Automatic segmentation of lower limb muscles from MR images of post-menopausal women based on deep learning and data augmentation.

Individual muscle segmentation is the process of partitioning medical images into regions representing each muscle. It can be used to isolate spatially structured quantitative muscle characteristics, such as volume, geometry, and the level of fat infiltration. These features are pivotal to measuring the state of muscle functional health and in tracking the response of the body to musculoskeletal and neuromusculoskeletal disorders. The gold standard approach to perform muscle segmentation requires manual processing of large numbers of images and is associated with significant operator repeatability issues and high time requirements. Deep learning-based techniques have been recently suggested to be capable of automating the process, which would catalyse research into the effects of musculoskeletal disorders on the muscular system. In this study, three convolutional neural networks were explored in their capacity to automatically segment twenty-three lower limb muscles from the hips, thigh, and calves from magnetic resonance images. The three neural networks (UNet, Attention UNet, and a novel Spatial Channel UNet) were trained independently with augmented images to segment 6 subjects and were able to segment the muscles with an average Relative Volume Error (RVE) between -8.6% and 2.9%, average Dice Similarity Coefficient (DSC) between 0.70 and 0.84, and average Hausdorff Distance (HD) between 12.2 and 46.5 mm, with performance dependent on both the subject and the network used. The trained convolutional neural networks designed, and data used in this study are openly available for use, either through re-training for other medical images, or application to automatically segment new T1-weighted lower limb magnetic resonance images captured with similar acquisition parameters.

Neonatal Hip Loading in Developmental Dysplasia: Finite Element Simulation of Proximal Femur Growth and Treatment.

Background: Abnormal prenatal hip joint loading can lead to compromised hip joint function. Early intervention is crucial for favorable outcomes. Purpose: This study investigates the impact of treatment timing (initiation and duration) on cartilage growth and ossification in the proximal femur of infants with developmental dysplasia of the hip, a condition affecting newborns. Methods: We used a mechanobiological model to simulate proximal femur growth during treatment durations of 3 months, 6 months, and a late-start treatment. Results: The findings indicate that the timing of treatment initiation is crucial, while a longer treatment duration does not contribute to improved morphological development of the hip joint. Conclusions: Mechanobiological models of growth can be used to develop treatments and therapies that correct loading conditions. Growing bone is particularly sensitive to loading conditions, and altered loading during growth can affect bone shape and functionality.

Cost-Effectiveness Analysis of CT-Based Finite Element Modeling for Osteoporosis Screening in Secondary Fracture Prevention: An Early Health Technology Assessment in the Netherlands.

Objective. To conduct cost-utility analyses for Computed Tomography To Strength (CT2S), a novel osteoporosis screening service, compared with dual-energy X-ray absorptiometry (DXA), treat all without screening, and no screening methods for Dutch postmenopausal women referred to fracture liaison service (FLS). CT2S uses CT scans to generate femur models and simulate sideways fall scenarios for bone strength assessment. Methods. Early health technology assessment (HTA) was adopted to evaluate CT2S as a novel osteoporosis screening tool for secondary fracture prevention. We constructed a 2-dimensional simulation model considering 4 strategies (no screening, treat all without screening, DXA, CT2S) together with screening intervals (5 y, 2 y), treatments (oral alendronate, zoledronic acid), and discount rate scenarios among Dutch women in 3 age groups (60s, 70s, and 80s). Strategy comparisons were based on incremental cost-effectiveness ratios (ICERs), considering an ICER below €20,000 per QALY gained as cost-effective in the Netherlands. Results. Under the base-case scenario, CT2S versus DXA had estimated ICERs of €41,200 and €14,083 per QALY gained for the 60s and 70s age groups, respectively. For the 80s age group, CT2S was more effective and less costly than DXA. Changing treatment from weekly oral alendronate to annual zoledronic acid substantially decreased CT2S versus DXA ICERs across all age groups. Setting the screening interval to 2 y increased CT2S versus DXA ICERs to €100,333, €55,571, and €15,750 per QALY gained for the 60s, 70s, and 80s age groups, respectively. In all simulated populations and scenarios, CT2S was cost-effective (in some cases dominant) compared with the treat all strategy and cost-saving (more effective and less costly) compared with no screening. Conclusion. CT2S was estimated to be potentially cost-effective in the 70s and 80s age groups considering the willingness-to-pay threshold of the Netherlands. This early HTA suggests CT2S as a potential novel osteoporosis screening tool for secondary fracture prevention. Highlights: For postmenopausal Dutch women who have been referred to the FLS, direct access to CT2S may be cost-effective compared with DXA for age groups 70s and 80s, when considering the ICER threshold of the Netherlands. This study positions CT2S as a potential novel osteoporosis-screening tool for secondary fracture prevention in the clinical setting.A shorter screening interval of 2 y increases the effectiveness of both screening strategies, but the ICER of CT2S compared with DXA also increased substantially, which made CT2S no longer cost-effective for the 70s age group; however, it remains cost-effective for individuals in their 80s.Annual zoledronic acid treatment with better adherence may contribute to a lower cost-effectiveness ratio when comparing CT2S to DXA screening and the treat all strategies for all age groups.

