 parameters are related for to pelvic functions.

er (48) related to pelvic function; its value changes by 69.6% for POP relative to normal conditions. In total, among the 33 identified POP diagnostic parameters, 11 parameters are related to tissue elasticity, 8 parameters are related to pelvic support structures, and 14 parameters are related for to pelvic functions. The analyzed groups of subjects have differences in age and parity as seen in Table 3. However, after these group equalization by age, 30 of 52 parameters are identified as statistically significant sensitivity to POP versus normal pelvic conditions (see Table 4). After these group equalization by parity and age, 29 of 52 parameters are identified as statistically significant sensitivity to POP versus normal pelvic conditions (see Table 5). It is important to note that the group with the normal pelvic conditions (no POP, no SUI) was composed of the visitors of urogynecological site; these patients may have some pelvic floor conditions that are not identified in this study. Possibly, the patients from the normal group have had pre-prolapse conditions which haven’t transformed yet into anatomically visible POP. This study reasonably proposes that if the normal group would be composed of 20 – 40 y.o. subjects with no history of consulting urogynecological clinics, more significant differences for the VTI parameters versus the POP group may be observed.

pse conditions which haven’t transformed yet into anatomically visible POP. This study reasonably proposes that if the normal group would be composed of 20 – 40 y.o. subjects with no history of consulting urogynecological clinics, more significant differences for the VTI parameters versus the POP group may be observed. The boxplots for selected parameter distributions in Figure 11 display (a) significant tissue elasticity changes with POP (see panels A and B), significant changes with POP in Level III and Level II supports (see panels C and D), but no change in Level I support under POP conditions (see panel E), significant changes in pelvic muscle contractive capabilities with POP (see panels F and G), and significant changes in pelvic muscle relaxation, which related with muscle innervations, with POP development (see panel H). The next step (which falls beyond the purview of this article) with these biomechanical parameters may include 1) an insight into POP classes (anterior vs posterior vs uterine), 2) analysis for continence versus incontinence conditions, 3) analysis of urogynecological surgical outcomes as a whole as well as per specific surgical procedure, 4) combining the VTI data with urodynamics, ultrasound, and MRI data, 5) to use the VTI and other clinically related data for predicative modeling of outcomes for conservative and surgical procedures (personalized predictive treatment), and 6) maintaining the objective history of biomechanical transformation of the patient pelvic floor.

TI data with urodynamics, ultrasound, and MRI data, 5) to use the VTI and other clinically related data for predicative modeling of outcomes for conservative and surgical procedures (personalized predictive treatment), and 6) maintaining the objective history of biomechanical transformation of the patient pelvic floor. One of the strengths of this study is that the current VTI offers an opportunity to assess the tissue elasticity, pelvic support structure, and pelvic function (muscle and ligaments) in high definition along the entire length of the anterior, posterior, and lateral walls at rest, with applied deflection pressures and with pelvic muscle contractions. All 52 parameters are calculated automatically in real-time. This allows a large body of measurements to evaluate individual variations in support defects as well as identify specific problematic structures. In addition, the technology provides the opportunity to measure pelvic floor muscle strength at specific locations along the vaginal wall and helps correlate the relative contributions to measured tissue properties. These measurements may provide insight into the functional contribution or relationships between support tissues and the underlying muscle support. Because VTI testing is relatively easy and inexpensive to obtain, post-treatment follow-up is available to evaluate the surgical impact on functional tissue properties and pelvic floor muscles. This may provide valuable outcome measurements for evaluating current and future treatments.

nd the underlying muscle support. Because VTI testing is relatively easy and inexpensive to obtain, post-treatment follow-up is available to evaluate the surgical impact on functional tissue properties and pelvic floor muscles. This may provide valuable outcome measurements for evaluating current and future treatments. One of the shortcomings of this study is its relatively small sample size. Further studies with larger patient population, investigating a variety of other pelvic floor conditions, and their use in the evaluation of interventions including physical therapy, conservative management options, and surgical correction are needed at this point to further explore the diagnostic values of the biomechanical mapping of the female pelvic floor. 5. Conclusion The biomechanical mapping of the female pelvic floor with the VTI provides a unique set of parameters characterizing POP versus normal conditions. These objectively measurable biomechanical transformations of pelvic tissues, support structures and functions under POP may be used in the future research and practical applications. Acknowledgements Research reported in this publication was supported by the National Institute On Aging of the National Institutes of Health under Awards Number R44AG034714 and SB1AG034714. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper. Disclosure Summary

Acknowledgements Research reported in this publication was supported by the National Institute On Aging of the National Institutes of Health under Awards Number R44AG034714 and SB1AG034714. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflicts of Interest The authors declare no conflicts of interest regarding the publication of this paper. Disclosure Summary V. Egorov: CEO and shareholder of Advanced Tactile Imaging, Inc. H. van Raalte: shareholder of Advanced Tactile Imaging, Inc. Figure 1. Vaginal probe. Pressure sensors are aligned on the outer surfaces of the probe (highlighted in the image). Figure 2. Locations of the VTI parameters within the pelvic floor. A1-A3 are in anterior compartment (Test 2), P1-P3 in posterior compartment (Test 2), and S1, S2 are in lateral compartments (left and right sides, Test 3). Figure 3. A tactile image acquired during the VTI probe insertion (Test 1) with anatomical landmarks and maximum pressure graphs (green lines, kPa) along anterior and posterior compartments. Figure 4. A tactile image acquired during the VTI probe elevation (Test 2) with anatomical landmarks and pressure values at specified locations (see A1-A3 and P1-P3 in Figure 2) along anterior and posterior compartments. The VTI software automatically identified all these 6 locations and shows the pressure values and gradient values (nor shown) for these locations.

TI probe elevation (Test 2) with anatomical landmarks and pressure values at specified locations (see A1-A3 and P1-P3 in Figure 2) along anterior and posterior compartments. The VTI software automatically identified all these 6 locations and shows the pressure values and gradient values (nor shown) for these locations. Figure 5. A tactile image acquired during the VTI probe rotation (Test 3) with pressure values at specified locations (see S1 and S2 in Figure 2). The VTI software automatically identified all these 3 locations and shows the pressure values (local maximums) for these locations. Figure 6. A dynamic pressure patterns acquired during the Valsalva maneuver for anterior and posterior compartments (Test 4). Figure 7. A dynamic pressure patterns acquired during the voluntary muscle contraction for anterior and posterior compartments (Test 5). Figure 8. A dynamic pressure patterns acquired during the voluntary muscle contraction for left and right vaginal compartments (Test 6). Figure 9. A dynamic pressure patterns acquired during the involuntary muscle relaxation for interior and posterior compartments (Test 7). Figure 10. A dynamic pressure patterns acquired during the reflex contraction (cough) for anterior and posterior compartments (Test 8). Figure 11. Boxplots A - F for selected biomechanical parameters for POP versus Normal groups from Table 3. Table 1. VTI Examination inlcudes 8 procedure tests.

Figure 9. A dynamic pressure patterns acquired during the involuntary muscle relaxation for interior and posterior compartments (Test 7). Figure 10. A dynamic pressure patterns acquired during the reflex contraction (cough) for anterior and posterior compartments (Test 8). Figure 11. Boxplots A - F for selected biomechanical parameters for POP versus Normal groups from Table 3. Table 1. VTI Examination inlcudes 8 procedure tests. Test No. Procedure Output Test 1 Probe insertion Tactile image for vaginal anterior and posterior compartments along the entire vagina (resistance, force, work, tissue elasticity). Test 2 Probe elevation Tactile image for anterior and posterior compartments which related to pelvic floor support structures (pressure value sand pressure gradients for specified/critical locations). Test 3 Probe rotation Tactile images for center and right sides along the entire vagina (force and pressure values for specified positions/locations). Test 4 Valsalva maneuver Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in force and pressure; pressure peak displacements). Test 5 Voluntary muscle contraction Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in force and pressure; maximum pressure values). Test 6 Voluntary muscle contraction (sides) Dynamic pressure response from opposite sides (center vs right) along the entire vagina (changes in force and pressure; maximum pressure values). Test 7 Involuntary relaxation Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in pressure). Test 8 Reflex muscle contraction (cough) Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in force and pressure; pressure peak displacements). Table 2. VTI biomechanical parameters.

pposite sites (anterior vs posterior) along the entire vagina (changes in pressure). Test 8 Reflex muscle contraction (cough) Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in force and pressure; pressure peak displacements). Table 2. VTI biomechanical parameters. No.

