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Noninvasive imaging of regional cardiac electrophysiology remains an elusive target. Such imaging is still in its infancy, particularly in comparison to structural imaging modalities such as magnetic resonance imaging (MRI), x-ray computed tomography (CT), and ultrasound. We present an overview of noninvasive ECG imaging, and the challenges and successes of the various techniques across a range of applications. Unlike MRI and CT, reconstructing cardiac electrophysiology from remote body surface measurements is a highly ill-posed problem. We therefore first review the theoretical considerations and associated algorithms that are used to address this issue. We then focus on the important issue of validation, and review and contrast recent advances in this area. Efforts to validate ECG inverse procedures using a modeling-based approach are addressed first. We then discuss various experimental studies that have been conducted to provide appropriate data for robust validations. We present new data that are simultaneously recorded from dense arrays of electrodes on the epicardium and body surface of anesthetized pigs during sinus rhythm, ventricular pacing, and regional ischemia. These data have been obtained specifically to help validate inverse ECG procedures, and form a useful supplement to recent clinical validation studies. Finally, clinical applications and outstanding issues regarding noninvasive imaging of regional cardiac electrophysiology are addressed. [ABSTRACT FROM AUTHOR]

Abnormal passive stiffness of the heart muscle (myocardium) is evident in the pathophysiology of several cardiovascular diseases, making it an important indicator of heart health. Recent advancements in cardiac imaging and biophysical modeling now enable more effective evaluation of this biomarker. Estimating passive myocardial stiffness can be accomplished through an MRI-based approach that requires comprehensive subject-specific input data. This includes the gross cardiac geometry (e.g. from conventional cine imaging), regional diastolic kinematics (e.g. from tagged MRI), microstructural configuration (e.g. from diffusion tensor imaging), and ventricular diastolic pressure, whether invasively measured or non-invasively estimated. Despite the progress in cardiac biomechanics simulations, developing a framework to integrate multiphase and multimodal cardiac MRI data for estimating passive myocardial stiffness has remained a challenge. Moreover, the sensitivity of estimated passive myocardial stiffness to input data has not been fully explored. This study aims to: (1) develop a framework for integrating subject-specific in vivo MRI data into in silico left ventricular finite element models to estimate passive myocardial stiffness, (2) apply the framework to estimate the passive myocardial stiffness of multiple healthy subjects under assumed filling pressure, and (3) assess the sensitivity of these estimates to loading conditions and myofiber orientations. This work contributes toward the establishment of a range of reference values for material parameters of passive myocardium in healthy human subjects. Notably, in this study, beat-to-beat variation in left ventricular end-diastolic pressure was found to have a greater influence on passive myocardial material parameter estimation than variation in fiber orientation., Competing Interests: Declarations. Competing interests: The authors declare no competing interests., (© 2025. The Author(s).)

Background: Atrial fibrillation (AF) and ventricular fibrillation (VF) episodes exhibit varying durations, with some spontaneously ending quickly while others persist. A quantitative framework to explain episode durations remains elusive. We hypothesized that observable self-terminating AF and VF episode lengths, whereby durations are known, would conform with a power law based on the ratio of system size and correlation length ([Formula: see text]., Methods: Using data from computer simulations (2-dimensional sheet and 3-dimensional left-atrial), human ischemic VF recordings (256-electrode sock, n=12 patients), and human AF recordings (64-electrode basket-catheter, n=9 patients; 16-electrode high definition-grid catheter, n=42 patients), conformance with a power law was assessed using the Akaike information criterion, Bayesian information criterion, coefficient of determination (R 2 , significance= P <0.05) and maximum likelihood estimation. We analyzed fibrillatory episode durations and [Formula: see text], computed by taking the ratio between system size ([Formula: see text], chamber/simulation size) and correlation length (xi, estimated from pairwise correlation coefficients over electrode/node distance)., Results: In all computer models, the relationship between episode durations and [Formula: see text] was conformant with a power law (Aliev-Panfilov R 2 : 0.90, P <0.001; Courtemanche R 2 : 0.91, P <0.001; Luo-Rudy R 2 : 0.61, P <0.001). Observable clinical AF/VF durations were also conformant with a power law relationship (VF R 2 : 0.86, P <0.001; AF basket R 2 : 0.91, P <0.001; AF grid R 2 : 0.92, P <0.001). [Formula: see text] also differentiated between self-terminating and sustained episodes of AF and VF ( P <0.001; all systems), as well as paroxysmal versus persistent AF ( P <0.001). In comparison, other electrogram metrics showed no statistically significant differences (dominant frequency, Shannon Entropy, mean voltage, peak-peak voltage; P >0.05)., Conclusions: Observable fibrillation episode durations are conformant with a power law based on system size and correlation length., Competing Interests: None.

When armed conflict compels people to flee from their homelands, they embark on protracted journeys during which they experience wide ranging physical, social, and psychological challenges. Few studies have focused on refugee psychosocial and physiological profiles during the transitional phase of forced migration that often involves temporary sheltering. Transient refugees' experiences can vary substantially based on local socio-ecological conditions in temporary settlements, including the length of stay, living conditions, as well as the availability and accessibility of physical and social resources. In this study, we compared physiological and psychosocial data from refugees (N=365; 406 observations) in Serbia and Kenya, respectively, with divergent temporal (length of stay) and socio-ecological conditions. In Serbia, refugees resided in asylum centers (mean stay: 0.9 y); in Kenya they were living in Kakuma Refugee Camp (mean stay: 8.8 y), one of the world's largest camps at the time. We had limited ability to directly compare psychosocial measures and used meta-analytic techniques to evaluate predictors of refugee mental and physical health at the two sites, including based on perceived social support. Refugees in Serbia had higher fingernail cortisol (p < 0.001) and were less likely to have elevated C-reactive protein (CRP) levels (p < 0.01) than refugees in Kakuma. We found common gender differences in both settings; women had lower cortisol but higher EBV antibody titers and higher likelihood of having elevated CRP compared to men (all p < 0.01). Woman also reported poorer mental and physical health (p < 0.001). These physiological and health differences may reflect variation between men and women in their psychosocial and physical experiences of factors such as stress, violence, and trauma during their journeys and as transitional refugees. Finally, we also found that refugees with lower levels of perceived social support reported poorer physical and mental health (p < 0.001). Although our results are cross-sectional, they suggest that this intermittent phase of the refugee experience is a key window for helping enhance refugee well-being through an emphasis on interpersonal and community support systems., Competing Interests: Declaration of Competing Interest The authors have no conflicts of interest to declare., (Copyright © 2024 Elsevier Ltd. All rights reserved.)

