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AIMS The aim of this project was to use codesign to develop a mobile application (app) for pelvic floor muscle training, with an intravaginal device (femfit®). The objective was to obtain user feedback to guide the design and development of a mobile app, consistent with the Mobile Application Rating Scale (MARS) framework. METHODS Twenty-six women (22-62 years) provided mobile app feedback using a Design Thinking framework and grounded theory approach. Four focus groups (2 h each) and two sets of one-to-one interviews (1 h each) were held from May 2018 to October 2019. The researchers debriefed the focus groups and interviews, and undertook analysis based on project objectives and key questions. RESULTS Recurring themes throughout the study aligned with sections of the MARS: (A) engagement (e.g., progress tracking), (B) functionality (e.g., intuitive interface), (C) aesthetics (e.g., smart graphics and colors), (D) information (e.g., clear, concise information). An internal preliminary assessment determined a MARS Quality Mean Score of 4.1 of 5 (engagement: 3.6 of 5; functionality: 4 of 5; aesthetics: 4.3 of 5: information: 4.4 of 5). CONCLUSIONS The development of the mobile app is on track to meet MARS requirements, and to be a fun, motivating app for women. Future work is required to investigate its efficacy.

The impact of surgery on pelvic floor muscle (PFM) function remains uncertain. There is a pressure differential along the length of the vagina, influenced by surrounding active and passive tissue structures, giving rise to a pressure profile. The aim of this study is to determine if an intravaginal pressure sensor, femfit®, can measure differences in pressure profiles before and after surgery for pelvic organ prolapse (POP). This pilot study includes 22 women undergoing POP surgery. Intravaginal pressure profiles were measured with femfit® pre- and post-surgery and differences tested using paired Student’s t-tests. Patients completed validated questionnaires for vaginal, bowel, and urinary incontinence symptoms pre- and post-POP surgery and a femfit® usability questionnaire. Sixteen sets of vaginal pressure data were analysed. The highest pressure generated was identified as the peak PFM pressure, whilst all sensor measurements provided a pressure profile. Intra-abdominal pressure (IAP) was measured by the most distal sensor, 8. On average, the difference between peak PFM pressure and IAP was significantly greater post-surgery (p

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 n = 14) vs non-forceps vaginal delivery (n = 40; 630 ± 40 N/m vs 500 ± 30 N/m; p n = 37) demonstrated higher pelvic floor stiffness values than those without (570 ± 30 N/m vs 450 ± 40 N/m; p 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.

Estimating the accuracy of subpixel image registration algorithms in practical experiments is important, yet challenging in many applications. The accuracy of these algorithms in camera-based systems is influenced not only by image content, but also camera noise. In this study, five experiments were designed to quantify the effect of changing camera settings on the image noise level, and consequently on the accuracy of subpixel displacement measurements. The systematic errors of the algorithms were measured separately to provide estimates of their contributions to the total measurement error. Experiments were conducted to measure the effects of random noise on the accuracy of displacement measurements. The results showed that the camera parameters directly influenced the image noise level, but the accuracy of algorithms in measuring displacements was not proportional to the image noise level. These results provide information on the quantitative relationship between camera settings and the registration error for a camera-based measurement system.

Traumatic brain injury (TBI) is a major public health problem. The majority of TBIs are in the form of mild TBI (also known as concussion) with sports-related concussion (SRC) receiving public attention in recent years.Here we have performed a systematic review of the literature on the use of Diffusion Tensor Imaging (DTI) on sports-related concussion and subconcussive injuries. Our review found different patterns of change in DTI parameters between concussed and subconcussed groups. The Fractional Anisotropy (FA) was either unchanged or increased for the concussion group, while the subconcussed group generally experienced a decrease in FA. A reverse pattern was observed for Mean Diffusivity (MD) - where the concussed group experienced a decrease in MD while the subconcussed group showed an increase in MD. However, in general, discrepancies were observed in the results reported in the literature - likely due to the huge variations in DTI acquisition parameters, and image processing and analysis methods used in these studies. This calls for more comprehensive and well-controlled studies in this field, including those that combine the advanced brain imaging with biomechancial modeling and kinematic sensors - to shed light on the underlying mechanisms behind the structural changes observed from the imaging studies.

4A three-dimensional finite element model of the mechanical and electrical behavior of the heart is being developed in a collaboration among Auckland University, New Zealand; the University of California at San Diego, U.S.; and McGill University, Canada. The equations of continuum mechanics from the theory of finite deformation elasticity are formulated in a prolate spheroidal coordinate system and solved using a combination of Galerkin and collocation techniques. The finite element basis functions used for the dependent and independent variables range from linear Lagrange to cubic Hermite, depending on the degree of spatial variation and continuity required for each variable. Orthotropic constitutive equations derived from biaxial testing of myocardial sheets are defined with respect to the microstructural axes of the tissue at the Gaussian quadrature points of the model. In particular, we define the muscle fiber orientation and the newly identified myocardial sheet axis orientation throughout the myocardium using finite element fields with nodal parameters fitted by least-squares to comprehensive measurements of these variables. Electrical activation of the model is achieved by solving the FitzHugh–Nagumo equations with collocation at fixed material points of the anatomical finite element model. Electrical propagation relies on an orthotropic conductivity tensor defined with respect to the local material axes. The mechanical constitutive laws for the Galerkin continuum mechanics model are (1) an orthotropic “pole–zero” law for the passive mechanical properties of myocardium and (2) a Wiener cascade model of the active mechanical properties of the muscle fibers. This chapter concentrates on two aspects of the model: first, grid generation, including both the generation of nodal coordinates for the finite element mesh and the generation of orthotropic material axes at each computational point, and, second, the formulation of constitutive laws suitable for numerically intensive finite element computations. Extensions to this model and applications to the mechanical and electrical function of the heart are described in Chapter 2 by McCulloch and co-workers.