pposite sites (anterior vs posterior) along the entire vagina (changes in pressure). Test 8 Reflex muscle contraction (cough) Dynamic pressure response from opposite sites (anterior vs posterior) along the entire vagina (changes in force and pressure; pressure peak displacements). Table 2. VTI biomechanical parameters. No. VTI Test Parameters Abbreviation Units Parameter Description Parameter Interpretation Parameter Class Targeting/ Contributing Pelvic Structures 1 1 Fmax N Maximum value of force measured during the VTI probe insertion [9] Maximum resistance of anterior vs posterior widening; tissue elasticity at specified location (capability to resist to applied deformation) Maximum vaginal tissue elasticity at specified location Tissues behind the anterior and posterior vaginal walls at 3 – 15 mm depth 2 1 Work mJ Work completed during the probe insertion (Work = Force × Displacement)[9] Integral resistance of vaginal tissue (anterior and posterior) along the probe insertion Average vaginal tissue elasticity Tissues behind the anterior and posterior vaginal walls at 3 – 15 mm depth 3 1 Gmax_a kPa/mm Maximum value of anterior gradient (change of pressure per anterior wall displacement in orthogonal direction to the vaginal channel) Maximum value of tissue elasticity in anterior compartment behind the vaginal at specified location Maximum value of anterior tissue elasticity Tissues/structures in anterior compartment at 10 – 15 mm depth 4 1 Gmax_p kPa/mm Maximum value of posterior gradient (change of pressure per posterior wall displacement in orthogonal direction to the vaginal channel) Maximum value of tissue elasticity in posterior compartment behind the vaginal at specified location Maximum value of posterior tissue elasticity Tissues/structures in anterior compartment at 10 – 15 mm depth 5 1 Pmax_a kPa Maximum value of pressure per anterior wall along the vagina Maximum resistance of anterior tissue to vaginal wall deformation Anterior tissue elasticity Tissues/structures in anterior compartment 6 1 Pmax_p kPa Maximum value of pressure per posterior wall along the vagina Maximum resistance of posterior tissue to vaginal wall deformation Posterior tissue elasticity Tissues/structures in posterior compartment 7 2 P1max_a kPa Maximum pressure at thearea of pubic bone (anterior, A1 in Figure 2) Proximity of pubic bone to vaginal wall and perineal body strength Anatomic aspects and tissue elasticity Tissues between vagina and pubic bone; perineal body 8 2 P2max_a kPa Maximum pres

ity Tissues/structures in posterior compartment 7 2 P1max_a kPa Maximum pressure at thearea of pubic bone (anterior, A1 in Figure 2) Proximity of pubic bone to vaginal wall and perineal body strength Anatomic aspects and tissue elasticity Tissues between vagina and pubic bone; perineal body 8 2 P2max_a kPa Maximum pres sure at the area of urethra (anterior, A2 in Figure 2) Elasticity/mobility of urethra Anatomic aspects and tissue elasticity Urethra and surrounding tissues 9 2 P3max_a kPa Maximum pressure at the cervix area (anterior, A3 in Figure 2) Mobility of uterus and conditions of uterosacral Uterosacral and cardinal and cardinal ligaments Pelvic floor support Uterosacral and cardinal ligaments 10 2 P1max_p kPa Maximum pressure at the perineal body (posterioir, see P1 in Figure 2) Pressure feedback of Level III support Pelvic floor support Puboperineal, puborectal muscles 11 2 P2max_p kPa Maximum pressure at middle third of vagina (posterioir, see P2 in Figure 2) Pressure feedback of Level II support Pelvic floor support Pubovaginal, puboanal muscles 12 2 P3max_p kPa Maximum pressure at upper third of vagina (posterioir, see P3 in Figure 2) Pressure feedback of Level I support Pelvic floor support Iliococcygeal muscle, levator plate 13 2 G1max_a kPa/mm Maximum gradient at the area of pubic bone (anterior, see A1 in Figure 2) Vaginal elasticity at pubic bone area Anterior tissue elasticity Tissues between vagina and pubic bone; perineal body 14 2 G2max_a kPa/mm Maximum gradient at the area of urethra (anterior, see A2 in Figure 2) Mobility and elasticity of urethra Urethral tissue elasticity Urethra and surrounding tissues 15 2 G3max_a kPa/mm Maximum gradient at the cervix area (anterior, see A3 in Figure 2) Conditions of uterosacral and cardinal ligaments Pelvic floor support Uterosacral and cardinal ligaments 16 2 G1max_p kPa/mm Maximum gradient at the perineal body (posterioir, see P1 in Figure 2) Strength of Level III support (tissue deformation up to 25 mm) Pelvic floor support Puboperineal, puborectal muscles 17 2 G2max_p kPa/mm Maximum gradient at middle third of vagina (posterioir, see P2 in Figure 2) Strength of Level II support (tissue deformation up to 35 mm) Pelvic floor support Pubovaginal, puboanal muscles 18 2 G3max_p kPa/mm Maximum gradient at upper third of vagina (posterioir, see P3 in Figure 2) Strength of Level I support (tissue deformation up to 45 mm) Pelvic floor support Iliococcygeal muscle, levator plate 19 3 Pmax kPa Maximum pressure at vaginal w

up to 35 mm) Pelvic floor support Pubovaginal, puboanal muscles 18 2 G3max_p kPa/mm Maximum gradient at upper third of vagina (posterioir, see P3 in Figure 2) Strength of Level I support (tissue deformation up to 45 mm) Pelvic floor support Iliococcygeal muscle, levator plate 19 3 Pmax kPa Maximum pressure at vaginal w alls deformation by 7 mm [9] Hard tissue or tight vagina Vaginal tissue elasticity Tissues behind the vaginal walls at 5 – 7 mm depth 20 3 Fap N Force applied by anterior and posterior compartments to the probe[9] Integral strength of anterior and posterior compartments Vaginal tightening Tissues behind anterior/ posterior vaginal walls.

7 mm [9] Hard tissue or tight vagina Vaginal tissue elasticity Tissues behind the vaginal walls at 5 – 7 mm depth 20 3 Fap N Force applied by anterior and posterior compartments to the probe[9] Integral strength of anterior and posterior compartments Vaginal tightening Tissues behind anterior/ posterior vaginal walls. 21 3 Fs N Force applied by entire left and right sides of vagina to the probe[9] Integral strength of left and right sides of vagina Vaginal tightening Vaginal right/left walls and tissues behind them. 22 3 P1_l kPa Pressure response from a selected location (irregularity 1) at left side (see S1 in Figure 2) Hard tissue on left vaginal wall Irregularity on vaginal wall Tissue/muscle behind the vaginal walls on left side. 23 3 P2_l kPa Pressure response from a selected location (irregularity 2) at left side (see S2 in Figure 2) Hard tissue on left vaginal wall Irregularity on vaginal wall Tissue/muscle behind the vaginal walls on left side. 24 3 P3_r kPa Pressure response from a selected location (irregularity 3) at right sidevaginal (see S1 in Figure 2) Hard tissue on right wall Irregularity on vaginal wall Tissue/muscle behind the vaginal walls on right side. 25 4 dF_a N Integral force change in anterior compartment at Valsalva maneuver Pelvic function* at Valsalva maneuver Pelvic function Multiple pelvic muscle* 26 4 dPmax_a kPa Maximum pressure changt in anterior compartment at Valsalva maneuver. Pelvic function* at Valsalva maneuver Pelvic function Multiple pelvic muscle* 27 4 dL_a mm Displacement of the maximum pressure peak instructures* anterior compartment Mobility of anterior Valsalva maneuver Pelvic function Urethra, pubovaginal muscle; ligaments* 28 4 dF_p N Integral force change in posterior compartment at Valsalva maneuver Pelvic function* at Valsalva maneuver Pelvic function Multiple pelvic muscle* 29 4 dPmax_p kPa Maximum pressure change in posterior compartment at Valsalva maneuver.

Valsalva maneuver Pelvic function Urethra, pubovaginal muscle; ligaments* 28 4 dF_p N Integral force change in posterior compartment at Valsalva maneuver Pelvic function* at Valsalva maneuver Pelvic function Multiple pelvic muscle* 29 4 dPmax_p kPa Maximum pressure change in posterior compartment at Valsalva maneuver. Pelvic function* at Valsalva maneuver Pelvic function Multiple pelvic muscle* 30 4 dL_p mm Displacement of the maximum pressure peak instructures* Mobility of posterioir Valsalva Pelvic function Anorectal, puborectal, pubovaginal muscles;ligaments* 31 5 dF_a N Integral force change in anterior compartment at voluntary muscle contraction Integral contraction strength of pelvic muscles along the vagina Pelvic function Puboperineal, puborectal, pubovaginal and ilicoccygeal muscles; uretra 32 5 dPmax_a kPa Maximum pressure change in anterior compartment at voluntary muscle contraction Contraction strength of specified pelvic muscles Pelvic function Puboperineal, puborectal and pubovaginal muscles 33 5 Pmax_a kPa Maximum pressure value in anterior compartment at voluntary muscle contraction. Static and dynamic peak support of the pelvic floor Pelvic function Puboperineal and puborectal muscles* 34 5 dF_p N Integral force change in posterior compartment at voluntary muscle contraction Integral contraction strength of pelvic muscles along the vagina Pelvic function Puboperineal, puborectal, pubovaginal and ilicoccygeal muscles 35 5 dPmax_p kPa Maximum pressure change in posterior compartment at voluntary muscle contraction Contraction strength of pelvic muscles at specified location Pelvic function Puboperineal, puborectal and pubovaginal muscles 36 5 Pmax_p kPa Maximum pressure value in posterior compartment at voluntary muscle contraction.