Background: Echocardiography is widely used to evaluate left ventricular (LV) diastolic function in patients suspected of heart failure. For patients in sinus rhythm, a combination of several echocardiographic parameters can differentiate between normal and elevated LV filling pressure with good accuracy. However, there is no established echocardiographic approach for the evaluation of LV filling pressure in patients with atrial fibrillation. The objective of the present study was to determine if a combination of several echocardiographic and clinical parameters may be used to evaluate LV filling pressure in patients with atrial fibrillation., Results: In a multicentre study of 148 atrial fibrillation patients, several echocardiographic parameters were tested against invasively measured LV filling pressure as the reference method. No single parameter had sufficiently strong association with LV filling pressure to be recommended for clinical use. Based on univariate regression analysis in the present study, and evidence from existing literature, we developed a two-step algorithm for differentiation between normal and elevated LV filling pressure, defining values ≥ 15 mmHg as elevated. The parameters in the first step included the ratio between mitral early flow velocity and septal mitral annular velocity (septal E/e'), mitral E velocity, deceleration time of E, and peak tricuspid regurgitation velocity. Patients who could not be classified in the first step were tested in a second step by applying supplementary parameters, which included left atrial reservoir strain, pulmonary venous systolic/diastolic velocity ratio, and body mass index. This two-step algorithm classified patients as having either normal or elevated LV filling pressure with 75% accuracy and with 85% feasibility. Accuracy in EF ≥ 50% and EF < 50% was similar (75% and 76%)., Conclusions: In patients with atrial fibrillation, no single echocardiographic parameter was sufficiently reliable to be used clinically to identify elevated LV filling pressure. An algorithm that combined several echocardiographic parameters and body mass index, however, was able to classify patients as having normal or elevated LV filling pressure with moderate accuracy and high feasibility., (© 2024. The Author(s).)

Background: Predicting breast tissue motion using biomechanical models can provide navigational guidance during breast cancer treatment procedures. These models typically do not account for changes in posture between procedures. Difference in shoulder position can alter the shape of the pectoral muscles and breast. A greater understanding of the differences in the shoulder orientation between prone and supine could improve the accuracy of breast biomechanical models., Methods: 19 landmarks were placed on the sternum, clavicle, scapula, and humerus of the shoulder girdle in prone and supine breast MRIs (N = 10). These landmarks were used in an optimization framework to fit subject-specific skeletal models and compare joint angles of the shoulder girdle between these positions., Findings: The mean Euclidean distance between joint locations from the fitted skeletal model and the manually identified joint locations was 15.7 mm ± 2.7 mm. Significant differences were observed between prone and supine. Compared to supine position, the shoulder girdle in the prone position had the lateral end of the clavicle in more anterior translation (i.e., scapula more protracted) (P < 0.05), the scapula in more protraction (P < 0.01), the scapula in more upward rotation (associated with humerus elevation) (P < 0.05); and the humerus more elevated (P < 0.05) for both the left and right sides., Interpretation: Shoulder girdle orientation was found to be different between prone and supine. These differences would affect the shape of multiple pectoral muscles, which would affect breast shape and the accuracy of biomechanical models., Competing Interests: Declaration of Competing Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2023. Published by Elsevier Ltd.)

Background: Left ventricular (LV) global longitudinal strain (GLS) has been proposed as an early imaging biomarker of cardiac mechanical dysfunction., Objective: To assess the impact of angiotensin-converting enzyme (ACE) inhibitor treatment of hypertensive heart disease on LV GLS and mechanical function., Methods: The spontaneously hypertensive rat (SHR) model of hypertensive heart disease ( n  = 38) was studied. A subset of SHRs received quinapril (TSHR, n  = 16) from 3 months (mo). Wistar Kyoto rats (WKY, n  = 13) were used as controls. Tagged cardiac MRI was performed using a 4.7 T Varian preclinical scanner., Results: The SHRs had significantly lower LV ejection fraction (EF) than the WKYs at 3 mo (53.0 ± 1.7% vs. 69.6 ± 2.1%, P  < 0.05), 14 mo (57.0 ± 2.5% vs. 74.4 ± 2.9%, P  < 0.05) and 24 mo (50.1 ± 2.4% vs. 67.0 ± 2.0%, P  < 0.01). At 24 mo, ACE inhibitor treatment was associated with significantly greater LV EF in TSHRs compared to untreated SHRs (64.2 ± 3.4% vs. 50.1 ± 2.4%, P  < 0.01). Peak GLS magnitude was significantly lower in SHRs compared with WKYs at 14 months (7.5% ± 0.4% vs. 9.9 ± 0.8%, P  < 0.05). At 24 months, Peak GLS magnitude was significantly lower in SHRs compared with both WKYs (6.5 ± 0.4% vs. 9.7 ± 1.0%, P  < 0.01) and TSHRs (6.5 ± 0.4% vs. 9.6 ± 0.6%, P  < 0.05)., Conclusions: ACE inhibitor treatment curtails the decline in global longitudinal strain in hypertensive rats, with the treatment group exhibiting significantly greater LV EF and GLS magnitude at 24 mo compared with untreated SHRs., (Copyright © 2023 Wolters Kluwer Health, Inc. All rights reserved.)

Objective . Early diagnosis of heart problems is essential for improving patient prognosis. Approach . We created a non-contact imaging system that calculates the vessel-induced deformation of the skin to estimate the carotid artery pressure displacement waveforms. We present a clinical study of the system in patients ( n = 27) with no underlying condition, aortic stenosis (AS), or mitral regurgitation (MR). Main results . Displacement waveforms were compared to aortic catheter pressures in the same patients. The morphologies of the pressure and displacement waveforms were found to be similar, and pulse wave analysis metrics, such as our modified reflection indices (RI) and waveform duration proportions, showed no significant differences. Compared with the control group, AS patients displayed a greater proportion of time to peak ( p = 0.026 and p = 0.047 for catheter and displacement, respectively), whereas augmentation index (AIx ) was greater for the displacement waveform only ( p = 0.030). The modified RI for MR ( p = 0.047 and p = 0.004 for catheter and displacement, respectively) was lower than in the controls. AS and MR were also significantly different for the proportion of time to peak ( p = 0.018 for the catheter measurements), RI ( p = 0.045 and p = 0.002 for the catheter and displacement, respectively), and AIx ( p = 0.005 for the displacement waveform). Significance . These findings demonstrate the ability of our system to provide insights into cardiac conditions and support further development as a diagnostic/telehealth-based screening tool., (Creative Commons Attribution license.)