Inhibitory Effects of Mongolian Medicine Yihe-Tang on Continuous Darkness Induced Liver Steatosis in Zebrafish.

The constant dark induction (DD) causes lipid degeneration and nonalcoholic fatty liver disease (NAFLD) in zebrafish, which might be closely related to the imbalance of gut microbiota and require in-depth study. In this study, a total of 144 zebrafish were divided into four groups, including the control group, Yihe-Tang group, constant dark group, and constant dark + Yihe-Tang group, and were treated with constant darkness (except control and Yihe-Tang groups) for 21 days. The bodyweights of zebrafish were recorded after 8 d, 15 d, and 22 d. The sequencing analysis of gut microbiota, detection of liver histopathological changes, and comparison of lipid metabolism-related gene expression levels were performed on the 22nd day of the experiment. The results showed that the Yihe-Tang could inhibit the constant dark-induced increase in zebrafish weight and liver steatosis. As compared to the control group, the dark treatment could alter the composition of gut microbiota in zebrafish, increase the relative abundance of harmful bacteria, and decrease the Cetobacterium and Bacteroides to Firmicutes ratio in the intestines. The abundance of Proteobacteria in the constant dark + Yihe-Tang group was close to that in the control group and that of Fusobacteria and Cetobacterium increased, especially the Cetobacterium, which increased significantly. The constant dark treatment caused an abnormal expression of liver lipid-related genes, inhibited lipid metabolism, and promoted fat accumulation. However, the Yihe-Tang could restore these changes to the level of the control group. This study indicated that Yihe-Tang could restore the constant dark-induced liver lipid degeneration. We hypothesized that Cetobacterium could significantly inhibit steatosis.

Finite element analysis informed variable selection for femoral fracture risk prediction.