35 5 dPmax_p kPa Maximum pressure change in posterior compartment at voluntary muscle contraction Contraction strength of pelvic muscles at specified location Pelvic function Puboperineal, puborectal and pubovaginal muscles 36 5 Pmax_p kPa Maximum pressure value in posterior compartment at voluntary muscle contraction. Static and dynamic peak support of the pelvic floor Pelvic function Puboperineal and puborectal muscles* 37 6 dF_r N Integral force change in right side at voluntary muscle contraction Integral contraction strength of pelvic muscles along the vagina Pelvic function Puboperineal, puborectal, and pubovaginal muscles 38 6 dPmax_r kPa Maximum pressure change in right side at voluntary muscle contraction Contraction strength of specific pelvic muscle Pelvic function Puboperineal or puborectal or pubovaginal muscles 39 6 Pmax_r kPa Maximum pressure value in right side at voluntary muscle contraction Specified pelvic muscle contractive capability and integrity Pelvic function Puboperineal or puborectal muscles 40 6 dF_l N Integral force change in left side at voluntary muscle contraction Integral contraction strength of pelvic muscles along the vagina Pelvic function Puboperineal, puborectal, and pubovaginal muscles 41 6 dPmax_l kPa Maximum pressure change in left side at voluntary muscle contraction Contraction strength of specific pelvic muscle Pelvic function Puboperineal or puborectal or pubovaginal muscles 42 6 Pmax_l kPa Maximum pressure value in left side at voluntary muscle contraction Specified pelvic muscle contractive capability and integrity Pelvic function Puboperineal or puborectal muscles 43 7 dPdt_a kPa/s Anterior absolute pressure change per second for maximum pressure at involuntary relaxation Innervation status of specified pelvic muscles Innervations status Levator ani muscles 44 7 dpcdt_a %/s Anterior relative pressure change per second for maximum pressure at involuntary relaxation Innervation status of specified pelvic muscles Innervations status Levator ani muscles 45 7 dPdt_p kPa/s Posterior absolute pressure change per second for maximum pressure at involuntary relaxation Innervation status of specified pelvic muscles Innervations status Levator ani muscles 46 7 dpcdt_p %/s Posterior relative pressure change per second for maximum pressure at involuntary relaxation Innervation status of specified pelvic muscles Innervations status Levator ani muscles 47 8 dF_a N Integral force change in anterior compartment at reflex pelvic muscle contraction

s status Levator ani muscles 46 7 dpcdt_p %/s Posterior relative pressure change per second for maximum pressure at involuntary relaxation Innervation status of specified pelvic muscles Innervations status Levator ani muscles 47 8 dF_a N Integral force change in anterior compartment at reflex pelvic muscle contraction (cough) Integral pelvic function* at reflex muscle contraction Pelvic function Multiple pelvic muscle* 48 8 dPmax_a kPa Maximum pressure change in anterior compartment at reflex pelvic muscle contraction (cough). Contraction strength of specified pelvic muscles Pelvic function Multiple pelvic muscle* 49 8 dL_a mm Displacement of the maximum pressure peak instructures* anterior compartment Mobility of anterior at reflex muscle contraction Pelvic function Urethra, pubovaginal muscle; ligaments* 50 8 dF_p N Integral force change in posterior compartment at reflex pelvic muscle contraction (cough) Integral pelvic function* at reflex muscle contraction Pelvic function Multiple pelvic muscle* 51 8 dPmax_p kPa Maximum pressure change in posterior compartment at reflex pelvic muscle contraction (cough). Contraction strength of specified pelvic muscles Pelvic function Multiple pelvic muscle* 52 8 dL_p mm Displacement of the maximum pressure peak instructures* posterior compartment Mobility of anterior at reflex muscle contraction Pelvic function Anorectal, puborectal and pubovaginal muscles; ligaments* * requires further interpretation. Table 3. Biomechanical Parameters: Prolapse (group of 54 subjects) versus Normal conditions (group of 42 subjects).

Contraction strength of specified pelvic muscles Pelvic function Multiple pelvic muscle* 49 8 dL_a mm Displacement of the maximum pressure peak instructures* anterior compartment Mobility of anterior at reflex muscle contraction Pelvic function Urethra, pubovaginal muscle; ligaments* 50 8 dF_p N Integral force change in posterior compartment at reflex pelvic muscle contraction (cough) Integral pelvic function* at reflex muscle contraction Pelvic function Multiple pelvic muscle* 51 8 dPmax_p kPa Maximum pressure change in posterior compartment at reflex pelvic muscle contraction (cough). Contraction strength of specified pelvic muscles Pelvic function Multiple pelvic muscle* 52 8 dL_p mm Displacement of the maximum pressure peak instructures* posterior compartment Mobility of anterior at reflex muscle contraction Pelvic function Anorectal, puborectal and pubovaginal muscles; ligaments* * requires further interpretation. Table 3. Biomechanical Parameters: Prolapse (group of 54 subjects) versus Normal conditions (group of 42 subjects). H p Units Aver POP Aver Norm SD POP SD Norm Min POP Min Norm Max POP Max Norm 0 0.828 cm 162.1 161.7 7.0 11.8 150 124 178 180 Height→ 0 0.311 Ib 157.4 151.2 31.8 26.4 105 110 243 200 Weight→ Age→ 1 0.005 y.o.

Table 3. Biomechanical Parameters: Prolapse (group of 54 subjects) versus Normal conditions (group of 42 subjects). H p Units Aver POP Aver Norm SD POP SD Norm Min POP Min Norm Max POP Max Norm 0 0.828 cm 162.1 161.7 7.0 11.8 150 124 178 180 Height→ 0 0.311 Ib 157.4 151.2 31.8 26.4 105 110 243 200 Weight→ Age→ 1 0.005 y.o. 59.0 51.2 10.6 16.0 37 26 82 90 Parity (P)→ 1 9 × 10−5 8.76E-05 - 2.5 1.4 1.1 1.0 0 0 6 3 Parameters number↓ Test↓ 1 1 1 5 × 10−5 N 0.73 1.24 0.44 0.74 0.22 0.23 2.74 4.05 2 1 1 0.001 mJ 30.06 42.34 13.91 22.46 9.50 4.50 68.10 96.30 3 1 1 2 × 10−4 kPa/mm 1.06 2.38 0.98 2.21 0.01 0.21 4.69 11.48 4 1 1 3 × 10−5 kPa/mm 0.77 1.57 0.70 1.08 0.02 0.17 4.02 5.06 5 1 1 1 × 10−7 kPa 16.09 39.43 11.30 26.78 3.10 6.00 52.10 145.50 6 1 1 8 × 10−6 kPa 11.70 22.64 8.06 14.33 3.20 5.10 46.70 60.90 7 2 1 0.001 kPa 18.54 28.24 13.76 15.13 1.60 4.50 57.10 70.50 8 2 1 3 × 10−6 kPa 6.00 11.85 3.43 7.72 1.90 0.10 20.10 31.80 9 2 0 0.082 kPa 5.88 8.51 6.66 8.03 0.80 0.00 50.30 40.70 10 2 1 2 × 10−5 kPa 7.11 13.80 4.44 9.65 1.60 2.10 20.50 53.60 11 2 1 1 × 10−4 kPa 5.52 9.54 3.10 6.41 1.90 1.60 15.30 29.20 12 2 0 0.620 kPa 6.30 6.94 5.01 7.62 0.70 0.40 29.60 44.00 13 2 0 0.254 kPa/mm 1.53 1.89 1.35 1.66 0.05 0.00 5.60 6.15 14 2 1 0.002 kPa/mm 0.38 0.79 0.35 0.84 0.03 0.00 1.70 3.95 15 2 1 0.010 kPa/mm 0.28 0.57 0.42 0.67 0.01 0.00 2.54 3.30 16 2 1 0.006 kPa/mm 0.35 0.73 0.38 0.90 0.01 0.06 2.11 4.91 17 2 1 0.004 kPa/mm 0.25 0.41 0.23 0.30 0.01 0.05 1.37 1.16 18 2 0 0.204 kPa/mm 0.31 0.44 0.35 0.60 0.05 0.00 1.80 3.48 19 3 1 2 × 10−6 kPa 16.67 32.16 14.19 15.51 4.16 5.04 62.40 69.40 20 3 1 1 × 10−5 N 2.54 4.03 1.27 1.91 0.78 1.26 6.55 9.15 21 3 0 0.716 N 1.24 1.19 0.64 0.83 0.17 0.10 3.12 3.49 22 3 1 3 × 10−5 kPa 4.71 9.21 3.66 6.36 1.00 2.30 22.10 30.70 23 3 1 5 × 10−4 kPa 3.14 4.93 1.65 3.14 0.90 0.80 10.10 12.90 24 3 1 5 × 10−7 kPa 4.62 9.86 2.77 6.43 1.10 2.40 12.40 25.50 25 4 0 0.157 N 1.52 1.24 0.96 0.80 0.17 0.31 4.64 3.78 26 4 1 0.039 kPa 6.34 10.63 8.30 10.81 −14.70 −4.30 40.90 40.20 27 4 0 0.071 mm 4.92 1.83 9.03 5.02 −19.00 −12.30 27.80 13.50 28 4 0 0.125 N 1.53 1.22 0.93 0.89 0.16 0.05 4.43 4.07 29 4 0 0.364 kPa 5.81 6.80 4.14 6.06 0.30 0.20 18.20 21.60 30 4 0 0.551 mm 3.14 2.39 5.92 5.52 −7.00 −10.00 22.80 18.80 31 5 1 0.007 N 1.09 1.57 0.73 0.99 0.13 0.30 3.12 5.89 32 5 1 0.043 kPa 15.94 22.27 14.57 15.44 0.30 1.80 56.50 80.40 33 5 1 7 × 10−5 kPa 24.95 40.86 18.12 19.26 3.80 4.40 76.00 99.40 34 5 1 0.001 N 1.15 1.84 0.77 1.27 0.20 0.31 3.53 5.87 35 5 1 1 × 10−5 kPa 7.72 1