Chronic thromboembolic pulmonary hypertension (CTEPH) involves abnormally high blood pressure in the pulmonary vessels and is associated with small vessel vasculopathy and pre-capillary proximal occlusions. Management of CTEPH disease is challenging, therefore accurate diagnosis is crucial in ensuring effective treatment and improved patient outcomes. The treatment of choice for CTEPH is pulmonary endarterectomy, which is an invasive surgical intervention to remove thrombi. Following PEA, a number of patients experience poor outcomes or worse-than-expected improvements, which may indicate that they have significant small vessel disease. A method that can predict the extent of distal remodelling may provide useful clinical information to plan appropriate CTEPH patient treatment. Here, a novel biophysical modelling approach has been developed to estimate and quantify the extent of distal remodelling. This method includes a combination of mathematical modelling and computed tomography pulmonary angiography to first model the geometry of the pulmonary arteries and to identify the under-perfused regions in CTEPH. The geometric model is then used alongside haemodynamic measurements from right heart catheterisation to predict distal remodelling. In this study, the method is tested and validated using synthetically generated remodelling data. Then, a preliminary application of this technique to patient data is shown to demonstrate the potential of the approach for use in the clinical setting.Clinical relevance- Patient-specific modelling can help provide useful information regarding the extent of distal vasculopathy on a per-patient basis, which remains challenging. Physicians can be unsure of outcomes following pulmonary endarterectomy. Therefore, the predictive aspect of the patient's response to surgery can help with clinical decision-making.

Clinical translation of personalised computational physiology workflows and digital twins can revolutionise healthcare by providing a better understanding of an individual's physiological processes and any changes that could lead to serious health consequences. However, the lack of common infrastructure for developing these workflows and digital twins has hampered the realisation of this vision. The Auckland Bioengineering Institute's 12 LABOURS project aims to address these challenges by developing a Digital Twin Platform to enable researchers to develop and personalise computational physiology models to an individual's health data in clinical workflows. This will allow clinical trials to be more efficiently conducted to demonstrate the efficacy of these personalised clinical workflows. We present a demonstration of the platform's capabilities using publicly available data and an existing automated computational physiology workflow developed to assist clinicians with diagnosing and treating breast cancer. We also demonstrate how the platform facilitates the discovery and exploration of data and the presentation of workflow results as part of clinical reports through a web portal. Future developments will involve integrating the platform with health systems and remote-monitoring devices such as wearables and implantables to support home-based healthcare. Integrating outputs from multiple workflows that are applied to the same individual's health data will also enable the generation of their personalised digital twin.Clinical Relevance- The proposed 12 LABOURS Digital Twin Platform will enable researchers to 1) more efficiently conduct clinical trials to assess the efficacy of their computational physiology workflows and support the clinical translation of their research; 2) reuse primary and derived data from these workflows to generate novel workflows; and 3) generate personalised digital twins by integrating the outputs of different computational physiology workflows.

Atrial and ventricular fibrillation (AF/VF) are characterized by the repetitive regeneration of topological defects known as phase singularities (PSs). The effect of PS interactions has not been previously studied in human AF and VF. We hypothesized that PS population size would influence the rate of PS formation and destruction in human AF and VF, due to increased inter-defect interaction. PS population statistics were studied in computational simulations (Aliev-Panfilov), human AF and human VF. The influence of inter-PS interactions was evaluated by comparison between directly modeled discrete-time Markov chain (DTMC) transition matrices of the PS population changes, and M/M/∞ birth-death transition matrices of PS dynamics, which assumes that PS formations and destructions are effectively statistically independent events. Across all systems examined, PS population changes differed from those expected with M/M/∞. In human AF and VF, the formation rates decreased slightly with PS population when modeled with the DTMC, compared with the static formation rate expected through M/M/∞, suggesting new formations were being inhibited. In human AF and VF, the destruction rates increased with PS population for both models, with the DTMC rate increase exceeding the M/M/∞ estimates, indicating that PS were being destroyed faster as the PS population grew. In human AF and VF, the change in PS formation and destruction rates as the population increased differed between the two models. This indicates that the presence of additional PS influenced the likelihood of new PS formation and destruction, consistent with the notion of self-inhibitory inter-PS interactions., (© 2023 Crown.)

Changes in cardiovascular hemodynamics are closely related to the development of aortic regurgitation (AR), a type of valvular heart disease. Metrics derived from blood flows are used to indicate AR onset and evaluate its severity. These metrics can be non-invasively obtained using four-dimensional (4D) flow magnetic resonance imaging (MRI), where accuracy is primarily dependent on spatial resolution. However, insufficient resolution often results from limitations in 4D flow MRI and complex aortic regurgitation hemodynamics. To address this, computational fluid dynamics simulations were transformed into synthetic 4D flow MRI data and used to train a variety of neural networks. These networks generated super-resolution, full-field phase images with an upsample factor of 4. Results showed decreased velocity error, high structural similarity scores, and improved learning capabilities from previous work. Further validation was performed on two sets of in vivo 4D flow MRI data and demonstrated success in de-noising flow images. This approach presents an opportunity to comprehensively analyse AR hemodynamics in a non-invasive manner., (© 2023. The Author(s).)

Cardiovascular imaging studies provide a multitude of structural and functional data to better understand disease mechanisms. While pooling data across studies enables more powerful and broader applications, performing quantitative comparisons across datasets with varying acquisition or analysis methods is problematic due to inherent measurement biases specific to each protocol. We show how dynamic time warping and partial least squares regression can be applied to effectively map between left ventricular geometries derived from different imaging modalities and analysis protocols to account for such differences. To demonstrate this method, paired real-time 3D echocardiography (3DE) and cardiac magnetic resonance (CMR) sequences from 138 subjects were used to construct a mapping function between the two modalities to correct for biases in left ventricular clinical cardiac indices, as well as regional shape. Leave-one-out cross-validation revealed a significant reduction in mean bias, narrower limits of agreement, and higher intraclass correlation coefficients for all functional indices between CMR and 3DE geometries after spatiotemporal mapping. Meanwhile, average root mean squared errors between surface coordinates of 3DE and CMR geometries across the cardiac cycle decreased from 7 ± 1 to 4 ± 1 mm for the total study population. Our generalised method for mapping between time-varying cardiac geometries obtained using different acquisition and analysis protocols enables the pooling of data between modalities and the potential for smaller studies to leverage large population databases for quantitative comparisons., (© 2023. The Author(s).)