Logistic regression classification (LRC) is widely used to develop models to predict the risk of femoral fracture. LRC models based on areal bone mineral density (aBMD) alone are poor, with area under the receiver operator curve (AUROC) scores reported to be as low as 0.63. This has led to researchers investigating methods to extract further information from the image to increase performance. Recently, the use of active shape (ASM) and appearance models (AAM) have resulted in moderate improvements, but there is a risk that inclusion of too many modes will lead to overfitting. In addition, there are concerns that the effort required to extract the additional information does not justify the modest improvement in fracture risk prediction. This raises the question, are we reaching the limits of the information that can be extracted from an image? Finite element analysis was used in combination with active shape and appearance modelling to select variables to develop LRC models of fracture risk. Active shape and active appearance models were constructed based on a previously reported cohort of 94 post-menopausal Caucasian women (47 with and 47 without a fracture). T-tests were used to identify differences between the two groups for each mode of variation. Femur strength was predicted for two load cases, stance and a fall. Stepwise multi-variate linear regression was used to identify shape and appearance modes that were predictors of strength for the femurs in the training set. Femurs were also synthetically generated to explore the influence of the first 10 modes of the shape and appearance models. Identified modes of variation were then used to generate LRC models to predict fracture risk. Only 6 modes, 4 active appearance and 2 active shape modes, were identified that had a significant influence on predicted fracture strength. Of these, only two active appearance modes were needed to substantially improve the predictive mode performance (ΔAUROC = 0.080). The addition of 3 more modes (1 AAM and two ASM) further improved the performance of the classifier (ΔAUROC = 0.123). Further addition of modes did not result in any further substantial improvements. Based on these findings, it is suggested that we are reaching the limits of the information that can be extracted from an image to predict fracture risk.

Femoral neck strain prediction during level walking using a combined musculoskeletal and finite element model approach.

Recently, coupled musculoskeletal-finite element modelling approaches have emerged as a way to investigate femoral neck loading during various daily activities. Combining personalised gait data with finite element models will not only allow us to study changes in motion/movement, but also their effects on critical internal structures, such as the femur. However, previous studies have been hampered by the small sample size and the lack of fully personalised data in order to construct the coupled model. Therefore, the aim of this study was to build a pipeline for a fully personalised multiscale (body-organ level) model to investigate the strain levels at the femoral neck during a normal gait cycle. Five postmenopausal women were included in this study. The CT and MRI scans of the lower limb, and gait data were collected for all participants. Muscle forces derived from the body level musculoskeletal models were used as boundary constraints on the finite element femur models. Principal strains were estimated at the femoral neck region during a full gait cycle. Considerable variation was found in the predicted peak strain among individuals with mean peak first principal strain of 0.24% ± 0.11% and mean third principal strain of -0.29% ± 0.24%. For four individuals, two overall peaks of the maximum strains were found to occur when both feet were in contact with the floor, while one individual had one peak at the toe-off phase. Both the joint contact forces and the muscular forces were found to substantially influence the loading at the femoral neck. A higher correlation was found between the predicted peak strains and the gluteus medius (R2 ranged between 0.95 and 0.99) than the hip joint contact forces (R2 ranged between 0.63 and 0.96). Therefore, the current findings suggest that personal variations are substantial, and hence it is important to consider multiple subjects before deriving general conclusions for a target population.

Postnatal pelvic floor muscle stiffness measured by vaginal elastometry in women with obstetric anal sphincter injury: a pilot study.

INTRODUCTION AND HYPOTHESIS: Vaginal childbirth is associated with pelvic floor muscle (PFM) damage in a third of women. The biomechanics prediction, detection and management of PFM damage remain poorly understood. We sought in this pilot study to determine whether quantifying PFM stiffness postnatally by vaginal elastometry, in women attending a perineal trauma clinic (PTC) within 6 months of obstetric anal sphincter injury, correlates with their antecedent labour characteristics, pelvic floor muscle damage, or urinary/bowel/sexual symptoms, to inform future definitive prospective studies. METHODS: In this pilot study, we measured postnatal PFM stiffness by vaginal elastometry in 54 women. A subset of participants (n = 14) underwent magnetic resonance imaging (MRI) to define any levator ani (LA) muscle defects from vaginal childbirth. We investigated the association of PFM stiffness with demographics, labour and delivery characteristics, clinical features and MRI evidence of LA damage. RESULTS: Raised maternal BMI was associated with reduced pelvic floor stiffness (r = -0.4; p < 0.01). Higher stiffness values were associated with forceps delivery for delayed second stage of labour (n = 14) vs non-forceps vaginal delivery (n = 40; 630 ± 40 N/m vs 500 ± 30 N/m; p < 0.05), and a non-significant trend towards longer duration of the second stage of labour. Women with urinary, bowel or sexual symptoms (n = 37) demonstrated higher pelvic floor stiffness values than those without (570 ± 30 N/m vs 450 ± 40 N/m; p < 0.05). CONCLUSIONS: A history of delayed second stage of labour and forceps delivery was associated with higher PFM stiffness values in the postnatal period. Whether high pelvic muscle stiffness antenatally is a risk factor for instrumental vaginal delivery and LA avulsion is unknown.