0.551 mm 3.14 2.39 5.92 5.52 −7.00 −10.00 22.80 18.80 31 5 1 0.007 N 1.09 1.57 0.73 0.99 0.13 0.30 3.12 5.89 32 5 1 0.043 kPa 15.94 22.27 14.57 15.44 0.30 1.80 56.50 80.40 33 5 1 7 × 10−5 kPa 24.95 40.86 18.12 19.26 3.80 4.40 76.00 99.40 34 5 1 0.001 N 1.15 1.84 0.77 1.27 0.20 0.31 3.53 5.87 35 5 1 1 × 10−5 kPa 7.72 1 3.86 5.16 9.62 0.50 2.00 20.60 44.40 36 5 1 8 × 10−8 kPa 12.49 22.75 6.33 10.75 3.40 5.60 29.50 49.00 37 6 0 0.077 N 0.63 0.85 0.55 0.64 0.03 0.09 2.62 2.77 38 6 1 7 × 10−4 kPa 4.01 7.68 3.93 6.11 0.10 0.20 18.20 23.60 39 6 1 7 × 10−6 kPa 6.65 13.32 4.94 8.35 1.30 2.20 22.70 29.50 40 6 0 0.162 N 0.66 0.85 0.59 0.71 0.02 0.09 3.07 3.18 41 6 1 0.003 kPa 3.93 6.92 3.70 5.54 0.04 0.50 16.90 20.60 42 6 1 1 × 10−4 kPa 6.88 12.37 4.54 8.28 1.30 2.60 23.30 28.40 43 7 0 0.563 kPa/s −1.53 −1.29 2.09 1.63 −9.90 −6.44 0.07 0.72 44 7 1 0.001 %/s −6.36 −3.10 5.05 3.56 −21.90 −11.70 0.30 4.30 45 7 0 0.363 kPa/s −0.80 −1.01 0.88 1.35 −4.70 −6.10 −0.02 0.37 46 7 1 0.016 %/s −6.19 −4.11 4.07 3.84 −15.80 −13.00 −0.40 1.40 47 8 0 0.535 N 2.10 2.26 0.91 1.42 0.57 0.13 4.15 5.53 48 8 1 0.025 kPa 8.22 13.93 8.30 14.94 −23.80 −17.30 31.40 61.50 49 8 0 0.945 mm 6.64 6.52 9.08 4.71 −5.00 −3.50 27.50 17.30 50 8 0 0.901 N 2.28 2.25 1.03 1.50 0.66 0.43 4.96 5.19 51 8 0 0.097 kPa 9.06 11.41 4.79 8.22 2.20 1.00 21.80 27.30 52 8 0 0.342 mm 5.09 3.65 6.96 6.33 −10.00 −5.00 22.30 20.00 Table 4. Biomechanical parameters: prolapse (group of 44 subjects) versus Normal conditions (group of 39 subjects). Thesegroups are equalized by age.

3.86 5.16 9.62 0.50 2.00 20.60 44.40 36 5 1 8 × 10−8 kPa 12.49 22.75 6.33 10.75 3.40 5.60 29.50 49.00 37 6 0 0.077 N 0.63 0.85 0.55 0.64 0.03 0.09 2.62 2.77 38 6 1 7 × 10−4 kPa 4.01 7.68 3.93 6.11 0.10 0.20 18.20 23.60 39 6 1 7 × 10−6 kPa 6.65 13.32 4.94 8.35 1.30 2.20 22.70 29.50 40 6 0 0.162 N 0.66 0.85 0.59 0.71 0.02 0.09 3.07 3.18 41 6 1 0.003 kPa 3.93 6.92 3.70 5.54 0.04 0.50 16.90 20.60 42 6 1 1 × 10−4 kPa 6.88 12.37 4.54 8.28 1.30 2.60 23.30 28.40 43 7 0 0.563 kPa/s −1.53 −1.29 2.09 1.63 −9.90 −6.44 0.07 0.72 44 7 1 0.001 %/s −6.36 −3.10 5.05 3.56 −21.90 −11.70 0.30 4.30 45 7 0 0.363 kPa/s −0.80 −1.01 0.88 1.35 −4.70 −6.10 −0.02 0.37 46 7 1 0.016 %/s −6.19 −4.11 4.07 3.84 −15.80 −13.00 −0.40 1.40 47 8 0 0.535 N 2.10 2.26 0.91 1.42 0.57 0.13 4.15 5.53 48 8 1 0.025 kPa 8.22 13.93 8.30 14.94 −23.80 −17.30 31.40 61.50 49 8 0 0.945 mm 6.64 6.52 9.08 4.71 −5.00 −3.50 27.50 17.30 50 8 0 0.901 N 2.28 2.25 1.03 1.50 0.66 0.43 4.96 5.19 51 8 0 0.097 kPa 9.06 11.41 4.79 8.22 2.20 1.00 21.80 27.30 52 8 0 0.342 mm 5.09 3.65 6.96 6.33 −10.00 −5.00 22.30 20.00 Table 4. Biomechanical parameters: prolapse (group of 44 subjects) versus Normal conditions (group of 39 subjects). Thesegroups are equalized by age. H p Units Aver POP Aver Norm SD POP SD Norm MIn POP Min Norm Max POP Max Norm 0 0.862 cm 162.7 161.5 6.6 11.57 150 125 176 177 Height→ 0 0.318 Ib 159.4 153.3 28.4 27.7 105 110 233 200 Weight→ Age→ 0 0.342 y.o 54.1 53.9 7.8 15.3 37 31 65 90 Parity (P)→ 1 0.001 - 2.4 1.6 1.1 1.0 1 0 6 3 Parameters number↓ Test↓ 1 1 1 2 × 10−5 N 0.71 1.19 0.36 0.74 0.24 0.23 1.67 4.05 2 1 1 0.010 mJ 30.00 40.37 13.64 21.77 10.20 4.50 68.10 96.30 3 1 1 0.002 kPa/mm 1.11 2.27 0.99 2.23 0.01 0.21 4.69 11.48 4 1 1 2 × 10−4 kPa/mm 0.77 1.55 0.71 1.12 0.05 0.17 4.02 5.06 5 1 1 6 × 10−6 kPa 16.60 38.72 11.65 27.56 3.10 6.00 52.10 145.50 6 1 1 9 × 10−5 kPa 11.43 22.07 8.18 14.72 3.20 5.10 46.70 60.90 7 2 1 0.006 kPa 18.82 27.92 14.14 15.45 1.60 4.50 57.10 70.50 8 2 1 1 × 10−4 kPa 6.09 10.92 3.56 6.93 1.90 0.10 20.10 28.10 9 2 0 0.19456 kPa 6.06 8.29 7.28 8.23 1.70 0.00 50.30 40.70 10 2 1 0.001 kPa 7.55 12.64 4.52 8.95 2.10 2.10 20.50 53.60 11 2 1 2 × 10−4 kPa 5.28 9.07 2.71 5.76 1.90 1.60 13.50 29.20 12 2 0 0.466 kPa 5.54 6.24 3.74 4.96 0.70 0.70 24.00 26.30 13 2 0 0.177 kPa/mm 1.43 1.85 1.16 1.68 0.05 0.00 5.10 6.15 14 2 1 0.010 kPa/mm 0.37 0.73 0.34 0.83 0.03 0.00 1.70 3.95 15 2 1 0.045 kPa/mm 0.29 0.55 0.46 0.68 0.05 0.00 2.54 3.30 16 2 0 0.062 kPa/mm 0.37 0.65 0.41 0.89 0.01 0.06 2.11 4.91 17 2 1 0.001 kPa/mm 0.23 0.39 0.15 0.30 0.01 0.05 0.68 1.16 18 2 0 0.322 kPa/mm 0.29 0.37 0.36 0.38 0.05 0.00 1.80 1.89 19 3 1 1 × 10−4 kPa 17.40 30.98 15.09 15.24 4.30 5.04 62.40 69.40 20 3 1 3 × 10−4 N 2.54 3.82 1.28 1.79 0.78 1.26 6.55 9.15 21 3 0 0.478 N 1.25 1.13 0.68 0.82 0.17 0.10 3.12 3.49 22 3 1 0.001 kPa 4.93 8.34 3.96 5.33 1.00 2.30 22.10 24.80 23 3 1 0.011 kPa 3.23 4.56 1.78 2.79 0.90 0.80 10.10 11.80 24 3 1 4 × 10−5 kPa 4.72 9.24 2.82 6.25 1.10 2.40 12.40 25.50 25 4 1 0.047 N 1.58 1.16 1.02 0.68 0.17 0.31 4.64 3.11 26 4 0 0.152 kPa 6.56 9.74 9.07 9.97 −14.70 −4.30 40.90 40.20 27 4 0 0.145 mm 4.71 2.08 9.17 4.90 −19.00 −12.30 27.80 13.50 28 4 1 0.030 N 1.59 1.13 1.00 0.76 0.16 0.05 4.43 3.05 29 4 0 0.993 kPa 6.31 6.30 4.42 5.63 0.30 0.20 18.20 21.00 30 4 0 0.689 mm 2.76 2.23 5.77 5.52 −7.00 −10.00 22.80 18.80 31 5 0 0.110 N 1.16 1.42 0.76 0.71 0.13 0.30 3.12 3.14 32 5 0 0.469 kPa 17.85 20