It is assumed changes occur to the biomechanics and viscoelastic response of the levator ani muscle during pregnancy; however, there is limited evidence of this. This study used instrumentation and clinical measures to determine the stiffness and active force capacity of levator ani muscle during pregnancy and post-partum, investigated any associations with delivery outcomes, and explored the biomechanical properties associated with symptoms of pelvic floor dysfunction. This was a prospective observational study, with nulliparous women with a singleton low-risk pregnancy. Data were collected at two stages during pregnancy and post-partum. Measurements included the Australian Pelvic Floor Questionnaire, palpation of active force, and elastometry measurements. Post-partum, 3D/4D ultrasound measurements were included. Repeated measures ANOVAs, pairwise comparisons, Pearson correlation coefficients, and Student’s t-tests were used as appropriate. Fifty-nine women took part in the study. Active force was significantly different over the pregnancy and post-partum, measured with instrumentation (p = 0.002) and palpation (p = 0.006 right, p = 0.029 left). There was no significant change in muscle stiffness during pregnancy. Post-partum muscle stiffness was significantly different between women who gave birth vaginally vs. caesarean section (p = 0.002). Post-partum there were differences in levator hiatal area, symptoms of bladder dysfunction, prolapse symptoms, and sexual dysfunction symptoms. Active force of the levator ani muscle was significantly reduced during pregnancy and in the post-partum period, while muscle stiffness reduced only in those who had vaginal deliveries.

The jugular venous (JV) pressure waveform is a non-invasive, proven indicator of cardiovascular disease. Conventional clinical methods for assessing these waveforms are often overlooked because they require specialised expertise, and are invasive and expensive to implement. Recently, image-based methods have been used to quantify JV pulsation waveforms on the skin as an indirect way of estimating the pressure waveforms. However, these existing image-based methods cannot explicitly measure skin deformations and rely on the use of photoplethysmography (PPG) devices for identification of the pulsatile waveforms. As a result, they often have limited accuracy and robustness and are unsuitable in the clinical environment. Here, we propose a technique to directly measure skin deformations caused by the JV pulse using a very accurate subpixel registration algorithm. The method simply requires images obtained from the subject’s neck using a commodity camera. The results show that our measured waveforms contained all of the essential features of diagnostic JV waveforms in all of 19 healthy subjects tested in this study, indicating a significantly important capability for a potential future diagnostic device. The shape of our measured JV displacement waveforms was validated using waveforms measured with a laser displacement sensor, where the average correlation score between the two waveforms was 0.93 ± 0.05. In addition, synchronously recorded ECG signals were used to verify the timings of diagnostic features of the measured waveforms. To our knowledge, this is the first use of image registration for direct measurement of JV displacement waveforms. Significant advantages of our novel method include the high precision of our measurements, and the ability to use ordinary cameras, such as those in modern mobile phones. These advantages will enable the development of affordable and accessible devices to measure JV waveforms for cardiac diagnostics in the clinical environment. Future devices based on this technology may provide viable options for telemedicine applications, point of care diagnostics, and mobile-based cardiac health monitoring systems.

Computer vision and image processing algorithms form essential components of many industrial, medical, commercial, and research-related applications. Modern imaging systems provide high resolution images at high frame rates, and are often required to perform complex computations to process image data. However, in many applications rapid processing is required, or it is important to minimise delays for analysis results. In these applications, central processing units (CPUs) are inadequate, as they cannot perform the calculations with sufficient speed. To reduce the computation time, algorithms can be implemented in hardware accelerators such as digital signal processors (DSPs), field-programmable gate arrays (FPGAs), and graphics processing units (GPUs). However, the selection of a suitable hardware accelerator for a specific application is challenging. Numerous families of DSPs, FPGAs, and GPUs are available, and the technical differences between various hardware accelerators make comparisons difficult. It is also important to know what speed can be achieved using a specific hardware accelerator for a particular algorithm, as the choice of hardware accelerator may depend on both the algorithm and the application. The technical details of hardware accelerators and their performance have been discussed in previous publications. However, there are limitations in many of these presentations, including: inadequate technical details to enable selection of a suitable hardware accelerator; comparisons of hardware accelerators at two different technological levels; and discussion of old technologies. To address these issues, we introduce and discuss important considerations when selecting suitable hardware accelerators for computer vision and image processing tasks, and present a comprehensive review of hardware accelerators. We discuss the practical details of chip architectures, available tools and utilities, development time, and the relative advantages and disadvantages of using DSPs, FPGAs, and GPUs. We provide practical information about state-of-the-art DSPs, FPGAs, and GPUs as well as examples from the literature. Our goal is to enable developers to make a comprehensive comparison between various hardware accelerators, and to select a hardware accelerator that is most suitable for their specific application.

This paper presents a new two-step method for finding two-dimensional translational shifts with subpixel accuracy. This algorithm can measure subpixel shifts, even in images with few features, or in noisy images where many existing algorithms fail. In the first step of the algorithm (the integer part), the noise-robustness of the gradient correlation methods was improved by replacing central difference differentiators with Savitzky–Golay differentiators (SGDs). In the second step of the algorithm (the subpixel part), several modifications have been proposed to increase the accuracy and noise-robustness of phase-based methods for finding subpixel shifts. Moreover, two error metrics were introduced to quantify the output accuracy of the integer and subpixel parts of the algorithm. Comprehensive tests were conducted on 2400 standard 128 pixel × 128 pixel subimages subjected to synthetic shifts and rotations. Tests showed that the accuracy of the proposed method for finding translational shifts is of the order of a few ten-thousandths of a pixel, which is a substantial improvement over other state-of-the-art methods. For the rotation tests, the method outperformed comparable techniques. Furthermore, results showed that the proposed method generally provides better performance than other competing methods when images contained Gaussian or salt and pepper noise. The proposed method can be used in applications where high accuracy, robustness to noise, and/or computation efficiency are important.