The effect of boundary and loading conditions on patient classification using finite element predicted risk of fracture.

BACKGROUND: Osteoporotic proximal femoral fractures associated to falls are a major health burden in the ageing society. Recently, bone strength estimated by finite element models emerged as a feasible alternative to areal bone mineral density as a predictor of fracture risk. However, previous studies showed that the accuracy of patients' classification under their risk of fracture using finite element strength when simulating posterolateral falls is only marginally better than that of areal bone mineral density. Patients tend to fall in various directions: since the predicted strength is sensitive to the fall direction, a prediction based on certain fall directions might not be fully representative of the physical event. Hence, side fall boundary conditions may not be completely representing the physical event. METHODS: The effect of different side fall boundary and loading conditions on a retrospective cohort of 98 postmenopausal women was evaluated to test models' ability to discriminate fracture and control cases. Three different boundary conditions (Linear, Multi-point constraints and Contact model) were investigated under various anterolateral and posterolateral falls. FINDINGS: The stratification power estimated by the area under the receiver operating characteristic curve was highest for Contact model (0.82), followed by Multi-point constraints and Linear models with 0.80. Both Contact and MPC models predicted high strains in various locations of the proximal femur including the greater trochanter, which has rarely reported previously. INTERPRETATION: A full range of fall directions and less restrictive displacement constraints can improve the finite element strength ability to classify patients under their risk of fracture.

Correction to: Are CT-Based Finite Element Model Predictions of Femoral Bone Strength Clinically Useful?

The original version "Are CT-Based Finite Element Model Predictions of Femoral Bone Strengthening Clinically Useful?"

Are CT-Based Finite Element Model Predictions of Femoral Bone Strength Clinically Useful?

PURPOSE OF REVIEW: This study reviews the available literature to compare the accuracy of areal bone mineral density derived from dual X-ray absorptiometry (DXA-aBMD) and of subject-specific finite element models derived from quantitative computed tomography (QCT-SSFE) in predicting bone strength measured experimentally on cadaver bones, as well as their clinical accuracy both in terms of discrimination and prediction. Based on this information, some basic cost-effectiveness calculations are performed to explore the use of QCT-SSFE instead of DXA-aBMD in (a) clinical studies with femoral strength as endpoint, (b) predictor of the risk of hip fracture in low bone mass patients. RECENT FINDINGS: Recent improvements involving the use of smooth-boundary meshes, better anatomical referencing for proximal-only scans, multiple side-fall directions, and refined boundary conditions increase the predictive accuracy of QCT-SSFE. If these improvements are adopted, QCT-SSFE is always preferable over DXA-aBMD in clinical studies with femoral strength as the endpoint, while it is not yet cost-effective as a hip fracture risk predictor, although pathways that combine both QCT-SSFE and DXA-aBMD are promising.

Investigating the mechanical response of paediatric bone under bending and torsion using finite element analysis.