20 27 4 0 0.145 mm 4.71 2.08 9.17 4.90 −19.00 −12.30 27.80 13.50 28 4 1 0.030 N 1.59 1.13 1.00 0.76 0.16 0.05 4.43 3.05 29 4 0 0.993 kPa 6.31 6.30 4.42 5.63 0.30 0.20 18.20 21.00 30 4 0 0.689 mm 2.76 2.23 5.77 5.52 −7.00 −10.00 22.80 18.80 31 5 0 0.110 N 1.16 1.42 0.76 0.71 0.13 0.30 3.12 3.14 32 5 0 0.469 kPa 17.85 20 .05 15.27 11.91 0.30 1.80 56.50 45.70 33 5 1 0.004 kPa 26.96 38.58 18.72 16.82 3.80 4.40 76.00 77.80 34 5 1 0.029 N 1.23 1.70 0.81 1.12 0.20 0.31 3.53 4.83 35 5 1 0.006 kPa 8.48 12.78 5.26 8.43 0.60 2.00 20.60 34.30 36 5 1 2 × 10−5 kPa 13.34 21.53 6.32 9.89 3.90 5.60 29.50 43.40 37 6 0 0.393 N 0.67 0.78 0.58 0.55 0.03 0.09 2.62 2.07 38 6 1 0.017 kPa 4.52 7.22 4.15 5.64 0.10 0.20 18.20 21.50 39 6 1 5 × 10−4 kPa 7.21 12.77 5.24 8.19 1.30 2.20 22.70 29.50 40 6 0 0.587 N 0.70 0.77 0.62 0.60 0.02 0.09 3.07 2.69 41 6 1 0.038 kPa 4.35 6.53 3.94 5.18 0.10 0.50 16.90 18.70 42 6 1 0.003 kPa 7.32 11.75 4.79 8.05 1.30 2.60 23.30 28.40 43 7 0 0.325 kPa/s −1.73 −1.27 2.24 1.68 −9.90 −6.44 0.07 0.72 44 7 1 0.001 %/s −6.53 −3.06 5.00 3.65 −21.90 −11.70 0.30 4.30 45 7 0 0.778 kPa/s −0.91 −0.98 0.92 1.37 −4.70 −6.10 −0.03 0.37 46 7 1 0.005 %/s −6.64 −4.04 4.04 3.89 −15.80 −13.00 −0.40 1.40 47 8 0 0.561 N 2.22 2.07 0.88 1.26 0.58 0.13 4.15 5.10 48 8 0 0.131 kPa 8.69 12.89 8.81 14.85 −23.80 −17.30 31.40 61.50 49 8 0 0.518 mm 7.64 6.44 9.23 4.80 −5.00 −3.50 27.50 17.30 50 8 0 0.180 N 2.45 2.07 1.02 1.38 0.66 0.43 4.96 5.19 51 8 0 0.674 kPa 9.96 10.57 4.77 7.74 2.20 1.00 21.80 27.30 52 8 0 0.289 mm 5.15 3.49 7.04 5.81 −10.00 −4.80 22.30 20.00 Table 5.

4.15 5.10 48 8 0 0.131 kPa 8.69 12.89 8.81 14.85 −23.80 −17.30 31.40 61.50 49 8 0 0.518 mm 7.64 6.44 9.23 4.80 −5.00 −3.50 27.50 17.30 50 8 0 0.180 N 2.45 2.07 1.02 1.38 0.66 0.43 4.96 5.19 51 8 0 0.674 kPa 9.96 10.57 4.77 7.74 2.20 1.00 21.80 27.30 52 8 0 0.289 mm 5.15 3.49 7.04 5.81 −10.00 −4.80 22.30 20.00 Table 5. Biomechanical parameters: Prolapse (group of 42 subjects) versus Normal conditions (group of 31 subjects). Thesegroups are equalized by parity and age.

4.15 5.10 48 8 0 0.131 kPa 8.69 12.89 8.81 14.85 −23.80 −17.30 31.40 61.50 49 8 0 0.518 mm 7.64 6.44 9.23 4.80 −5.00 −3.50 27.50 17.30 50 8 0 0.180 N 2.45 2.07 1.02 1.38 0.66 0.43 4.96 5.19 51 8 0 0.674 kPa 9.96 10.57 4.77 7.74 2.20 1.00 21.80 27.30 52 8 0 0.289 mm 5.15 3.49 7.04 5.81 −10.00 −4.80 22.30 20.00 Table 5. Biomechanical parameters: Prolapse (group of 42 subjects) versus Normal conditions (group of 31 subjects). Thesegroups are equalized by parity and age. H p Units Aver POP Aver Norm SD POP SD Norm MIn POP Min Norm Max POP Max Norm 0 0.988 cm 161.9 161.9 7.0 11.3 150 125 176 177 Height→ 0 0.191 Ib 162.2 152.9 32.9 27.2 105 110 243 200 Weight→ Age→ 0 0.123 y.o 57.7 53.1 9.0 16.1 37 26 75 90 Parity (P)→ 0 0.968 n/a 1.9 1.9 0.7 0.7 0 1 3 3 Parameters number↓ Test↓ 1 1 1 5 × 10−4 N 0.72 1.10 0.37 0.53 0.22 0.26 1.67 2.18 2 1 0 0.056 mJ 31.80 39.29 13.94 19.08 10.20 4.50 68.10 88.60 3 1 1 0.004 kPa/mm 1.09 2.01 1.01 1.66 0.01 0.21 4.69 7.56 4 1 1 0.002 kPa/mm 0.76 1.52 0.74 1.21 0.02 0.17 4.02 5.06 5 1 1 2 × 10−6 kPa 16.40 37.09 11.24 22.61 3.10 6.00 52.10 84.50 6 1 1 0.001 kPa 11.82 21.24 8.41 15.14 3.20 5.10 46.70 60.90 7 2 1 0.006 kPa 18.75 29.20 14.33 17.35 1.60 4.50 57.10 70.50 8 2 1 5 × 10−5 kPa 6.32 12.42 3.55 8.20 2.20 1.60 20.10 31.80 9 2 0 0.155 kPa 6.27 9.00 7.33 8.92 1.70 0.00 50.30 40.70 10 2 1 0.003 kPa 7.62 12.91 4.68 9.82 1.60 2.10 20.50 53.60 11 2 1 4 × 10−4 kPa 5.49 9.67 2.97 6.35 1.90 2.50 13.50 29.20 12 2 0 0.608 kPa 5.81 6.34 3.70 5.11 1.50 0.70 24.00 26.30 13 2 1 0.023 kPa/mm 1.41 2.23 1.24 1.79 0.05 0.00 5.60 6.15 14 2 1 4 × 10−4 kPa/mm 0.36 0.92 0.29 0.92 0.03 0.00 1.10 3.95 15 2 1 0.009 kPa/mm 0.27 0.63 0.38 0.76 0.05 0.00 2.54 3.30 16 2 0 0.057 kPa/mm 0.36 0.68 0.41 0.96 0.01 0.06 2.11 4.91 17 2 1 0.005 kPa/mm 0.23 0.38 0.18 0.26 0.01 0.05 0.73 1.16 18 2 0 0.339 kPa/mm 0.29 0.37 0.35 0.36 0.05 0.00 1.80 1.89 19 3 1 2 × 10−4 kPa 17.23 31.10 14.57 15.65 4.16 5.04 62.40 69.40 20 3 1 0.002 N 2.69 3.86 1.29 1.89 0.98 1.26 6.55 9.15 21 3 0 0.106 N 1.33 1.05 0.66 0.80 0.53 0.10 3.12 3.49 22 3 1 0.009 kPa 5.06 8.35 4.02 6.36 1.00 2.30 22.10 30.70 23 3 0 0.091 kPa 3.34 4.17 1.78 2.32 1.10 0.80 10.10 11.30 24 3 1 6 × 10−4 kPa 4.82 8.67 2.80 6.19 1.30 2.40 12.40 25.50 25 4 0 0.096 N 1.50 1.14 0.95 0.66 0.17 0.33 4.64 3.11 26 4 0 0.087 kPa 6.33 10.48 9.18 10.25 −14.70 −4.30 40.90 40.20 27 4 1 0.042 mm 5.02 1.31 8.26 4.99 −10.00 −12.30 27.80 13.50 28 4 0 0.112 N 1.51 1.16 0.93 0.78 0.16 0.05 4.43 3.05 29 4 0 0.495 kPa 5.91 6.77 4.43 5.86 0.30 0.20 18.20 21.00 30 4 0 0.433 mm 3.21 2.06 5.86 5.79 −3.00 −10.00 22.80 18.80 31 5 1 0.042 N 1.10 1.46 0.72 0.73 0.13 0.30 3.12 3.14 32 5 0 0.378 kPa 16.69 19.46 14.

1 0.042 mm 5.02 1.31 8.26 4.99 −10.00 −12.30 27.80 13.50 28 4 0 0.112 N 1.51 1.16 0.93 0.78 0.16 0.05 4.43 3.05 29 4 0 0.495 kPa 5.91 6.77 4.43 5.86 0.30 0.20 18.20 21.00 30 4 0 0.433 mm 3.21 2.06 5.86 5.79 −3.00 −10.00 22.80 18.80 31 5 1 0.042 N 1.10 1.46 0.72 0.73 0.13 0.30 3.12 3.14 32 5 0 0.378 kPa 16.69 19.46 14. 17 11.79 0.30 1.80 54.50 45.70 33 5 1 0.008 kPa 26.08 37.58 18.15 17.14 3.80 4.40 76.00 77.80 34 5 1 0.011 N 1.17 1.72 0.74 1.06 0.22 0.31 3.41 3.90 35 5 1 0.003 kPa 8.13 13.04 5.13 8.36 0.60 2.00 20.60 34.30 36 5 1 3 × 10−5 kPa 13.16 21.76 6.33 10.18 3.90 5.60 29.50 43.40 37 6 0 0.511 N 0.65 0.74 0.57 0.51 0.06 0.09 2.62 1.94 38 6 1 0.023 kPa 4.18 6.80 3.97 5.55 0.40 0.20 18.20 21.50 39 6 1 0.002 kPa 7.05 12.11 5.19 8.25 1.40 2.20 22.70 29.50 40 6 0 0.862 N 0.67 0.69 0.60 0.45 0.09 0.09 3.07 1.56 41 6 1 0.047 kPa 3.94 5.97 3.71 4.76 0.20 0.50 16.90 18.40 42 6 1 0.007 kPa 6.91 11.09 4.74 7.82 2.00 2.60 23.30 28.40 43 7 0 0.423 kPa/s −1.68 −1.29 2.26 1.68 −9.90 −6.44 0.07 0.51 44 7 1 0.001 %/s −6.69 −3.10 4.81 3.70 −21.90 −11.70 0.30 4.30 45 7 0 0.457 kPa/s −0.82 −1.03 0.88 1.47 −4.70 −6.10 −0.03 0.37 46 7 1 0.014 %/s −6.35 −3.96 3.91 3.94 −15.80 −13.00 −0.40 1.40 47 8 0 0.985 N 2.14 2.13 0.89 1.51 0.58 0.13 4.15 5.53 48 8 0 0.159 kPa 7.49 11.74 8.16 16.14 −23.80 −17.30 22.40 61.50 49 8 0 0.561 mm 7.65 6.39 9.80 5.16 −5.00 −3.50 27.50 17.30 50 8 0 0.465 N 2.36 2.12 1.04 1.56 0.66 0.43 4.96 5.19 51 8 0 0.430 kPa 9.36 10.70 4.98 8.78 2.20 1.00 21.80 27.30 52 8 0 0.057 mm 5.60 2.39 7.40 4.32 −10.00 −5.00 22.30 17.50