Systems biology has experienced dramatic growth in the number, size, and complexity of computational models. To reproduce simulation results and reuse models, researchers must exchange unambiguous model descriptions. We review the latest edition of the Systems Biology Markup Language (SBML), a format designed for this purpose. A community of modelers and software authors developed SBML Level 3 over the past decade. Its modular form consists of a core suited to representing reaction‐based models and packages that extend the core with features suited to other model types including constraint‐based models, reaction‐diffusion models, logical network models, and rule‐based models. The format leverages two decades of SBML and a rich software ecosystem that transformed how systems biologists build and interact with models. More recently, the rise of multiscale models of whole cells and organs, and new data sources such as single‐cell measurements and live imaging, has precipitated new ways of integrating data with models. We provide our perspectives on the challenges presented by these developments and how SBML Level 3 provides the foundation needed to support this evolution., Over the past two decades, scientists from different fields have been developing SBML, a standard format for encoding computational models in biology and medicine. This article summarizes recent progress and gives perspectives on emerging challenges.

We investigate the use of spatially resolved diffuse imaging to track a fluid jet delivered at high speed into skin tissue. A jet injector with a short needle to deliver drugs beneath the dermis, is modified to incorporate a laser beam into the jet, which is ejected into ex vivo porcine tissue. The diffuse light emitted from the side and top of the tissue sample is recorded using high-speed videography. Similar experiments, using a depth-controlled fiber optic source, generate a reference dataset. The side light distribution is related to source depth for the controlled-source experiments and used to track the effective source depth of the injections. Postinjection X-ray images show agreement between the jet penetration and ultimate light source depth. The surface light intensity profile is parameterized with a single parameter and an exponential function is used to relate this parameter to source depth for the controlled-source data. This empirical model is then used to estimate the effective source depth from the surface profile of the injection experiments. The depth estimates for injections into fat remain close to the side depth estimates, with a root-mean-square error of 1.1 mm, up to a source depth of 8 mm.

In this work, a system is developed for tracking the skin layer to which a needle-free jet injection of fluid has penetrated by incorporating a laser beam into the jet, and measuring the diffuse light emitted from skin tissue. Monitoring the injection in this way offers the ability to improve the reliability of drug delivery with this transdermal delivery method. A laser beam, axially aligned with a jet of fluid, created a distribution of diffuse light around the injection site that varied as the injection progressed. High-speed videography was used to capture the diffuse light emission from laser-coupled jet injections into samples of porcine skin, fat, and muscle. The injection produced a distribution of diffuse light around the injection site that varied as the injection descended. A classifier, trained to distinguish whether the light source was located in the fat or muscle from surface intensity profile measurements, correctly identified the injected layer in [Formula: see text] of the cases when cross-examined against estimates using the light distribution emitted from the side of the sample.

Aim Physiotherapists typically use digital palpation to determine residual tension in a muscle, referred to as muscle stiffness or tone. These assessments are subjective, and little is known about their accuracy or repeatability. Despite this, it is standard practice to base clinical treatment on these findings. The aim of this study was to assess physiotherapists' ability to assign a seven-point palpation scale to quantitative stiffness values generated by a novel device. Methods Prospective observational study involving 125 musculoskeletal and pelvic floor physiotherapists. A novel device was developed that replicates the haptic feedback that clinicians assess as muscle stiffness. Measurements of displacement, force, and stiffness were recorded. Results There was wide overlap between each scale category assigned to the stiffness values, from low stiffness at -3 (119 [106, 132] N/m) to moderate stiffness at 0 (462 [435,489] N/m); to high stiffness at +3 (897 [881,913] N/m). Consistency in applying the scale was poor, and the probability of a similar value of stiffness being assigned to the same scale category by different participants was low. Conclusions While palpation is used globally by physiotherapists as a readily available and low-cost method of assessing muscle stiffness, these results indicate that it should be used with caution in diagnosing and defining patient care. Clinical assessment of muscle stiffness requires a validated and reliable palpation scale if this metric is to be used to diagnose pathology and develop treatment protocols. Training in this scale should then be recommended to improve reliability in patient assessment.

Clinicians face many challenges when diagnosing and treating breast cancer. These challenges include interpreting and co-locating information between different medical imaging modalities that are used to identify tumours and predicting where these tumours move to during different treatment procedures. We have developed a novel automated breast image analysis workflow that integrates state-of-the-art image processing and machine learning techniques, personalized three-dimensional biomechanical modelling and population-based statistical analysis to assist clinicians during breast cancer detection and treatment procedures. This paper summarizes our recent research to address the various technical and implementation challenges associated with creating a fully automated system. The workflow is applied to predict the repositioning of tumours from the prone position, where diagnostic magnetic resonance imaging is performed, to the supine position where treatment procedures are performed. We discuss our recent advances towards addressing challenges in identifying the mechanical properties of the breast and evaluating the accuracy of the biomechanical models. We also describe our progress in implementing a prototype of this workflow in clinical practice. Clinical adoption of these state-of-the-art modelling techniques has significant potential for reducing the number of misdiagnosed breast cancers, while also helping to improve the treatment of patients.

Outcomes on pelvic floor function after pelvic floor surgery are difficult to quantify. Urinary incontinence affects 25% of women, with 12% of these women requiring surgical intervention to relieve symptoms. However, quantitative measurement of pelvic floor function following surgery is not currently available. This work considers the use of an intra-vaginal pressure sensor array to measure the vaginal pressure profile as a means to quantify surgical outcomes. An observational cohort study is underway to evaluate changes in vaginal pressure profiles pre and post pelvic organ prolapse surgery.