Fractures of bone account 25% of all paediatric injuries (Cooper et al. in J Bone Miner Res 19:1976-1981, 2004. https://doi.org/10.1359/JBMR.040902 ). These can be broadly categorised into accidental or inflicted injuries. The current clinical approach to distinguish between these two is based on the clinician's judgment, which can be subjective. Furthermore, there is a lack of studies on paediatric bone to provide evidence-based information on bone strength, mainly due to the difficulties of obtaining paediatric bone samples. There is a need to investigate the behaviour of children's bones under external loading. Such data will critically enhance our understanding of injury tolerance of paediatric bones under various loading conditions, related to injuries, such as bending and torsional loads. The aim of this study is therefore to investigate the response of paediatric femora under two types of loading conditions, bending and torsion, using a CT-based finite element approach, and to determine a relationship between bone strength and age/body mass of the child. Thirty post-mortem CT scans of children aged between 0 and 3 years old were used in this study. Two different boundary conditions were defined to represent four-point bending and pure torsional loads. The principal strain criterion was used to estimate the failure moment for both loading conditions. The results showed that failure moment of the bone increases with the age and mass of the child. The predicted failure moment for bending, external and internal torsions were 0.8-27.9, 1.0-31.4 and 1.0-30.7 Nm, respectively. To the authors' knowledge, this is the first report on infant bone strength in relation to age/mass using models developed from modern medical images. This technology may in future help advance the design of child, car restrain system, and more accurate computer models of children.

Modeling the second stage of labor.

Vaginal delivery is the primary cause of levator ani muscle injury, which is in turn the leading factor contributing to pelvic floor disorders including pelvic organ prolapse and urinary stress incontinence. Existing biomechanical models of childbirth have provided some understanding of pelvic floor function during delivery and have helped in the investigation of preventative strategies. The modeling frameworks for childbirth simulation are described with emphasis on (1) the recent advances in medical imaging quality and computational power; (2) improvements in the anatomical representation of the pelvic floor and fetal head; (3) more realistic boundary conditions for delivery; and (4) mechanical properties determined from experiments. Researchers have used these models to analyze childbirth mechanics and identify anatomical and mechanical features of the maternal pelvic floor, shape of the fetal head, and delivery techniques that potentially contribute to a difficult labor and higher risk of levator ani muscle injuries. The challenges to be addressed for these frameworks to be clinically useful are also discussed, including: (1) the improvements required to more accurately simulate the second stage of labor; (2) automatic segmentation of medical images and creation of customized computer models; (3) acquisition of individual specific pelvic floor mechanical properties; and (4) construction of statistical models for rapidly predicting the indices of childbirth mechanics. Within the next decade, it is likely that biomechanical models of childbirth will be sufficiently well informed and functional for personalized birth planning, and as educational tools for clinicians. WIREs Syst Biol Med 2016, 8:506-516. doi: 10.1002/wsbm.1351 For further resources related to this article, please visit the WIREs website.

Towards the generation of a parametric foot model using principal component analysis: A pilot study.

There have been many recent developments in patient-specific models with their potential to provide more information on the human pathophysiology and the increase in computational power. However they are not yet successfully applied in a clinical setting. One of the main challenges is the time required for mesh creation, which is difficult to automate. The development of parametric models by means of the Principle Component Analysis (PCA) represents an appealing solution. In this study PCA has been applied to the feet of a small cohort of diabetic and healthy subjects, in order to evaluate the possibility of developing parametric foot models, and to use them to identify variations and similarities between the two populations. Both the skin and the first metatarsal bones have been examined. Besides the reduced sample of subjects considered in the analysis, results demonstrated that the method adopted herein constitutes a first step towards the realization of a parametric foot models for biomechanical analysis. Furthermore the study showed that the methodology can successfully describe features in the foot, and evaluate differences in the shape of healthy and diabetic subjects.

Developing CT based computational models of pediatric femurs.

The mechanisms of fracture in infants and toddlers are not well understood. There have been very few studies on the mechanical properties of pediatric bones and their responses under fracture loading. A better understanding of fracture mechanisms in children will help elucidate both accidental and non-accidental injuries, as well as bone fragility diseases. The aim of this study is to develop in silico femoral models from CT scans to provide detailed quantitative information regarding the geometry and mechanical response of the femur, with the long term potential of investigating injury mechanisms. Fifteen anonymized QCT scans (aged 0-3 years) were collected and used to create personalized computational models of femurs. The elastic modulus of femur was illustrated at various ages. The models were also subjected to a series of four point bending simulations taking into account a range of loads perpendicular to the femoral shaft. The results showed that mid-shaft cross-section at birth appeared circular, but the diameter in the anteroposterior axis gradually increased with age. The density, and by implication modulus of elasticity at the mid-shaft became more differentiated with growth. Pediatric cortical bone with density close to the peak values found in adults was attained a few weeks after birth. The method is able to capture quantitative variations in geometries, material properties and mechanical responses, and has confirmed the rapid development of bone during the first few years of life using in silico models.