1. Introduction Preterm delivery is a leading cause of infant mortality and morbidity. It is estimated that annually about 15 million infants are born preterm worldwide [1]. Across 184 countries, the rate of preterm birth ranges from 5% to 18%, with almost 1 million children dying each year due to complications in preterm birth. Of the 14 million survivors per year, many face a lifetime of disability, including learning disorders, as well as visual and hearing impairments [2]. Long-term complications include cognitive disorders, behavioral problems, and cerebral palsy [3] [4] [5] [6]. These consequences imply devastating financial, social, and emotional effects on the parents and/or the affected children. In the US, the short-term hospital costs during the first year of life of preterm birth/low-birth-weight infants were estimated to be at $5.8 billion and the estimated annual societal economic burden in the US is, at a minimum, $26.2 billion [7]. Identifying women at risk for spontaneous preterm delivery (SPTD) remains an issue of paramount importance [8] [9] [10].

the first year of life of preterm birth/low-birth-weight infants were estimated to be at $5.8 billion and the estimated annual societal economic burden in the US is, at a minimum, $26.2 billion [7]. Identifying women at risk for spontaneous preterm delivery (SPTD) remains an issue of paramount importance [8] [9] [10]. Premature cervical softening and shortening may be considered an early mechanical failure that predisposes to preterm birth [11]. The digital cervical score [12] and Bishop score [13] as predictors of SPTD have demonstrated low diagnostic accuracy (61% - 68%) [14]. Even though numerous risk factors associated with SPTD have been identified in previous work, the ability to accurately predict when labor will occur remains elusive [15] [16] [17] [18]. In a well-regarded, large observational cohort study, serial transvaginal ultrasound cervical length and quantitative vaginal fetal fibronectin had low predictive accuracy for SPTD among nulliparous women [19]. Recent clinical findings suggest that cervical elastography may be a more useful test to predict preterm delivery [20]–[25]. Cervical elasticity may better assess microstructural changes in the cervix that predict preterm birth [26], and therefore, using cervical stiffness and length as part of a multiple marker screen to predict SPTD has the potential to improve on current methods. The objective of this study was to assess a new approach for cervical elasticity and length measurements based on the acquisition of stress-strain data by a cervix probe with tactile and ultrasound transducers in a clinical study.

Premature cervical softening and shortening may be considered an early mechanical failure that predisposes to preterm birth [11]. The digital cervical score [12] and Bishop score [13] as predictors of SPTD have demonstrated low diagnostic accuracy (61% - 68%) [14]. Even though numerous risk factors associated with SPTD have been identified in previous work, the ability to accurately predict when labor will occur remains elusive [15] [16] [17] [18]. In a well-regarded, large observational cohort study, serial transvaginal ultrasound cervical length and quantitative vaginal fetal fibronectin had low predictive accuracy for SPTD among nulliparous women [19]. Recent clinical findings suggest that cervical elastography may be a more useful test to predict preterm delivery [20]–[25]. Cervical elasticity may better assess microstructural changes in the cervix that predict preterm birth [26], and therefore, using cervical stiffness and length as part of a multiple marker screen to predict SPTD has the potential to improve on current methods. The objective of this study was to assess a new approach for cervical elasticity and length measurements based on the acquisition of stress-strain data by a cervix probe with tactile and ultrasound transducers in a clinical study. The pilot study was conducted with the use of a new cervical probe.

Premature cervical softening and shortening may be considered an early mechanical failure that predisposes to preterm birth [11]. The digital cervical score [12] and Bishop score [13] as predictors of SPTD have demonstrated low diagnostic accuracy (61% - 68%) [14]. Even though numerous risk factors associated with SPTD have been identified in previous work, the ability to accurately predict when labor will occur remains elusive [15] [16] [17] [18]. In a well-regarded, large observational cohort study, serial transvaginal ultrasound cervical length and quantitative vaginal fetal fibronectin had low predictive accuracy for SPTD among nulliparous women [19]. Recent clinical findings suggest that cervical elastography may be a more useful test to predict preterm delivery [20]–[25]. Cervical elasticity may better assess microstructural changes in the cervix that predict preterm birth [26], and therefore, using cervical stiffness and length as part of a multiple marker screen to predict SPTD has the potential to improve on current methods. The objective of this study was to assess a new approach for cervical elasticity and length measurements based on the acquisition of stress-strain data by a cervix probe with tactile and ultrasound transducers in a clinical study. The pilot study was conducted with the use of a new cervical probe. 2. Material and Methods 2.1. Study Design Between July 2017 and February 2018, 10 non-pregnant women and 10 pregnant women at 22 – 29 weeks of pregnancy were enrolled into a pilot clinical study and examined with the Cervix Monitor (CM). Written informed consent was obtained for this Institutional Review Board approved observational study (clinical trials identifiers ). The study objectives were: 1) to assess the device performance, 2) to assess the potential risks of the CM to pregnant women and fetuses, first with non-pregnant women followed by pregnant subjects, and 3) to verify the proposed data collection and examination techniques. The study with pregnant women followed the assessment of the risks of the CM examination procedure with non-pregnant women, as required by the Code of Federal Regulations, Title 45, §46.204(a). The inclusion criteria were that the participants had to be adult women, aged between 21 – 44 years, who were not pregnant for the first phase of the study, and pregnant in the second phase. Exclusion criteria included the presence of active cancer of the colon, rectum wall, cervix, vagina, uterus or bladder; ongoing or prior radiation therapy for abdominal or pelvic cancer; recent (less than 12 months) pelvic surgery; surgically absent uterus, rectum or bladder; significant circulatory or cardiac conditions that could cause excessive risk from the examination as determined by the attending physician; severe abdominal or pelvic adhesions preventing access to pertinent anatomy; known or suspected bleeding disorders; HIV or hepatitis B positive serology; warty lesions on the vulva; extensive varicose veins on the vulva; active skin infection or ulceration within the vagina/vulva (Herpes infection); and the presence of a vaginal septum. In addition, pregnant women deemed to be at a high-risk owing to a maternal or fetal condition were excluded. The participants’ age, height, weight, gestational age and parity distribution data were collected.

skin infection or ulceration within the vagina/vulva (Herpes infection); and the presence of a vaginal septum. In addition, pregnant women deemed to be at a high-risk owing to a maternal or fetal condition were excluded. The participants’ age, height, weight, gestational age and parity distribution data were collected. The total study workflow comprised of the following steps: 1) Recruiting women who routinely undergo gynecological or obstetric examination; 2) Acquisition of clinical information related to the studied cases by standard clinical means; 3) Performing a CM examination in a lithotomy position; and 4) Analyzing the CM data. All the participating women were asked to complete a questionnaire about their pain and comfort levels during the CM examination. 2.2. Cervix Monitor (CM) The Vaginal Tactile Imager (VTI) was initially developed as a biomechanical mapping device to assess vaginal and pelvic floor conditions [27] [28]. It allows the acquisition of cervical pressure response signals but does not allow cervical elasticity and length measurements. The CM has a drastically revised design in most of the engineering and clinical aspects.

ly developed as a biomechanical mapping device to assess vaginal and pelvic floor conditions [27] [28]. It allows the acquisition of cervical pressure response signals but does not allow cervical elasticity and length measurements. The CM has a drastically revised design in most of the engineering and clinical aspects. The CM was designed as a cart-based device with a medical grade touchscreen computer (Tangent, CA) and a detachable single-use cervix probe. The CM probe contains a tactile array with four sensors and an ultrasound transducer as shown in Figure 1. The ultrasound 3.0 MHz transducer, working in the pulse-echo mode with data acquisition resolution of 20 ns (50 MHz sample rate), measures 3.5 mm in diameter. Biocompatible, two-component silicones (NuSil Technology, CA) were employed to provide sensor assembly functionality, durability, stability and mechanical protection. A proprietary printed circuit board was designed to perform the dual functions of tactile signal acquisition and generation/acquisition of synchronized ultrasound signals. Its key features are to serve four tactile/pressure sensors and one ultrasound transducer at 100 data frames per second. Figure 1 presents the CM probe used in this study.