The measurement of the displacement of soft robotic devices and configurations of actuators is essential for the implementation of force and position control. Conventional deformation sensors, such as capacitive and resistive, are unable to acheive the large extensions required to accurately measure these configurations. Recent advances in flexible optical deformation sensors over the last four years have provided sensor technologies that can measure the large extensions that are experienced in soft actuators. However, the majority of existing optical sensors suffer from performance issues relating to unknown losses in optical power and the lack of immunity to external light sources. To address these issues, a simple optical sensor, constructed using a silicone elastomer, has been tested. By measuring the ratio of two wavelengths of light with different attenuation coefficients, the effects of wavelength dependent optical losses and external light interference can be addressed. A clear silicone sensor was characterised using a RGB LED over 500 extension cycles up to 100 % extension, giving a repeatable output and low and linear hysteresis over all 500 cycles. The effect of different optical dyes was investigated, showing that different dyes can controllably attenuate specific wavelengths and thus affect the sensitivity of the measurements. This investigation demonstrates that a ratioed wavelength flexible optical deformation sensor is capable of repeatable measuring large deformations, suitable for use in a range of applications.

Cellular mechanics is an area that has been readily explored, yet there is still much that is unknown about the behaviour of heart muscle cells (myocytes) during contraction in both healthy and diseased states. Currently available systems for contractility measurements expect myocytes to be aligned within the imaging system and expect them to contract axially. However, myocyte contraction is not always uniform, and hence localised changes in the myocyte may not be captured in 1D measurements such as average sarcomere and cell length. With the availability of new and robust image correlation techniques, there is new potential to track displacements of cells without the need for external markers. Here, we present the use of a subpixel image registration (accurate to the millipixel) to track the internal movement of an isolated myocyte during unloaded contraction. Additionally, methods were developed to estimate the orientation of a contracting myocyte frame by frame, removing the need for myocytes to be perfectly aligned in the imaging system. This will allow measurement of sarcomere lengths and displacement regardless of what angle the myocyte is at. Furthermore, it offers the potential to find localised myocyte angle during contraction and therefore localised sarcomere lengths.

Computer vision technologies have become popular tools for performing non-contact measurements. Stereoscopic systems have been used in several applications for length and geometry measurements. Three-dimensional (3D) reconstruction is an essential part of performing 3D measurements. A variety of methods have been developed for 3D reconstruction in stereoscopic systems. Block matching methods are considered as the most suitable option for 3D measurements, but they require the views to be similar for the cameras of a stereoscopic system. To satisfy this need, the cameras of a stereoscopic system should have small angles between their optical axes on the object’s surface. However, it is not always feasible nor desirable to arrange cameras in this way for some applications. We have proposed a new method to address this restriction. Our method uses an initial transform between the images from two cameras to make the views similar. Points on the transformed images are used as initial estimates of matched points in the two camera views. The points are then matched between the two images using an accurate subpixel image registration algorithm.The new method was tested using an object with known dimensions. The maximum measurement error achieved was 0.05 mm with a standard deviation of 0.09 mm for 10 measurements of a 12 mm length. The high accuracy of this method makes it a suitable option for applications that require reliable 3D measurements.

Key points The complexity of computational models is increasing, supported by research in modelling tools and frameworks. But relatively little thought has gone into design principles for complex models. We propose a set of design principles for complex model construction with the Physiome standard modelling protocol CellML. By following the principles, models are generated that are extensible and are themselves suitable for reuse in larger models of increasing complexity. We illustrate these principles with examples including an architectural prototype linking, for the first time, electrophysiology, thermodynamically compliant metabolism, signal transduction, gene regulation and synthetic biology. The design principles complement other Physiome research projects, facilitating the application of virtual experiment protocols and model analysis techniques to assist the modelling community in creating libraries of composable, characterised and simulatable quantitative descriptions of physiology. Abstract The ability to produce and customise complex computational models has great potential to have a positive impact on human health. As the field develops towards whole-cell models and linking such models in multi-scale frameworks to encompass tissue, organ, or organism levels, reuse of previous modelling efforts will become increasingly necessary. Any modelling group wishing to reuse existing computational models as modules for their own work faces many challenges in the context of construction, storage, retrieval, documentation and analysis of such modules. Physiome standards, frameworks and tools seek to address several of these challenges, especially for models expressed in the modular protocol CellML. Aside from providing a general ability to produce modules, there has been relatively little research work on architectural principles of CellML models that will enable reuse at larger scales. To complement and support the existing tools and frameworks, we develop a set of principles to address this consideration. The principles are illustrated with examples that couple electrophysiology, signalling, metabolism, gene regulation and synthetic biology, together forming an architectural prototype for whole-cell modelling (including human intervention) in CellML. Such models illustrate how testable units of quantitative biophysical simulation can be constructed. Finally, future relationships between modular models so constructed and Physiome frameworks and tools are discussed, with particular reference to how such frameworks and tools can in turn be extended to complement and gain more benefit from the results of applying the principles.

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.

Objective: A jet injector is a device that can be used to deliver liquid drugs through the skin using a fluid jet, without the use of a needle. Most jet injectors are designed and used for the delivery of inviscid liquids, and are not optimized for the delivery of viscous drug compounds. To better understand the requirements for delivering viscous drugs, we have developed a mathematical model of the electromechanics of a moving-coil actuated jet injector as it delivers viscous fluids. Methods: The model builds upon previous work by incorporating the nonlinear electrical properties of the motor, compliant elements of the mechanical piston and ampoule system, and the effect of viscosity on injector characteristics. The model has been validated by monitoring the movement of the piston tip and measurements of the jet force. Results: The results of the model indicate that the jet speed is diminished with increasing fluid viscosity, but overshoot and ringing in the jet speed is unaffected. However, a stiffer ampoule and piston will allow for a better control of the jet speed profile during an injection, and reduce ringing. Conclusion: We identified that the piston friction coefficient, the compliance of the injector components, and the viscous properties of the fluid are important determinants of performance when jet-injecting viscous fluids. Significance: By expanding upon previous jet injector models, this study has provided informative simulations of jet injector characteristics and performance. The model can be used to guide the design of future jet injectors for viscous fluids.