Large-scale finite element analysis of human cancellous bone tissue micro computer tomography data: a convergence study.

The complex geometry of cancellous bone tissue makes it difficult to generate finite element (FE) models. Only a few studies investigated the convergence behavior at the tissue scale using Cartesian meshes. However, these studies were not conducted according to an ideal patch test and the postelastic convergence behavior was not reported. In this study, the third principal strain and stress, and the displacement obtained from human micro finite element (microFE) models of lower resolutions were compared against the model of 19.5 µm as a reference, representing the original spatial resolution of microCT data. Uni-axial compression simulations using both linear-elastic and nonlinear constitutive equations were performed. The results showed a decrease in percentage difference in all three values as the element size decreased, with the displacement converging the fastest among the three. Simulations carried out using a nonlinear constitutive equation however, failed to show convergence for the third principal strains and stresses. It was concluded that at the tissue level, Cartesian meshes of human cancellous bone tissue were able to reach a converged solution in all three parameters investigated for linear simulation and only in displacement for nonlinear simulation. These parameters can be used as references in the future for studies in local biomechanical behavior of human cancellous bone tissues with linear simulation. The convergence behavior for human cancellous bone tissue using nonlinear constitutive equations needs further investigation.

Spatial Stroop interference occurs in the processing of radicals of ideogrammic compounds.

In this study, we investigated whether the meanings of radicals are involved in reading ideogrammic compounds in a spatial Stroop task. We found spatial Stroop effects of similar size for the simple characters [symbol: see text] ("up") and [symbol: see text] ("down") and for the complex characters [symbol: see text] ("nervous") and [symbol: see text] ("nervous"), which are ideogrammic compounds containing a radical [symbol: see text] or [symbol: see text], in Experiments 1 and 2. In Experiment 3, the spatial Stroop effects were also similar for the simple characters [symbol: see text] ("east") and [symbol: see text] ("west") and for the complex characters [symbol: see text] ("state") and [symbol: see text] ("spray"), which contain [symbol: see text] and [symbol: see text] as radicals. This outcome occurred regardless of whether the task was to identify the character (Exps. 1 and 3) or its location (Exp. 2). Thus, the spatial Stroop effect emerges in the processing of radicals just as it does for processing simple characters. This finding suggests that when reading ideogrammic compounds, (a) their radicals' meanings can be processed and (b) ideogrammic compounds have little or no influence on their radicals' semantic processing.

Anisotropic effects of the levator ani muscle during childbirth.

Pelvic floor dysfunction and pelvic organ prolapse have been associated with damage to the levator ani (LA) muscle, but the exact mechanisms linking them remain unknown. It has been postulated that factors such as vaginal birth and ageing may contribute to long-term, irreversible LA muscle damage. To investigate the biomechanical significance of the LA muscle during childbirth, researchers and clinicians have used finite element models to simulate the second stage of labour. One of the challenges is to represent the anisotropic mechanical response of the LA muscle. In this study, we investigated the effects of anisotropy by varying the relative stiffness between the fibre and the matrix components, whilst maintaining the same overall stress-strain response in the fibre direction. A foetal skull was passed through two pelvic floor models, which incorporated the LA muscle with different anisotropy ratios. Results showed a substantial decrease in the magnitude of the force required for delivery as the fibre anisotropy was increased. The anisotropy ratio markedly affected the mechanical response of the LA muscle during a simulated vaginal delivery. It is apparent that we need to obtain experimental data on muscle mechanics in order to better approximate the LA muscle mechanical properties for quantitative analysis. These models may advance our understanding of the injury mechanisms of pelvic floor during childbirth.