Our study methodology is motivated from three disparate needs: one, imaging studies have existed in silo and study organs but not across organ systems; two, there are gaps in our understanding of paediatric structure and function; three, lack of representative data in New Zealand. Our research aims to address these issues in part, through the combination of magnetic resonance imaging, advanced image processing algorithms and computational modelling. Our study demonstrated the need to take an organ-system approach and scan multiple organs on the same child. We have pilot tested an imaging protocol to be minimally disruptive to the children and demonstrated state-of-the-art image processing and personalized computational models using the imaging data. Our imaging protocol spans brain, lungs, heart, muscle, bones, abdominal and vascular systems. Our initial set of results demonstrated child-specific measurements on one dataset. This work is novel and interesting as we have run multiple computational physiology workflows to generate personalized computational models. Our proposed work is the first step towards achieving the integration of imaging and modelling improving our understanding of the human body in paediatric health and disease., Competing Interests: Authors HK and JM were employed by the company GE Healthcare (Australia & New Zealand). The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Kumar, Green, Cornfeld, Condron, Emsden, Elsayed, Zhao, Gilbert, Nash, Clark, Tawhai, Burrowes, Murphy, Tayebi, McGeown, Kwon, Shim, Wang, Choisne, Carman, Besier, Handsfield, Babarenda Gamage, Shen, Maso Talou, Safaei, Maller, Taylor, Potter, Holdsworth and Wilson.)

Segmentation of the left ventricle (LV) in echocardiography is an important task for the quantification of volume and mass in heart disease. Continuing advances in echocardiography have extended imaging capabilities into the 3D domain, subsequently overcoming the geometric assumptions associated with conventional 2D acquisitions. Nevertheless, the analysis of 3D echocardiography (3DE) poses several challenges associated with limited spatial resolution, poor contrast-to-noise ratio, complex noise characteristics, and image anisotropy. To develop automated methods for 3DE analysis, a sufficiently large, labeled dataset is typically required. However, ground truth segmentations have historically been difficult to obtain due to the high inter-observer variability associated with manual analysis. We address this lack of expert consensus by registering labels derived from higher-resolution subject-specific cardiac magnetic resonance (CMR) images, producing 536 annotated 3DE images from 143 human subjects (10 of which were excluded). This heterogeneous population consists of healthy controls and patients with cardiac disease, across a range of demographics. To demonstrate the utility of such a dataset, a state-of-the-art, self-configuring deep learning network for semantic segmentation was employed for automated 3DE analysis. Using the proposed dataset for training, the network produced measurement biases of -9 ± 16 ml, -1 ± 10 ml, -2 ± 5 %, and 5 ± 23 g, for end-diastolic volume, end-systolic volume, ejection fraction, and mass, respectively, outperforming an expert human observer in terms of accuracy as well as scan-rescan reproducibility. As part of the Cardiac Atlas Project, we present here a large, publicly available 3DE dataset with ground truth labels that leverage the higher resolution and contrast of CMR, to provide a new benchmark for automated 3DE analysis. Such an approach not only reduces the effect of observer-specific bias present in manual 3DE annotations, but also enables the development of analysis techniques which exhibit better agreement with CMR compared to conventional methods. This represents an important step for enabling more efficient and accurate diagnostic and prognostic information to be obtained from echocardiography., Competing Interests: MN was the CSO of HeartLab (NZ) Ltd. JD’h holds research contracts with GE Vingmed. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Zhao, Ferdian, Maso Talou, Quill, Gilbert, Wang, Babarenda Gamage, Pedrosa, D’hooge, Sutton, Lowe, Legget, Ruygrok, Doughty, Camara, Young and Nash.)

Computational physiological models continue to increase in complexity, however, the task of efficiently calibrating the model to available clinical data remains a significant challenge. One part of this challenge is associated with long calibration times, which present a barrier for the routine application of model-based prediction in clinical practice. Another aspect of this challenge is the limited available data for the unique calibration of complex models. Therefore, to calibrate a patient-specific model, it may be beneficial to verify that task-specific model predictions have acceptable uncertainty, rather than requiring all parameters to be uniquely identified. We have developed a pipeline that reduces the set of fitting parameters to make them structurally identifiable and to improve the efficiency of a subsequent Markov Chain Monte Carlo (MCMC) analysis. MCMC was used to find the optimal parameter values and to determine the confidence interval of a task-specific prediction. This approach was demonstrated on numerical experiments where a lumped parameter model of the cardiovascular system was calibrated to brachial artery cuff pressure, echocardiogram volume measurements, and synthetic cerebral blood flow data that approximates what can be obtained from 4D-flow MRI data. This pipeline provides a cerebral arterial pressure prediction that may be useful for determining the risk of hemorrhagic stroke. For a set of three patients, this pipeline successfully reduced the parameter set of a cardiovascular system model from 12 parameters to 8-10 structurally identifiable parameters. This enabled a significant ( > 4 × ) efficiency improvement in determining confidence intervals on predictions of pressure compared to performing a naive MCMC analysis with the full parameter set. This demonstrates the potential that the proposed pipeline has in helping address one of the key challenges preventing clinical application of such models. Additionally, for each patient, the MCMC approach yielded a 95% confidence interval on systolic blood pressure prediction in the middle cerebral artery smaller than ±10 mmHg (±1.3 kPa). The proposed pipeline exploits available high-performance computing parallelism to allow straightforward automation for general models and arbitrary data sets, enabling automated calibration of a parameter set that is specific to the available clinical data with minimal user interaction., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Argus, Zhao, Babarenda Gamage, Nash and Maso Talou.)

Background and Objective: Renewal theory is a statistical approach to model the formation and destruction of phase singularities (PS), which occur at the pivots of spiral waves. A common issue arising during observation of renewal processes is an inspection paradox, due to oversampling of longer events. The objective of this study was to characterise the effect of a potential inspection paradox on the perception of PS lifetimes in cardiac fibrillation. Methods: A multisystem, multi-modality study was performed, examining computational simulations (Aliev-Panfilov (APV) model, Courtmanche-Nattel model), experimentally acquired optical mapping Atrial and Ventricular Fibrillation (AF/VF) data, and clinically acquired human AF and VF. Distributions of all PS lifetimes across full epochs of AF, VF, or computational simulations, were compared with distributions formed from lifetimes of PS existing at 10,000 simulated commencement timepoints. Results: In all systems, an inspection paradox led towards oversampling of PS with longer lifetimes. In APV computational simulations there was a mean PS lifetime shift of +84.9% (95% CI, ± 0.3%) ( p < 0.001 for observed vs overall), in Courtmanche-Nattel simulations of AF +692.9% (95% CI, ±57.7%) ( p < 0.001), in optically mapped rat AF +374.6% (95% CI, ± 88.5%) ( p = 0.052), in human AF mapped with basket catheters +129.2% (95% CI, ±4.1%) ( p < 0.05), human AF-HD grid catheters 150.8% (95% CI, ± 9.0%) ( p < 0.001), in optically mapped rat VF +171.3% (95% CI, ±15.6%) ( p < 0.001), in human epicardial VF 153.5% (95% CI, ±15.7%) ( p < 0.001). Conclusion: Visual inspection of phase movies has the potential to systematically oversample longer lasting PS, due to an inspection paradox. An inspection paradox is minimised by consideration of the overall distribution of PS lifetimes., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2022 Jenkins, Dharmaprani, Schopp, Quah, Tiver, Mitchell, Xiong, Aguilar, Pope, Akar, Roney, Niederer, Nattel, Nash, Clayton and Ganesan.)