We propose an automatic pipeline for creating shape modelling suitable parametric meshes of the trapeziometacarpal (TMC) joint from clinical CT images for the purpose of batch processing and analysis. The method uses 3D random forest regression voting (RFRV) with statistical shape model (SSM) segmentation. The method was demonstrated in a validation experiment involving 65 CT images, 15 of which were randomly selected to be excluded from the training set for testing. With mean root mean squared (RMS) errors of 1.066 mm and 0.632 mm for the first metacarpal and trapezial bones respectively, and a segmentation time of ~2 minutes per CT image, the preliminary results showed promise for providing accurate 3D meshes of TMC joint bones for batch processing.

Cardiovascular diseases are a common cause of death. Symptoms of cardiovascular disease often arise at a stage of the disease where treatments are ineffective. Hence, methods that can help early diagnosis of heart problems are essential for preventing heart failure. Assessing the shape of the carotid artery waveforms is one of the methods that clinicians use to diagnose heart and valvular diseases, such as hypertrophic obstructive cardiomyopathy, aortic stenosis, and aortic regurgitation. The carotid artery waveforms may be estimated using pulsed-Doppler ultrasound devices or quantified using catheterisation. However, both of these solutions have limitations. Currently, among available solutions, there is no inexpensive, non-invasive objective method, or diagnostic tool for estimating or quantifying the carotid waveforms. To address these limitations, we have designed a portable non-contact camera-based device to quantify the carotid arterial waveforms. The proposed device calculates the vessel-induced deformation of skin from videos taken from the neck to estimate the carotid artery pressure waveforms. This device takes advantage of our precise and sensitive subpixel image registration algorithm to measure skin deformations from sequential frames of the videos. The skin deformations obtained using our device were compared against a laser displacement measurement device with a resolution of 0.2 μm, and a correlation score of 0.95 was achieved for five subjects.

The normal decline in lung function that occurs with age is virtually indistinguishable from early disease, leading to frequent misdiagnosis in the elderly. Computational modelling promises to be a useful tool for improving our understanding of lung mechanics. However, there is currently no unified structure-function computational model that explains how age-dependent structural changes translate to decline in whole lung function. Furthermore, existing models suffer from weak parameterisation due to lack of available data. To begin addressing this issue, we have developed a real-time full-field stereoscopic imaging system for tracking surface deformation of the rat lung during pressure-controlled ventilation. The system will enable the acquisition of novel physiological data on lung tissue mechanics. This study presents preliminary lung surface tracking results from experiments on Sprague-Dawley rats under pressure controlled ventilation. This rich data will provide us with previously unavailable information for constructing and validating more realistic computational models of the lung to help us better understand the mechanisms behind decline in lung function with aging and help guide the development of new diagnostic methods to distinguish age from lung disease.

A non-destructive imaging technique is required for quantifying the anisotropic and heterogeneous structural arrangement of collagen in soft tissue membranes, such as bovine pericardium, which are used in the construction of bioprosthetic heart valves. Previously, our group developed a Stokes imaging polarimeter that measures the linear birefringence of samples in a transmission arrangement. With this device, linear retardance and optic axis orientation; can be estimated over a sample using simple vector algebra on Stokes vectors in the Poincare sphere. However, this method is limited to a single path retardation of a half-wave, limiting the thickness of samples that can be imaged. The polarimeter has been extended to allow illumination of narrow bandwidth light of controllable wavelength through achromatic lenses and polarization optics. We can now take advantage of the wavelength dependence of relative retardation to remove ambiguities that arise when samples have a single path retardation of a half-wave to full-wave. This effectively doubles the imaging depth of this method. The method has been validated using films of cellulose of varied thickness, and applied to samples of bovine pericardium.

The effect of varying velocity during jet injection on the dispersion of fluid into tissue is investigated using a custom-built X-ray imaging system. Injections are performed into ex-vivo porcine abdominal tissue using a voice coil actuated injection device. Single velocity and two-phase velocity injections reveal the complex nature of the dispersion of the fluid jet in layered tissue and highlight the effects of changing the jet velocity following the initial penetration of the liquid into the tissue.

Summary Objective Characterising the morphological differences between healthy and early osteoarthritic (EOA) trapeziometacarpal (TMC) joints is important for understanding osteoarthritis onset, and early detection is important for treatment and disease management. This study has two aims: first, to characterise morphological differences between healthy and EOA TMC bones. The second aim was to determine the efficacy of using a statistical shape model (SSM) to detect early signs of osteoarthritis (OA). Methods CT image data of TMC bones from 22 asymptomatic volunteers and 47 patients with EOA were obtained from an ongoing study and used to generate a SSM. A linear discriminant analysis (LDA) classifier was trained on the principal component (PC) weights to characterise features of each group. Multivariable statistical analysis was performed on the PC to investigate morphologic differences. Leave-one-out classification was performed to evaluate the classifiers performance. Results We found that TMC bones of EOA subjects exhibited a lower aspect ratio (P = 0.042) compared with healthy subjects. The LDA classifier predicted that protrusions (up to 1.5 mm) at the volar beak of the first metacarpal were characteristic of EOA subjects. This was accompanied with widening of the articular surface, deepening of the articular surface, and protruding bone growths along the concave margin. These characteristics resulted in a leave-one-out classification accuracy of 73.9% (95% CI [61.9%, 83.8%]), sensitivity of 89.4%, specificity of 40.9%, and precision of 75.9%. Conclusion Our findings indicate that morphological degeneration is well underway in the EOA TMC joint, and shows promise for a clinical tool that can detect these features automatically.

Many calorimetric sensing applications, such as measurement of heat exchange in chemical reactions or of the heat production of biological specimens, require high-resolution temperature sensors suitable for use at or near room temperature. We have developed a thermometer that measures changes in the vapor pressure of a volatile substance to infer the temperature of its liquid phase. Our prototype sensor provided a noise-equivalent-temperature resolution of 16 μK over a 1 Hz bandwidth — an order of magnitude improvement over previous vapor-pressure thermometers. The thermometer design enables temperature-resolution that has the potential to be extended to the microkelvin range, and imposes minimal thermal load on the heat source. Furthermore, the sensing element responsible for transduction of temperature changes into movement is inexpensive, enabling the possibility of disposable transducing elements in a sensor system. While this thermometer demonstrates the feasibility of the modality for high-resolution measurements of temperature change, without further advances in methodology current construction techniques limit the reproducibility between sensors, which may constrain the wide applicability of the sensor system.