Effects of nonlinear muscle elasticity on pelvic floor mechanics during vaginal childbirth.

The role of the pelvic floor soft tissues during the second stage of labor, particularly the levator ani muscle, has attracted much interest recently. It has been postulated that the passage of the fetal head through the pelvis may cause excessive stretching of the levator ani muscle, which may lead to pelvic floor dysfunction and pelvic organ prolapse later in life. In order to study the complex biomechanical interactions between the levator ani muscle and the fetal head during the second stage of labor, finite element models have been developed for quantitative analysis of this process. In this study we have simulated vaginal delivery using individual-specific anatomical computer models of the pelvic floor interacting with a fetal head model with minimal restrictions placed upon its motion. Two constitutive relations were considered for the levator ani muscle (of exponential and neo-Hookean forms). For comparison purposes, the exponential relation was chosen to exhibit much greater stiffening at higher strains beyond the range of the experimental data. We demonstrated that increased nonlinearity in the elastic response of the tissues leads to considerably higher (56%) estimated force required for delivery, accompanied by a more homogeneous spatial distribution of maximum principal stretch ratio across the muscle. These results indicate that the form of constitutive relation beyond the presently available experimental data markedly affects the estimated function of the levator ani muscle during vaginal delivery, due to the large strains that occur. Further experimental data at higher strains are necessary in order to more reliably characterize the constitutive behavior required for modeling vaginal childbirth.

Modeling childbirth: elucidating the mechanisms of labor.

The process of childbirth and the mechanisms of labor have been studied for over a century, beginning with simple measurements of fetal skull and maternal pelvis dimensions. More recently, X-rays, ultrasound, and magnetic resonance imaging have been used to try and quantify the biomechanics of labor. With the development of computational technologies, biomechanical models have emerged as a quantitative analysis tool for modeling childbirth. These methods are well known for their capabilities to analyze function at the organ scale. This review provides an overview of the state-of-the-art finite element models of the mechanics of vaginal delivery, with detailed descriptions of the data sources, modeling frameworks, and results. We also discuss the limitations and improvements required in order for the models to be more accurate and clinically useful. Some of the major challenges include: modeling the complex geometry of the maternal pelvic floor muscles and fetal head motion during the second stage of labor; the lack of experimental data on the pelvic floor structures; and development of methods for clinical validation. To date, models have had limited success in helping clinicians understand possible factors leading to birth-induced pelvic floor muscle injuries and dysfunction. However, much more can be achieved with further development of these quantitative modeling frameworks, such as tools for birth planning and medical education.

Modelling childbirth: comparing athlete and non-athlete pelvic floor mechanics.

There is preliminary evidence that athletes involved in high-intensity sports for sustained periods have a higher probability of experiencing a prolonged second stage of labour compared to non-athletes. The mechanisms responsible for these differences are not clear, although it is postulated that muscle hypertrophy and increased muscle tone in athletes may contribute to difficulties in vaginal delivery. In order to test these hypotheses, we have constructed individual-specific finite element models of the female pelvic floor (one athlete and one non-athlete) and the fetal head to simulate vaginal delivery and enable quantitative analysis of the differences. The motion of the fetal head descending through the pelvic floor was modelled using finite deformation elasticity with contact mechanics. The force required to push the head was compared between the models and a 45% increase in peak force was observed in the athlete model compared to the non-athlete. In both cases, the overall maximum stretch was induced at the muscle insertions to the pubis. This is the beginning of a quantitative modelling framework that is intended to help clinicians assess the risk of natural versus caesarean birth by taking into account the possible mechanical response of pelvic floor muscles based on their size and activation patterns prior to labour.