Background: Ventricular fibrillation (VF) is characterized by multiple wavelets and rotors. No equation to predict the number of rotors and wavelets observed during fibrillation has been validated in human VF., Objective: The purpose of this study was to test the hypothesis that a single equation derived from a Markov M/M/∞ birth-death process could predict the number of rotors and wavelets occurring in human clinical VF., Methods: Epicardial induced VF (256-electrode) recordings obtained from patients undergoing cardiac surgery were studied (12 patients; 62 epochs). Rate constants for phase singularity (PS) (which occur at the pivot points of rotors) and wavefront (WF) formation and destruction were derived by fitting distributions to PS and WF interformation and lifetimes. These rate constants were combined in an M/M/∞ governing equation to predict the number of PS and WF in VF episodes. Observed distributions were compared to those predicted by the M/M/∞ equation., Results: The M/M/∞ equation accurately predicted average PS and WF number and population distribution, demonstrated in all epochs. Self-terminating episodes of VF were distinguished from VF episodes requiring termination by a trend toward slower PS destruction, slower rates of PS formation, and a slower mixing rate of the VF process, indicated by larger values of the second largest eigenvalue modulus of the M/M/∞ birth-death matrix. The longest-lasting PS (associated with rotors) had shorter interactivation time intervals compared to shorter-lasting PS lasting <150 ms (∼1 PS rotation in human VF)., Conclusion: The M/M/∞ equation explains the number of wavelets and rotors observed, supporting a paradigm of VF based on statistical fibrillatory dynamics., (© 2021 Heart Rhythm Society. Published by Elsevier Inc. All rights reserved.)

The onset and progression of pathological heart conditions, such as cardiomyopathy or heart failure, affect its mechanical behaviour due to the remodelling of the myocardial tissues to preserve its functional response. Identification of the constitutive properties of heart tissues could provide useful biomarkers to diagnose and assess the progression of disease. We have previously demonstrated the utility of efficient AI-surrogate models to simulate passive cardiac mechanics. Here, we propose the use of this surrogate model for the identification of myocardial mechanical properties and intra-ventricular pressure by solving an inverse problem with two novel AI-based approaches. Our analysis concluded that: (i) both approaches were robust toward Gaussian noise when the ventricle data for multiple loading conditions were combined; and (ii) estimates of one and two parameters could be obtained in less than 9 and 18 s, respectively. The proposed technique yields a viable option for the translation of cardiac mechanics simulations and biophysical parameter identification methods into the clinic to improve the diagnosis and treatment of heart pathologies. In addition, the proposed estimation techniques are general and can be straightforwardly translated to other applications involving different anatomical structures., Competing Interests: GM and TB are scientific advisors at HeartLab (NZ) Ltd. MN is Chief Scientific Officer at HeartLab (NZ) Ltd., (Copyright © 2021 Maso Talou, Babarenda Gamage and Nash.)

Passive mechanical tissue properties are major determinants of myocardial contraction and relaxation and, thus, shape cardiac function. Tightly regulated, dynamically adapting throughout life, and affecting a host of cellular functions, passive tissue mechanics also contribute to cardiac dysfunction. Development of treatments and early identification of diseases requires better spatio-temporal characterisation of tissue mechanical properties and their underlying mechanisms. With this understanding, key regulators may be identified, providing pathways with potential to control and limit pathological development. Methodologies and models used to assess and mimic tissue mechanical properties are diverse, and available data are in part mutually contradictory. In this review, we define important concepts useful for characterising passive mechanical tissue properties, and compare a variety of in vitro and in vivo techniques that allow one to assess tissue mechanics. We give definitions of key terms, and summarise insight into determinants of myocardial stiffness in situ . We then provide an overview of common experimental models utilised to assess the role of environmental stiffness and composition, and its effects on cardiac cell and tissue function. Finally, promising future directions are outlined., Competing Interests: Conflict of interestThe authors declare no competing interests., (© The Author(s) 2021.)

Significance: A non-destructive technique for accurately characterizing the spatial distribution of optical properties of soft tissue membranes may give improved outcomes in many tissue engineering applications., Aim: This study aimed to develop a non-destructive macroscopic imaging technique that is sensitive to optical anisotropy, typical of fibrous components in soft tissue membranes, and can address some of the difficulties caused by the complex turbid nature of these tissues., Approach: A near-infrared Mueller matrix imaging polarimeter employing logarithm decomposition was developed and used to conduct transmission measurements of all the polarization properties across the full thickness of bovine pericardium tissue., Results: The full Mueller matrix was measured across a 70  mm  ×  70  mm sample of calf bovine pericardium and revealed significant retardance (linear and circular) and depolarization in this tissue. Regions with a uniform axis of optical anisotropy were identified. Mueller matrix imaging demonstrated that the exhibited circular retardance was sufficient to lead to possible misinterpretation of apparent fiber orientation when using conventional polarization imaging techniques for such tissues., Conclusions: Mueller matrix imaging can identify regional distributions of optical anisotropy in calf bovine pericardium. This new capability is a promising development in non-destructive imaging for tissue selection.

Aims: Left ventricular (LV) volumes estimated using three-dimensional echocardiography (3D-echo) have been reported to be smaller than those measured using cardiac magnetic resonance (CMR) imaging, but the underlying causes are not well-understood. We investigated differences in regional LV anatomy derived from these modalities and related subsequent findings to image characteristics. Methods and Results: Seventy participants (18 patients and 52 healthy participants) were imaged with 3D-echo and CMR (<1 h apart). Three-dimensional left ventricular models were constructed at end-diastole (ED) and end-systole (ES) from both modalities using previously validated software, enabling the fusion of CMR with 3D-echo by rigid registration. Regional differences were evaluated as mean surface distances for each of the 17 American Heart Association segments, and by comparing contours superimposed on images from each modality. In comparison to CMR-derived models, 3D-echo models underestimated LV end-diastolic volume (EDV) by -16 ± 22, -1 ± 25, and -18 ± 24 ml across three independent analysis methods. Average surface distance errors were largest in the basal-anterolateral segment (11-15 mm) and smallest in the mid-inferoseptal segment (6 mm). Larger errors were associated with signal dropout in anterior regions and the appearance of trabeculae at the lateral wall. Conclusions: Fusion of CMR and 3D-echo provides insight into the causes of volume underestimation by 3D-echo. Systematic signal dropout and differences in appearances of trabeculae lead to discrepancies in the delineation of LV geometry at anterior and lateral regions. A better understanding of error sources across modalities may improve correlation of clinical indices between 3D-echo and CMR., Competing Interests: At study commencement, HH held a position as Advanced Development Product Manager at Siemens Healthineers and provided training toward the acquisition and analysis of 3D-echo data. JD'h currently holds research contracts with GE Vingmed. MN and AY held a research contract with Siemens Healthineers. MN was on the scientific advisory board for HeartLab NZ Ltd. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Zhao, Quill, Gilbert, Wang, Houle, Legget, Ruygrok, Doughty, Pedrosa, D'hooge, Young and Nash.)