Introduction The influence of levator-ani muscles on second-stage labor is poorly understood. The ability of these muscles to stretch without damage may affect birth outcomes, but little is known about material properties, effects of pregnancy and/or ethnicity on levator-ani stiffness. There are strong associations between muscle damage and subsequent pelvic floor disorders. This study aimed to quantify levator-ani muscle stiffness during the third trimester of pregnancy and postpartum in European and Polynesian women. Associations between stiffness, obstetric variables, and the risk of intrapartum levator-ani injury (avulsion) were investigated. Material and methods This was a prospective observational pilot study. A total of 167 (106 European and 61 Polynesian) nulliparous women were recruited antenatally; 129 returned postnatally. Participants were assessed between 36 and 38 weeks' gestation and three to five months postpartum. Assessments included pelvic floor ultrasound, elastometry testing, and validated questionnaires on pelvic floor function. Logistic regression, Student t-, Chi-square and Mann–Whitney tests were used as appropriate. Results There are significant differences between antenatal and postnatal muscle stiffness measurements (p < 0.01). Stiffness was significantly higher in the European cohort (p = 0.03). There were more avulsion injuries in European (20%) than in Polynesian (9%) women. There were no significant differences in antenatal stiffness between women with and without avulsion, but change in stiffness (antenatal to postnatal) was significantly less in the avulsion group. There were no associations between stiffness, and other obstetric variables, epidural anaesthesia seemed protective (p = 0.03). Conclusions Quantification of levator-ani muscle stiffness is feasible. Muscle stiffness is significantly different before and after birth.

A wireless intravaginal pressure sensor (IVPS) has been developed to quantify abdominal pressure (Pabd) changes during exercise and activities of daily living to guide post-operative advice given to women. In this pilot study, we aimed to compare IVPS performance, comfort, retention, and acceptability to a standard fluid-filled intrarectal pressure catheter currently used to measure Pabd during routine urodynamics. A Life-Tech 3-mm urodynamic intrarectal catheter and IVPS were inserted concurrently in volunteers attending a urodynamics clinic. The IVPS was positioned above the levator plate and the intrarectal catheter positioned in routine fashion well above the anal sphincter. Routine urodynamics was undertaken, with women asked to perform star jumps if coughing or Valsalva did not invoke leakage. Subjects rated device comfort using a visual analogue scale (0–10). Repeated measures Bland-Altman analysis determined level of agreement (LOA) between the two devices for peak pressures for each activity. Twenty-seven women were recruited, 67 % of the participants preferred the IVPS, 18 % the intrarectal catheter, while 15 % had no preference. Mean comfort score was 0.9 ± 1.7 and 2.1 ± 2.6 (p = 0.049) for the IVPS and intrarectal catheter respectively. Bland-Altman analysis demonstrated minimal bias for cough and Valsalva, however LOA were wide. Differences were more prominent during star jumps where rapid dynamic pressure changes occurred. The IVPS had a higher comfort score and was well retained. The LOA between the two systems was moderate, but the high sampling rate and lower susceptibility to motion artefacts of the IVPS may provide more accurate information that will be important clinically.

We present a workflow for producing a statistical shape model (SSM) of the femur with automatically defined regions resembling general anatomic features. Explicitly defined regions enforce correspondence of anatomical features, and allow the shapes of regions to be analysed independently if needed. A training set of manually segmented femur surfaces are partitioned according to Gaussian curvature. Partitioned regions across the training set are then grouped using mean-shift clustering to identify the most stable regions into which surfaces are divided. Reference piecewise parametric meshes are designed for and fitted to each region, and used to train regional SSMs through fitting–training iterations. Fitted region meshes are assembled into full femur meshes for training a whole femur region-based SSM (rSSM). Partitioning, clustering and shape modelling results are presented for 41 femurs. In comparison to a non-regional SSM, the rSSM was more efficient and correspondent in its approximation of unseen femurs.

Very high resolution power sensors are required for measuring the rate of heat production (~10 μW) of small samples of heart muscle (rat cardiac trabeculae, ~2 mm long and ~200 μm diameter). In this paper, we examine the design criteria for thermopiles to maximize their signal-to-noise ratio for heat balance calorimetry. We found that those thermopiles with a high thermoelectric figure-of-merit (ZT) are the best for power measurements. An initial prototype with a resolution of 53 nW has been built. KeywordsCalorimetry, thermal variables measurement, thermal sensors, thermal noise

Aim Design and develop an automated, hand-held instrument (elastometer) to assess in vivo passive stiffness of the pelvic floor muscle. Materials and Methods The elastometer system consisted of a hand piece, real-time controller, and laptop computer. A cable connected the hand-piece to the controller, which communicated with a laptop computer via an ethernet connection. Force sensitivity calibration and displacement accuracy were determined experimentally using a spring load and an Instron mechanical tester. A test re-test series quantified the in vivo repeatability (within a procedure) and reproducibility (between procedures after a 5 min delay) of passive stiffness in volunteers (n = 20). Stiffness was determined from the gradient of the force–displacement curve for each cycle. Results The force-aperture spring measurements from the elastometer showed consistent (r2 = 1.0000) agreement with those measured by the Instron. The difference between spring stiffness as measured by the elastometer and the Instron (388.1 N/m cf. 388.5 N/m, respectively) was negligible. The intra-class correlation coefficient for repeatability within procedures was 0.986 95% CI (0.964–0.994) n = 20, and reproducibility between procedures ICC 0.934 (95% CI 0.779–0.981) n = 12. Bland–Altman analysis determined a bias of 0.3 and 18.5 N/m, for repeatability and reproducibility respectively. Neither bias is likely to be clinically significance. Conclusion The elastometer demonstrated very good repeatability and accuracy in the measurement of force/displacement during in vitro testing. There was a high degree of repeatability and reproducibility in stiffness measurements in a test re-test series. Our results demonstrate the elastometer is accurate and reliable and thereby suitable for larger clinical trials. Neurourol. Urodynam. 34:133–138, 2015. © 2013 Wiley Periodicals, Inc.