ircuit board was designed to perform the dual functions of tactile signal acquisition and generation/acquisition of synchronized ultrasound signals. Its key features are to serve four tactile/pressure sensors and one ultrasound transducer at 100 data frames per second. Figure 1 presents the CM probe used in this study. The pressure measurement noise level was below 25 Pa within the operational range of 40 kPa. The ultrasound transmitting pulses had a peak amplitude below 50 V, a length less than 1 μs, which provide acoustic power significantly below the limits established by the FDA for ultrasound emission in obstetrics: spatial-peak temporal-average Ispta = 94 (mW/cm2), spatial-peak pulse-average intensity Isppa = 190 (W/cm2), and mechanical index MI = 1.9. Medical grade 316 stainless steel, used in the production of surgical instruments, was used to fabricate the probe body (Figure 1). The CM software interface allows real-time observation of the cervical ultrasound signal as well as applied pressure. The ultrasound peak position for cervix internal os signal was calculated with the use of a signal envelope after the Gaussian complex wavelet filtering [29] at 3 MHz frequency. The cervical elasticity was calculated as a ratio of the applied load (stress) to the surface of the cervix from the CM probe to the resultant changes of the cervical length (strain). This approach was validated with the soft tissue models in bench testing and verification. Young’s modulus was calculated from the stress-strain data based on a semi-infinitive linear elastic model [30] [31].

tress) to the surface of the cervix from the CM probe to the resultant changes of the cervical length (strain). This approach was validated with the soft tissue models in bench testing and verification. Young’s modulus was calculated from the stress-strain data based on a semi-infinitive linear elastic model [30] [31]. 2.3. Examination Procedure The CM examination procedures followed the following steps: 1) Inserting the speculum into the vagina to provide appropriate visualization and access to the cervix; 2) Performing double CM measurements at 3, 6, 9, and 12 o’clock, specifying the probe tip location on cervix on the CM touchscreen display; 3) Reviewing of the measurement results (ultrasound reflected waves and applied loads); and 4) Removal of the probe and speculum from the vagina.

lization and access to the cervix; 2) Performing double CM measurements at 3, 6, 9, and 12 o’clock, specifying the probe tip location on cervix on the CM touchscreen display; 3) Reviewing of the measurement results (ultrasound reflected waves and applied loads); and 4) Removal of the probe and speculum from the vagina. 2.4. Statistical Analysis Measurement repeatability between two measurements at the same cervix sector on pregnant women was assessed with an intraclass correlation coefficient (ICC), as the correlation between any two measurements made on the same subject [32]. The following parameters were calculated as described by Bland and Altman [33]: 1) Bias (i.e., the mean of the proportionate difference [the difference between two CM measurements divided by the average value of two measurements]); 2) Precision (i.e., the standard deviation of the difference between the two measurements); and 3) Proportionate 95% limits of agreement (i.e., 1.96 times the standard deviation of the mean of the proportionate difference). The average values and standard deviations were calculated. Statistical analysis was performed with MATLAB version R2018a (MathWorks, MA).

of the difference between the two measurements); and 3) Proportionate 95% limits of agreement (i.e., 1.96 times the standard deviation of the mean of the proportionate difference). The average values and standard deviations were calculated. Statistical analysis was performed with MATLAB version R2018a (MathWorks, MA). 3. Results 3.1. Study with Non-Pregnant Women The study with non-pregnant women demonstrated reliable acquisition of the tactile signals. However, the ultrasound reflected signals had prolonged appearance; identification of the cervix internal os in these signals was not reliable. However, the signal post-processing of 8 of the 10 cases allowed the calculation of average cervical elasticity of 54 ± 17 kPa and length of 42 ± 13 mm. In 2 of the 10 cases, we found very low returned ultrasound signal amplitudes which offered no possibility for the elasticity assessment. These were expected difficulties with CM signal acquisition due to the cervical anatomy and positioning in non-pregnant women. The average pain level for 10 cases was 1.1 on the scale from 1 to 4 (1: none, 2: mildly painful, 3: painful, 4: severely painful). The comfort level was adjudged at 2.2 on the scale from 1 to 3, i.e. essentially similar to manual palpation (1: more comfortable than manual palpation, 2: the same, 3: less comfortable).

The average pain level for 10 cases was 1.1 on the scale from 1 to 4 (1: none, 2: mildly painful, 3: painful, 4: severely painful). The comfort level was adjudged at 2.2 on the scale from 1 to 3, i.e. essentially similar to manual palpation (1: more comfortable than manual palpation, 2: the same, 3: less comfortable). 3.2. Study with Pregnant Women Women at 22 – 29 weeks of pregnancy scheduled for a regular examination were considered eligible for the second part of the CM study enrollment. CM measurements were performed at an average gestational age of 25.4 ± 2.3 weeks (range, 22 – 29 weeks). The study of all ten women was successful. The recorded ultrasound signals had an identifiable peak amplitude reflected from the cervix’s internal os to allow reproducible measurement of ultrasound time-of-flight (see Figure 2). The peak position was calculated with the use of a signal envelope—see the light brown envelope line in the left panel of Figure 2. Figure 3 presents all CM data recorded for cases 1 – 10. The cervix map has four sectors; the results for one of ten cases (tissue elasticity and length distribution per four sectors) are shown in Figure 3. Average values and standard deviations (up/down bars) for cervical elasticity and length for 10 cases were calculated based on two measurements per 4 sectors (8 measurements per case); the values were 19.7 ± 15.4 kPa, and the length was 30.7 ± 6.6 mm. The average standard deviation for the 4 cervix sector measurements of elasticity was found as ±3.5 kPa and the length was ±3.4 mm.

cal elasticity and length for 10 cases were calculated based on two measurements per 4 sectors (8 measurements per case); the values were 19.7 ± 15.4 kPa, and the length was 30.7 ± 6.6 mm. The average standard deviation for the 4 cervix sector measurements of elasticity was found as ±3.5 kPa and the length was ±3.4 mm. Measurement repeatability between two measurements at the same cervix sector on pregnant women was assessed with an intraclass correlation coefficient (ICC), as the correlation between any two measurements made on the same subject [34]. ICC for cervix elasticity was found to be 0.97 and for a cervical length of 0.93 (see Figure 4). The bias and the 95% limits of agreement of the cervical elasticity measurement are 3.8% and −22.4% to +14.9%, the precision was 9.5% (see left panel in Figure 5). The bias and the 95% limits of agreement of the cervical length measurements are −1.6% and −13.3% to +16.5%, the precision was 7.6% (see right panel in Figure 5). The cervical length measurements with GE Voluson E8 (conventional ultrasound method) was not part of the protocol, but we obtained the measurements in 8 of 10 subjects that were studied. The Pearson correlation coefficient between cervical length measured with CM (average in sectors 1 and 3) and commercial ultrasound was found to be 0.48 for these 8 subjects; CM in average demonstrated 16.4% decrease versus conventional ultrasound in cervix length measurements.

ts in 8 of 10 subjects that were studied. The Pearson correlation coefficient between cervical length measured with CM (average in sectors 1 and 3) and commercial ultrasound was found to be 0.48 for these 8 subjects; CM in average demonstrated 16.4% decrease versus conventional ultrasound in cervix length measurements. The average level of pain reported by pregnant women was 1.7 on the scale from 1 to 4; the comfort level as 2.0 on a scale from 1 to 3. No adverse events with the CM were reported.

ts in 8 of 10 subjects that were studied. The Pearson correlation coefficient between cervical length measured with CM (average in sectors 1 and 3) and commercial ultrasound was found to be 0.48 for these 8 subjects; CM in average demonstrated 16.4% decrease versus conventional ultrasound in cervix length measurements. The average level of pain reported by pregnant women was 1.7 on the scale from 1 to 4; the comfort level as 2.0 on a scale from 1 to 3. No adverse events with the CM were reported. 4. Discussion The study has shown that the proposed tactile-ultrasound approach allows the measurement of cervical elasticity and length at an average gestational age of 25.4 ± 2.3 weeks with an acceptable precision of 9.5% and 7.6% consequently. It seems that the acceptable measurement reproducibility with the soft tissue elasticity measurements, being transformed into the Young’s module values, typically demonstrate a measurement accuracy of 3% - 15% and a measurement repeatability of 8% - 14% [31]. The cervical elasticity (average for 4 sectors) in this study ranged from 4.9 kPa to 58.6 kPa which constituted almost a 10-fold change from the lowest value. The 9.5% change (precision) from 32 kPa (average value in 4.9 kPa - 58.6 kPa range) amounts to 3.0 kPa, seems to be an acceptable proportion for elasticity measurement. The length of the cervix (average for 4 sectors) in this study ranged from 25.5 mm to 42.9 mm, which constitutes a 68% increase from the lower value. The critical changes in the cervical length are expected from 40 mm to 20 mm and 7.6% from the lower value will be 1.5 mm. The average standard deviation for the 4 cervix sector measurements seems to basically represent the variability by the cervix sectors which were found as ±3.5 kPa (elasticity) and ±3.4 mm (length). That means the reproducibility error of cervical length measurement of ±1.5 mm is capable to detect not only the length differences in pregnant women, but it allows resolution of the cervix anatomical variability by its 4 sectors. The +3.8% bias in the cervical elasticity measurement may be explained by the cervix strain hardening at the second measurement; the −1.6% bias in the cervical length measurement may cause cervix strain hysteresis at the second measurement (see Figure 5).

esolution of the cervix anatomical variability by its 4 sectors. The +3.8% bias in the cervical elasticity measurement may be explained by the cervix strain hardening at the second measurement; the −1.6% bias in the cervical length measurement may cause cervix strain hysteresis at the second measurement (see Figure 5). CM appeared to under measure the cervix length in comparison with the conventional ultrasound. This may be explained by cervix lengthen during the cervical measurement with commercial ultrasound because funneling may lessen. In contrary, measurement with CM may shorten the cervix because CM probe is targeted to compress cervix along its canal. It may be advantageous to measure with CM only through a portion of the cervix (whether it is anterior, posterior or lateral) because funneling may be removed, which can be dynamic, from the equation. It is important to note that absolute cervical length is not important for the cervical elasticity measurement. The average level of pain reported by women was 1.4 on the scale from 1 to 4; the comfort level as 2.1 on a scale from 1 to 3. A speculum is generally considered more uncomfortable that a manual digital exam; it is expected that the examination with the CM using the speculum was more uncomfortable.