In experimental studies on cardiac tissue, the end-systolic force-length relation (ESFLR) has been shown to depend on the mode of contraction: isometric or isotonic. The isometric ESFLR is derived from isometric contractions spanning a range of muscle lengths while the isotonic ESFLR is derived from shortening contractions across a range of afterloads. The ESFLR of isotonic contractions consistently lies below its isometric counterpart. Despite the passing of over a hundred years since the first insight by Otto Frank, the mechanism(s) underlying this protocol-dependent difference in the ESFLR remain incompletely explained. Here, we investigate the role of mechano-calcium feedback in accounting for the difference between these two ESFLRs. Previous studies have compared the dynamics of isotonic contractions to those of a single isometric contraction at a length that produces maximum force, without considering isometric contractions at shorter muscle lengths. We used a mathematical model of cardiac excitation-contraction to simulate isometric and force-length work-loop contractions (the latter being the 1D equivalent of the whole-heart pressure-volume loop), and compared Ca 2+ transients produced under equivalent force conditions. We found that the duration of the simulated Ca 2+ transient increases with decreasing sarcomere length for isometric contractions, and increases with decreasing afterload for work-loop contractions. At any given force, the Ca 2+ transient for an isometric contraction is wider than that during a work-loop contraction. By driving simulated work-loops with wider Ca 2+ transients generated from isometric contractions, we show that the duration of muscle shortening was prolonged, thereby shifting the work-loop ESFLR toward the isometric ESFLR. These observations are explained by an increase in the rate of binding of Ca 2+ to troponin-C with increasing force. However, the leftward shift of the work-loop ESFLR does not superimpose on the isometric ESFLR, leading us to conclude that while mechano-calcium feedback does indeed contribute to the difference between the two ESFLRs, it does not completely account for it., (Copyright © 2020 Guidry, Nickerson, Crampin, Nash, Loiselle and Tran.)

Models of cardiac mechanics require a well-defined reference geometry from which deformations and hence myocardial strain and stress can be calculated. In the in vivo beating heart, the load-free (LF) geometry generally cannot be measured directly, since, in many cases, there is no stage at which the lumen pressures and contractile state are all zero. Therefore, there is a need for an efficient method to estimate the LF geometry, which is essential for an accurate mechanical simulation of left ventricular (LV) mechanics, and for estimations of passive and contractile constitutive parameters of the heart muscle. In this paper, we present a novel method for estimating both the LF geometry and the passive stiffness of the myocardium. A linear combination of principal components from a population of diastolic displacements is used to construct the LF geometry. For each estimate of the LF geometry and tissue stiffness, LV inflation is simulated, and the model predictions are compared with surface data at multiple stages during passive diastolic filling. The feasibility of this method was demonstrated using synthetically deformation data that were generated using LV models derived from clinical magnetic resonance image data, and the identifiability of the LF geometry and passive stiffness parameters were analysed using Hessian metrics. Applications of this method to clinical data would improve the accuracy of constitutive parameter estimation and allow a better simulation of LV wall strains and stresses., (© 2020 John Wiley & Sons, Ltd.)

Heart failure (HF) is one of the leading causes of death worldwide. HF is associated with substantial microstructural remodeling, which is linked to changes in left ventricular geometry and impaired cardiac function. The role of myocardial remodeling in altering the mechanics of failing hearts remains unclear. Structurally based constitutive modeling provides an approach to improve understanding of the relationship between biomechanical function and tissue organization in cardiac muscle during HF. In this study, we used cardiac magnetic resonance imaging and extended-volume confocal microscopy to quantify the remodeling of left ventricular geometry and myocardial microstructure of healthy and spontaneously hypertensive rat hearts at the ages of 12 and 24 months. Passive cardiac mechanical function was characterized using left ventricular pressure-volume compliance measurements. We have developed a, to our knowledge, new structurally based biomechanical constitutive equation built on parameters quantified directly from collagen distributions observed in confocal images of the myocardium. Three-dimensional left ventricular finite element models were constructed from subject-specific in vivo magnetic resonance imaging data. The structurally based constitutive equation was integrated into geometrically subject-specific finite element models of the hearts and used to investigate the underlying mechanisms of ventricular dysfunction during HF. Using a single pair of material parameters for all hearts, we were able to produce compliance curves that reproduced all of the experimental compliance measurements. The value of this study is not limited to reproducing the mechanical behavior of healthy and diseased hearts, but it also provides important insights into the structure-function relationship of diseased myocardium that will help pave the way toward more effective treatments for HF., (Copyright © 2019 Biophysical Society. Published by Elsevier Inc. All rights reserved.)

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., Competing Interests: We declare we have no competing interests.

Many computer vision algorithms have been presented to track surface deformations, but few have provided a direct comparison of measurements with other stereoscopic approaches and physics-based models. We have previously developed a phase-based cross-correlation algorithm to track dense distributions of displacements over three-dimensional surfaces. In the present work, we compare this algorithm with one that uses an independent tracking system, derived from an array of fluorescent microspheres. A smooth bicubic Hermite mesh was fitted to deformations obtained from the phase-based cross-correlation data. This mesh was then used to estimate the microsphere locations, which were compared to stereo reconstructions of the microsphere positions. The method was applied to a 35 mm × 35 mm × 35 mm soft silicone gel cube under indentation, with three square bands of microspheres placed around the indenter tip. At an indentation depth of 4.5 mm, the root-mean-square (RMS) differences between the reconstructed positions of the microspheres and their identified positions for the inner, middle, and outer bands were 60 µm, 20 µm, and 19 µm, respectively. The usefulness of the strain-tracking data for physics-based finite element modelling of large deformation mechanics was then demonstrated by estimating a neo-Hookean stiffness parameter for the gel. At the optimal constitutive parameter estimate, the RMS difference between the measured microsphere positions and their finite element model-predicted locations was 143 µm.