Accurate measurement of skin deformation is essential to study and understand its behaviour under mechanical load. Digital image correlation (DIC) techniques are commonly used for in-vivo subpixel measurements of deformation using camera-based devices. However, most of the existing DIC methods have modest accuracy and require the addition of feature-rich textures in order to measure the deformations. These limitations have made it challenging to measure skin deformations using DIC, especially where the skin does not have a rich texture and high measurement accuracies are required. Recently, an accurate and robust algorithm, named phase-based Savitzky–Golay gradient correlation (P-SG-GC), has been proposed for subpixel image registration. This algorithm addresses many of the limitations of existing DIC algorithms, and its advantages could lead to new advances in measuring skin deformations. In this paper, we test the accuracy and applicability of P-SG-GC for measuring subpixel deformations of living skin.

Clinicians face many challenges when diagnosing and treating breast cancer. Biomechanical modeling of the breast is a field of research that aims to assist clinicians in addressing some of these challenges using a physics-based approach. This includes helping to colocate information between various medical imaging modalities that are used to identify tumors, and providing the ability to predict the location of these tumors during different treatment procedures. This review describes the state of the art in the field of modeling breast biomechanics, highlighting methods that have been used for constructing biomechanical models of the breast, and the constitutive relations that are typically used to describe the behavior of its different tissues. Examples of how these models have been used to address clinical challenges are also presented. Clinical adoption of such modeling techniques has significant potential for reducing instances of misdiagnosed breast cancers, while also helping to improve clinical treatment of patients.

Several methods have been proposed to correct motion in medical and non-medical applications, such as optical flow measurements, particle filter tracking, and image registration. In this paper, we designed experiments to test the accuracy and robustness of a recently proposed algorithm for subpixel image registration. In this case, the algorithm is used to correct the relative motion of the object and camera in pairs of images. This recent algorithm (named phase-based Savitzky-Golay gradient-correlation (P-SG-GC)) can achieve very high accuracies in finding synthetically applied translational shifts.

Abusive head trauma, previously termed “shaken baby syndrome”, refers to head injuries inflicted on young infants by their caregivers. There is currently a lack of scientific evidence around the causes of these injuries, but violent shaking has been implicated [1]. Computational modelling of the infant head can help to address ambiguities surrounding the diagnosis of abusive head trauma. To validate this numerical approach, in-vivo brain deformations of the adult brain undergoing mild angular accelerations were used.

This study aimed to determine the accuracy to which prone and supine MRI can be registered using biomechanical models, to help clinicians with pre-operative breast cancer treatment planning. A framework was developed for constructing a biomechanical model of the breast from diagnostic prone MRI. These images were then warped using a prone-to-supine mechanics simulation to generate an initial estimate of the tissue displacement in the supine position. This initial estimate of tissue motion was subsequently used for registering the prone MRI to pre-operative supine MRI using an image intensity-based non-rigid registration algorithm. The framework was demonstrated using MR images from two volunteers. The results showed that a two parameter breast model provided good initial estimates of tissue displacement for registering the prone and supine MR images, with registration errors less than 5 mm for mean tissue displacement magnitudes of up to 61.8 mm between the prone and supine positions.

We present an inexpensive imaging system for measuring the diffuse surface radiance profile produced by a light source within a turbid medium. The diffusion model of light propagation in multiple scattering media is used to estimate the optical properties of a sample and subsequently approximate the depth of an optical source. The system is shown to accurately estimate the relative changes in source depth in a homogeneous phantom. The absolute depth estimate may be improved with a better estimate of the optical parameters. Preliminary tests on a porcine skin sample show that the simple model can be used to roughly track the relative changes in the depth of a source in a layered medium. However, a rigorous model of the layered geometry may be required to more accurately localize a source, particularly near interfaces between tissue layers.

Two of the major imaging modalities used to detect and monitor breast cancer are (contrast enhanced) magnetic resonance (MR) imaging and mammography. Image fusion, including accurate registration between MR images and mammograms, or between CC and MLO mammograms, is increasingly key to patient management (for example in the multidisciplinary meeting), but registration is extremely difficult because the breast shape varies massively between the modalities, due both to the different postures of the patient for the two modalities and to the fact that the breast is forcibly compressed during mammography. In this paper, we develop a 3D, patient-specific, anatomically accurate, finite element model of the breast using MR images, which can be deformed in a physically realistic manner using nonlinear elasticity theory to simulate the breast during mammography. © Springer-Verlag Berlin Heidelberg 2004.

The VPH/Physiome Project is developing the model encoding standards CellML (cellml.org) and FieldML (fieldml.org) as well as web-accessible model repositories based on these standards (models.physiome.org). Freely available open source computational modelling software is also being developed to solve the partial differential equations described by the models and to visualise results. The OpenCMISS code (opencmiss.org), described here, has been developed by the authors over the last six years to replace the CMISS code that has supported a number of organ system Physiome projects. OpenCMISS is designed to encompass multiple sets of physical equations and to link subcellular and tissue-level biophysical processes into organ-level processes. In the Heart Physiome project, for example, the large deformation mechanics of the myocardial wall need to be coupled to both ventricular flow and embedded coronary flow, and the reaction-diffusion equations that govern the propagation of electrical waves through myocardial tissue need to be coupled with equations that describe the ion channel currents that flow through the cardiac cell membranes. In this paper we discuss the design principles and distributed memory architecture behind the OpenCMISS code. We also discuss the design of the interfaces that link the sets of physical equations across common boundaries (such as fluid-structure coupling), or between spatial fields over the same domain (such as coupled electromechanics), and the concepts behind CellML and FieldML that are embodied in the OpenCMISS data structures. We show how all of these provide a flexible infrastructure for combining models developed across the VPH/Physiome community.