CM appeared to under measure the cervix length in comparison with the conventional ultrasound. This may be explained by cervix lengthen during the cervical measurement with commercial ultrasound because funneling may lessen. In contrary, measurement with CM may shorten the cervix because CM probe is targeted to compress cervix along its canal. It may be advantageous to measure with CM only through a portion of the cervix (whether it is anterior, posterior or lateral) because funneling may be removed, which can be dynamic, from the equation. It is important to note that absolute cervical length is not important for the cervical elasticity measurement. The average level of pain reported by women was 1.4 on the scale from 1 to 4; the comfort level as 2.1 on a scale from 1 to 3. A speculum is generally considered more uncomfortable that a manual digital exam; it is expected that the examination with the CM using the speculum was more uncomfortable. In the last decade, a new technology named elastography, or elasticity imaging, for measuring and the visualizing the soft tissue viscoelastic characteristics, has emerged. Two approaches for cervical ultrasound elastography for quantitative determination of the physical properties of the cervix, namely, strain elastography and shear wave elastography have been developed. We identified 11 clinical studies in the last three years, which tested the hypothesis that cervical elastography may be useful in predicting preterm delivery [20]-[25] [34] [35] [36] [37] [38]. Of the eleven studies identified, seven used strain ultrasound [20]-[25] [35] and four used shear wave ultrasound [34] [36] [37] [38]. These studies assessed between 30 and 628 subjects with a total of 1901 women in the eleven studies. The data from these works suggest that assessment of cervical elasticity may be a more useful predictor than simply measuring the length of the cervix. Predictive sensitivity and specificity were found to be in the range from 59.0% and 86.0% [25] to 96.7% and 87.0% for the two approaches, respectively [37]. In all these publications, the investigators noted that they felt that significant additional work was necessary before the measurement procedure can be standardized and made reliable.

y and specificity were found to be in the range from 59.0% and 86.0% [25] to 96.7% and 87.0% for the two approaches, respectively [37]. In all these publications, the investigators noted that they felt that significant additional work was necessary before the measurement procedure can be standardized and made reliable. Strain ultrasound elastography determines only the relative values of tissue elasticity because the applied transducer pressure is unknown. The shear wave ultrasound elastography provides, in principle at least, a more objective description of tissue elasticity; however, the cervical elasticity is described as a shear wave speed [34] [36] [37] [38], but not as Young’s modulus which requires solution of the inverse mechanical problem in absence of stress data. There are several difficulties in using this approach: 1) cervical tissue heterogeneity implies distortions in the shear wave elasticity estimates, 2) placing a transducer next to the cervix is likely to cause a tissue deformation, thereby causing a non-controllable increase in the tissue stiffening, 3) any movement should be avoided for 3 – 5 seconds with a shear wave transducer, and 4) it requires a special transducer [39]. Both these ultrasound techniques require premium level, expensive ultrasound equipment [40] [41]. A much simpler and a less expensive aspiration technique has significant limitations in the context of biomechanical characterization of the cervix: a) uncertainty of the applied force, and b) only a small volume of tissue, primarily on the distal cervix, is tested [11] [42]. The proposed approach with the CM allows a) direct acquisition of stress-strain data, and b) direct assessment of the cervix with Young’s modulus [30] [31].

cal characterization of the cervix: a) uncertainty of the applied force, and b) only a small volume of tissue, primarily on the distal cervix, is tested [11] [42]. The proposed approach with the CM allows a) direct acquisition of stress-strain data, and b) direct assessment of the cervix with Young’s modulus [30] [31]. The clinical risk factors for SPTD include obstetric history (i.e., familial genetic predisposition, uterine malformation, previous preterm labor, previous cervical surgery) and other aspects of the current pregnancy (i.e., multifetal gestation, genital tract bleeding and/or infection, fetal malformation, shortened cervix) [43] [44]. Current tests for the SPTD can be divided into three general categories: 1) risk factors, 2) cervical conditions, and 3) biochemical testing. Combining all of the risk factors still falls short of 50% in the prediction of pregnancies that deliver preterm [43] [45]. The biochemical markers (gestation tissues, biological fluid analysis, proteomic data) for the prediction of SPTD do not achieve the desired diagnostic accuracy [46] [47] [48] [49][50]. The cervical length, measured in the routine second-trimester transvaginal ultrasonography, is not sensitive enough to predict SPTD [19] [51] [52].

al markers (gestation tissues, biological fluid analysis, proteomic data) for the prediction of SPTD do not achieve the desired diagnostic accuracy [46] [47] [48] [49][50]. The cervical length, measured in the routine second-trimester transvaginal ultrasonography, is not sensitive enough to predict SPTD [19] [51] [52]. Extensive remodeling is needed for the cervix to dilate and pass a fetus completely. The extracellular matrix of the cervix is primarily made up of tightly packed collagen bundles. Gradually, throughout the pregnancy, the composition of the cervix changes as the collagen density decreases, and the realignment and degradation of collagen cross-linking due to proteolytic enzymes, and an increase in the hyaluronic acid and water content. Cervical softening and distention result from these extracellular matrix compositional changes [53]. This pilot study provided 1) the assessment of the proposed approach to measure cervix elasticity and length, 2) the highlights of its strong and weak aspects to be addressed in the probe and procedures modifications, and 3) the basis for extended prospective development and validation clinical studies.

Extensive remodeling is needed for the cervix to dilate and pass a fetus completely. The extracellular matrix of the cervix is primarily made up of tightly packed collagen bundles. Gradually, throughout the pregnancy, the composition of the cervix changes as the collagen density decreases, and the realignment and degradation of collagen cross-linking due to proteolytic enzymes, and an increase in the hyaluronic acid and water content. Cervical softening and distention result from these extracellular matrix compositional changes [53]. This pilot study provided 1) the assessment of the proposed approach to measure cervix elasticity and length, 2) the highlights of its strong and weak aspects to be addressed in the probe and procedures modifications, and 3) the basis for extended prospective development and validation clinical studies. The strength of this study lies in the novel approach for cervical elasticity and length. The cervical elasticity receives quantification in terms of Young’s modulus from stress-strain data. We acknowledge that our study has some limitations. First, one needs to make sure that the reflected ultrasound signal came from the cervix internal oz; it will be the subject of further research. Second, it seems that a cervix elasticity model must be incorporated into the cervix elasticity calculation which will take in account the strain distribution along measured cervix compression (strain distribution) by the probe. Third, the total studies sample size in the study is relatively small. A study with a larger number of cases would enable us to explore the entire range of the cervical conditions and focus more on the prediction of SPTD at the gestational age when clinical procedures could prevent the SPTD. Yet, this is the first study using CM for this purpose, and the current study will serve as the basis to guide the design of future protocols.

enable us to explore the entire range of the cervical conditions and focus more on the prediction of SPTD at the gestational age when clinical procedures could prevent the SPTD. Yet, this is the first study using CM for this purpose, and the current study will serve as the basis to guide the design of future protocols. The novelty of this work is the implementation of the tactile and ultrasound transducers in one cervical probe and demonstration of feasibility of proposed approach for measurement of cervical elasticity and length on pregnant women. 5. Conclusion This study has demonstrated clinically acceptable measurement performance and reproducibility based on the acquisition of stress-strain data by tactile and ultrasound transducers. Availability of the stress-strain data allowed the computation of cervical elasticity and length. This approach has the potential to provide cervical markers in the prediction of spontaneous preterm delivery. Further research is needed. Acknowledgements Research grant R43HD090793 from Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), USA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflicts of Interest V. Egorov has submitted a patent application related to the described approach. The other authors declare no conflicts of interest regarding the publication of this paper.

Acknowledgements Research grant R43HD090793 from Eunice Kennedy Shriver National Institute of Child Health & Human Development (NICHD), USA. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health. Conflicts of Interest V. Egorov has submitted a patent application related to the described approach. The other authors declare no conflicts of interest regarding the publication of this paper. Figure 1. Cervical probe. (A) General view of the Cervix Monitor probe; (B) Probe tip with tactile and ultrasound transducers; (C) Probe positioning at cervical measurement. Figure 2. Measurement approach. (A) Ultrasound signals reflected from internal cervical os during cervix deformation by the probe; (B) Stress (pressure)-strain (compression) data recorded for 32 y.o. women at 25 week pregnancy. Figure 3. Cervical elasticity and length for 10 pregnant women measured by Cervix Monitor. Cervical Map with four sectors shows measurement results for subject number 10. Figure 4. Relationship for two measurements. Intraclass correlation coefficients (ICC) for two measurements of cervical elasticity (A) and length (B) by the same operator. Figure 5. Scatter plots of difference between two measurements. Bland-Altman scatter plot of the percentage difference between two measurements of cervical elasticity (A) and length (B) by the same operator. The solid lines represent the proportionate mean difference; the dashed lines represent the 95% limits of agreement.