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.

Although magnetic resonance elastography (MRE) has been used to estimate isotropic stiffness in the heart, myocardium is known to have anisotropic properties. This study investigated the determinability of global transversely isotropic material parameters using MRE and finite-element modeling (FEM). A FEM-based material parameter identification method, using a displacement-matching objective function, was evaluated in a gel phantom and simulations of a left ventricular (LV) geometry with a histology-derived fiber field. Material parameter estimation was performed in the presence of Gaussian noise. Parameter sweeps were analyzed and characteristics of the Hessian matrix at the optimal solution were used to evaluate the determinability of each constitutive parameter. Four out of five material stiffness parameters (Young's modulii E 1 and E 3 , shear modulus G 13 and damping coefficient s), which describe a transversely isotropic linear elastic material, were well determined from the MRE displacement field using an iterative FEM inversion method. However, the remaining parameter, Poisson's ratio, was less identifiable. In conclusion, Young's modulii, shear modulii and damping can theoretically be well determined from MRE data, but Poisson's ratio is not as well determined and could be set to a reasonable value for biological tissue (close to 0.5)., (Copyright © 2017 John Wiley & Sons, Ltd.)

Objective: The electrocardiogram (ECG) provides an effective, non-invasive approach for clinical diagnosis in patients with cardiac diseases such as atrial fibrillation (AF). AF is the most common cardiac rhythm disturbance and affects ~2% of the general population in industrialized countries. Automatic AF detection in clinics remains a challenging task due to the high inter-patient variability of ECGs, and unsatisfactory existing approaches for AF diagnosis (e.g. atrial or ventricular activity-based analyses)., Approach: We have developed RhythmNet, a 21-layer 1D convolutional recurrent neural network, trained using 8528 single-lead ECG recordings from the 2017 PhysioNet/Computing in Cardiology (CinC) Challenge, to classify ECGs of different rhythms including AF automatically. Our RhythmNet architecture contained 16 convolutions to extract features directly from raw ECG waveforms, followed by three recurrent layers to process ECGs of varying lengths and to detect arrhythmia events in long recordings. Large 15  ×  1 convolutional filters were used to effectively learn the detailed variations of the signal within small time-frames such as the P-waves and QRS complexes. We employed residual connections throughout RhythmNet, along with batch-normalization and rectified linear activation units to improve convergence during training., Main Results: We evaluated our algorithm on 3658 testing data and obtained an F 1 accuracy of 82% for classifying sinus rhythm, AF, and other arrhythmias. RhythmNet was also ranked 5th in the 2017 CinC Challenge., Significance: Potentially, our approach could aid AF diagnosis in clinics and be used for patient self-monitoring to improve the early detection and effective treatment of AF.

Understanding the aetiology of heart failure with preserved (HFpEF) and reduced (HFrEF) ejection fraction requires knowledge of biomechanical factors such as diastolic myocardial stiffness and stress. Cine CMR images and intra-ventricular pressure recordings were acquired in 8 HFrEF, 11 HFpEF and 5 control subjects. Diastolic myocardial stiffness was estimated using biomechanical models and found to be greater in HFrEF (6.4 ± 1.2 kPa) than HFpEF (2.7 ± 0.6 kPa, p < 0.05) and also greater than control (1.2 ± 0.4 kPa, p < 0.005). End-diastolic mid-ventricular myofibre stress derived from the personalised biomechanics model was higher in HFrEF (2.9 ± 0.3 kPa) than control (0.9 ± 0.3 kPa, p < 0.01). Chamber stiffness, measured from the slope of the diastolic pressure-volume relationship, is determined by the intrinsic tissue properties as well as the size and shape of the heart, and was unable to distinguish between any of the three groups (p > 0.05). Personalised biomechanical analysis may provide more specific information about myocardial mechanical behaviour than global chamber indices, which are confounded by variations in ventricular geometry.

In this paper, we present a novel approach to quantify the spatio-temporal organization of electrical activation during human ventricular fibrillation (VF). We propose three different methods based on correlation analysis, graph theoretical measures and hierarchical clustering. Using the proposed approach, we quantified the level of spatio-temporal organization during three episodes of VF in ten patients, recorded using multi-electrode epicardial recordings with 30 s coronary perfusion, 150 s global myocardial ischaemia and 30 s reflow. Our findings show a steady decline in spatio-temporal organization from the onset of VF with coronary perfusion. We observed transient increases in spatio-temporal organization during global myocardial ischaemia. However, the decline in spatio-temporal organization continued during reflow. Our results were consistent across all patients, and were consistent with the numbers of phase singularities. Our findings show that the complex spatio-temporal patterns can be studied using complex network analysis.

Magnetic resonance elastography (MRE) has been used to estimate isotropic myocardial stiffness. However, anisotropic stiffness estimates may give insight into structural changes that occur in the myocardium as a result of pathologies such as diastolic heart failure. The virtual fields method (VFM) has been proposed for estimating material stiffness from image data. This study applied the optimised VFM to identify transversely isotropic material properties from both simulated harmonic displacements in a left ventricular (LV) model with a fibre field measured from histology as well as isotropic phantom MRE data. Two material model formulations were implemented, estimating either 3 or 5 material properties. The 3-parameter formulation writes the transversely isotropic constitutive relation in a way that dissociates the bulk modulus from other parameters. Accurate identification of transversely isotropic material properties in the LV model was shown to be dependent on the loading condition applied, amount of Gaussian noise in the signal, and frequency of excitation. Parameter sensitivity values showed that shear moduli are less sensitive to noise than the other parameters. This preliminary investigation showed the feasibility and limitations of using the VFM to identify transversely isotropic material properties from MRE images of a phantom as well as simulated harmonic displacements in an LV geometry., (Copyright © 2018 John Wiley & Sons, Ltd.)

Abusive head trauma (AHT) is a potentially fatal result of child abuse, but the mechanisms by which injury occur are often unclear. To investigate the contention that shaking alone can elicit the injuries observed, effective computational models are necessary. The aim of this study was to develop a probabilistic model describing infant head kinematics in AHT. A deterministic model incorporating an infant's mechanical properties, subjected to different shaking motions, was developed in OpenSim. A Monte Carlo analysis was used to simulate the range of infant kinematics produced as a result of varying both the mechanical properties and the type of shaking motions. By excluding physically unrealistic shaking motions, worst-case shaking scenarios were simulated and compared to existing injury criteria for a newborn, a 4.5 month-old, and a 12 month-old infant. In none of the three cases were head kinematics observed to exceed previously-estimated subdural haemorrhage injury thresholds. The results of this study provide no biomechanical evidence to demonstrate how shaking by a human alone can cause the injuries observed in AHT, suggesting either that additional factors, such as impact, are required, or that the current estimates of injury thresholds are incorrect.