Detailed knowledge of the lymphatic drainage of the breast is limited. Lymphoscintigraphy is a technique used during breast cancer treatment to accurately map patterns of lymphatic drainage from the primary tumour to the draining lymph nodes. This study aimed to create a statistical model to analyse the spread of breast cancer and primary tumour location using a large lymphoscintigraphy database, and visualise the results with a novel computational model. This study was based on lymphoscintigraphy data from 2,304 breast cancer patients treated at the Royal Prince Alfred Hospital Medical Centre in Sydney, Australia. Bayesian inferential techniques were implemented to estimate the probabilities of lymphatic drainage from each region of the breast to each draining node field, to multiple node fields, and to determine probabilities of tumour prevalence in each breast region. A finite element model of the torso and discrete model of the draining node fields were created to visualise these data and a software tool was developed to display the results ( www.abi.auckland.ac.nz/breast-cancer ). Results confirmed that lymphatic drainage is most likely to occur to the axillary node field, and that there is significant likelihood of drainage to the internal mammary node field. The likelihood of lymphatic drainage from the whole breast to the axillary, internal mammary, infraclavicular, supraclavicular and interpectoral node fields were 98.2, 35.3, 1.7, 3.1, and 0.7%, respectively; whilst the probability of lymphatic drainage to multiple node fields was estimated to be 36.4%. Additionally, primary tumours are most likely to develop in the upper regions of the breast. The models developed provide quantitative estimates of lymphatic drainage of the breast, giving important insights into understanding breast cancer metastasis and have the potential to benefit both clinicians and patients during breast cancer diagnosis and treatment.

Current understanding of the lymphatics draining the breast is controversial, despite its known importance in the spread of breast cancer. Similarly, knowledge regarding the spatial distribution of primary tumours in the breast is limited. This study sought to test commonly held assumptions in this field, including: (i) that breast lymphatic drainage and tumour prevalence are symmetric between the left and right sides of the body, (ii) that males and females have the same drainage patterns and tumour prevalences, and (iii) that lymphatic drainage in the breast occurs independently to different node fields. This study has used lymphoscintigraphy data from 2304 breast cancer patients treated at the RPAH Medical Centre, Sydney, Australia. Symmetry of lymphatic drainage and tumour distribution as well as gender differences were tested using Fisher's exact test. Drainage independence was assessed using Fisher's exact test, and a multivariate probit model was used to test for drainage correlations. Results showed that the breasts are likely to have symmetric lymphatic drainage and tumour prevalence, and that there is no significant difference between males and females. Furthermore, results showed that direct lymphatic drainage of the breasts is likely to be independent between node fields. Collectively, these results serve to further our understanding of lymphatic anatomy and the distribution of tumours in the breast.

This study investigates the use of multiple gravity-loaded configurations of a soft heterogeneous body for the identification of its mechanical properties. It is largely motivated by the need for in vivo, non-invasive determination of the mechanical properties of biological tissue, such as the breast, for the purposes of tracking and predicting tumor locations. In order to validate this approach, experiments were performed on a heterogeneous two-layered silicone gel cantilever beam, laser scanned in eight different orientations under gravity loading. A finite element model of the beam was constructed and analyzed using non-linear finite elasticity and a neo-Hookean stress–strain relationship. The constitutive parameters representing the stiffness of each layer were estimated, using non-linear optimization techniques, to best fit the laser-scanned data. Different subsets of the experiments were used for training (parameter fitting), with the remaining experiments being used for validation. In both experimental sets, a cross-validation study was performed in order to compare and assess the predictive power of the identified parameters. Several determinability criteria were used to assess the objective function in the neighborhood of the identified minimum. We found that individual experiments were not sufficient for reliable parameter identification of heterogeneous soft bodies under gravity loading, but that a small number of gravity-loaded configurations were sufficient to reliably estimate the parameters within the scale of experimental errors. We also discuss the practical and numerical issues related to both single and multi-experiment parameter estimation.

Background: The mechanical properties of skin, and its ability to resist a wide range of deformations, are mainly determined by the collagen network within the dermis. Aims: In order to quantify the structure–function relationship of skin, quantitative data on collagen orientation are acquired in this study. Materials & Methods: Saggital cryosections from the abdominal region of young pigs were stained with picrosirus red for collagen detection and images were acquired by confocal laser scanning microscopy (CLSM). Spatial distributions of collagen orientation were determined using a structure–tensor approach. Orientation data were fitted to a mixture of two von Mises distributions. Results: It was observed that collagen is organised into large bundles in the reticular dermis that run obliquely between the epidermis to hypodermis along two predominant orientations. Discussion: This distinct lattice structure was apparent in all sections, regardless of the sectioning orientation. Based on our observations from CLSM images,we propose a conceptual model expressed in terms of a density distribution function to describe collagen orientation. Conclusion: We demonstrate that two parameters of this distribution (the mean and spread parameter) may be directly determined using CLSM image analysis. An important advantage of this approach is that model parameters can be estimated directly from observable microstructural features.

Motivation: The Physiome Project was established in 1997 to develop tools to facilitate international collaboration in the physiological sciences and the sharing of biological models and experimental data. The CellML language was developed to represent and exchange mathematical models of biological processes. CellML models can be very complicated, making it difficult to interpret the underlying physical and biological concepts and relationships captured/described in the mathematical model. Results: To address this issue a set of ontologies was developed to explicitly annotate the biophysical concepts represented in the CellML models. This article presents a framework that combines a visual language, together with CellML ontologies, to support the visualization of the underlying physical and biological concepts described by the mathematical model and also their relationships with the CellML model. Automated CellML model visualization assists in the interpretation of model concepts and facilitates model communication and exchange between different communities. Contact: sarala.dissanayake@auckland.ac.nz Supplementary information: Supplementary data are available at Bioinformatics online.