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 anesthesia seemed protective (p = 0.03)., Conclusions: Quantification of levator-ani muscle stiffness is feasible. Muscle stiffness is significantly different before and after birth., (© 2017 Nordic Federation of Societies of Obstetrics and Gynecology.)

A triaxial force-sensitive microrobot was developed to dynamically perturb skin in multiple deformation modes, in vivo. Wiener static nonlinear identification was used to extract the linear dynamics and static nonlinearity of the force-displacement behavior of skin. Stochastic input forces were applied to the volar forearm and thenar eminence of the hand, producing probe tip perturbations in indentation and tangential extension. Wiener static nonlinear approaches reproduced the resulting displacements with variances accounted for (VAF) ranging 94-97%, indicating a good fit to the data. These approaches provided VAF improvements of 0.1-3.4% over linear models. Thenar eminence stiffness measures were approximately twice those measured on the forearm. Damping was shown to be significantly higher on the palm, whereas the perturbed mass typically was lower. Coefficients of variation (CVs) for nonlinear parameters were assessed within and across individuals. Individual CVs ranged from 2% to 11% for indentation and from 2% to 19% for extension. Stochastic perturbations with incrementally increasing mean amplitudes were applied to the same test areas. Differences between full-scale and incremental reduced-scale perturbations were investigated. Different incremental preloading schemes were investigated. However, no significant difference in parameters was found between different incremental preloading schemes. Incremental schemes provided depth-dependent estimates of stiffness and damping, ranging from 300 N/m and 2 Ns/m, respectively, at the surface to 5 kN/m and 50 Ns/m at greater depths. The device and techniques used in this research have potential applications in areas, such as evaluating skincare products, assessing skin hydration, or analyzing wound healing.

The spontaneously hypertensive rat (SHR) is an established model of human hypertensive heart disease transitioning into heart failure. The study of the progression to heart failure in these animals has been limited by the lack of longitudinal data. We used MRI to quantify left ventricular mass, volume, and cardiac work in SHRs at age 3 to 21 month and compared these indices to data from Wistar-Kyoto (WKY) controls. SHR had lower ejection fraction compared with WKY at all ages, but there was no difference in cardiac output at any age. At 21 month the SHR had significantly elevated stroke work (51 ± 3 mL.mmHg SHR vs. 24 ± 2 mL.mmHg WKY; n = 8, 4; P < 0.001) and cardiac minute work (14.2 ± 1.2 L.mmHg/min SHR vs. 6.2 ± 0.8 L.mmHg/min WKY; n = 8, 4; P < 0.001) compared to control, in addition to significantly larger left ventricular mass to body mass ratio (3.61 ± 0.15 mg/g SHR vs. 2.11 ± 0.008 mg/g WKY; n = 8, 6; P < 0.001). SHRs showed impaired systolic function, but developed hypertrophy to compensate and successfully maintained cardiac output. However, this was associated with an increase in cardiac work at age 21 month, which has previously demonstrated fibrosis and cell death. The interplay between these factors may be the mechanism for progression to failure in this animal model., (© 2017 The Authors. Physiological Reports published by Wiley Periodicals, Inc. on behalf of The Physiological Society and the American Physiological Society.)

Cardiac myofibre deformation is an important determinant of the mechanical function of the heart. Quantification of myofibre strain relies on 3D measurements of ventricular wall motion interpreted with respect to the tissue microstructure. In this study, we estimated in vivo myofibre strain using 3D structural and functional atlases of the human heart. A finite element modelling framework was developed to incorporate myofibre orientations of the left ventricle (LV) extracted from 7 explanted normal human hearts imaged ex vivo with diffusion tensor magnetic resonance imaging (DTMRI) and kinematic measurements from 7 normal volunteers imaged in vivo with tagged MRI. Myofibre strain was extracted from the DTMRI and 3D strain from the tagged MRI. We investigated: i) the spatio-temporal variation of myofibre strain throughout the cardiac cycle; ii) the sensitivity of myofibre strain estimates to the variation in myofibre angle between individuals; and iii) the sensitivity of myofibre strain estimates to variations in wall motion between individuals. Our analysis results indicate that end systolic (ES) myofibre strain is approximately homogeneous throughout the entire LV, irrespective of the inter-individual variation in myofibre orientation. Additionally, inter-subject variability in myofibre orientations has greater effect on the variabilities in myofibre strain estimates than the ventricular wall motions. This study provided the first quantitative evidence of homogeneity of ES myofibre strain using minimally-invasive medical images of the human heart and demonstrated that image-based modelling framework can provide detailed insight to the mechanical behaviour of the myofibres, which may be used as a biomarker for cardiac diseases that affect cardiac mechanics.

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., (© 2016 Wiley Periodicals, Inc.)

With heart and cardiovascular diseases continually challenging healthcare systems worldwide, translating basic research on cardiac (patho)physiology into clinical care is essential. Exacerbating this already extensive challenge is the complexity of the heart, relying on its hierarchical structure and function to maintain cardiovascular flow. Computational modelling has been proposed and actively pursued as a tool for accelerating research and translation. Allowing exploration of the relationships between physics, multiscale mechanisms and function, computational modelling provides a platform for improving our understanding of the heart. Further integration of experimental and clinical data through data assimilation and parameter estimation techniques is bringing computational models closer to use in routine clinical practice. This article reviews developments in computational cardiac modelling and how their integration with medical imaging data is providing new pathways for translational cardiac modelling.

Models of cardiac mechanics are increasingly used to investigate cardiac physiology. These models are characterized by a high level of complexity, including the particular anisotropic material properties of biological tissue and the actively contracting material. A large number of independent simulation codes have been developed, but a consistent way of verifying the accuracy and replicability of simulations is lacking. To aid in the verification of current and future cardiac mechanics solvers, this study provides three benchmark problems for cardiac mechanics. These benchmark problems test the ability to accurately simulate pressure-type forces that depend on the deformed objects geometry, anisotropic and spatially varying material properties similar to those seen in the left ventricle and active contractile forces. The benchmark was solved by 11 different groups to generate consensus solutions, with typical differences in higher-resolution solutions at approximately 0.5%, and consistent results between linear, quadratic and cubic finite elements as well as different approaches to simulating incompressible materials. Online tools and solutions are made available to allow these tests to be effectively used in verification of future cardiac mechanics software.