Annals of Biomedical Engineering

BackgroundConventional left ventricular assist device ramp metrics are load dependent, obscuring intrinsic myocardial recovery. A mechanistic, patient-specific representation of ventricular mechanics, identifiable from routine clinical data, could provide quantitative indices of intrinsic left ventricular (LV) function for longitudinal recovery surveillance. ObjectiveTo develop and verify a ramp-integrated, patient-specific model of HeartMate 3-assisted LV function that can yield indices of intrinsic myocardial contractility and remodeling. MethodsWe represented LV pressure-volume (PV) behavior with a PV envelope composed of a monotonic passive PV relation (pPVR) and a unimodal active PV relation (aPVR). We developed a parameterization procedure to infer the patient-specific shape of this envelope directly from routine ramp-test data. We then embedded the parameterized envelope within the PSCOPE framework, a hybrid platform that couples a lumped-parameter network to a physical HeartMate 3 flow loop, to reproduce clinical ramp hemodynamics. Percent residuals between simulated outputs and the corresponding clinical measurements verified the implementation of the PV envelope within PSCOPE. ResultsIn three HeartMate 3 recipients, the PSCOPE models reproduced ramp hemodynamics with residuals generally [≤] 20% across pump speeds and measured variables. Cardiac index residuals ranged from 0-18.5%, systemic and pulmonary arterial pressure residuals remained [≤] 18.4%, and pulmonary arterial wedge pressure residuals remained [≤] 20%. The PSCOPE models matched central venous pressure within [≤] 3 mmHg in all cases, although one setting yielded a 33.3% residual due to a low reference pressure. For one patient, the model reproduced ramp hemodynamics at a speed deliberately withheld from PV-envelope parameterization with residuals [≤] 10%, supporting cross-speed generalizability. Patient-specific PV envelopes also revealed clinically meaningful heterogeneity in LV diastolic stiffness, volume threshold for declining systolic function, operating PV points for peak systolic function, and contractile reserve. ConclusionsRamp-integrated parameterization of the monotonic pPVR and unimodal aPVR yields a compact, mechanistic PV envelope that is identifiable from routine clinical data and verifiable within PSCOPE. The resulting indices characterize intrinsic LV function and may enhance longitudinal recovery surveillance and inform LVAD management. Prospective multicenter validation is warranted to confirm the generalizability and clinical utility of this approach.

IntroductionStereological estimates of villous membrane thickness and surface area are widely used to infer the diffusive exchange capacity of the human placenta. A key geometric determinant of exchange capacity can be expressed as an effective diffusive length scale. Here we combine virtual histological sections with computational modelling in realistic villous geometries to assess the accuracy of classical stereological estimates of this diffusive length scale. MethodsTwo terminal villi, reconstructed from three-dimensional imaging, were digitally sectioned to generate random two-dimensional geometries containing fetal capillaries and surrounding villous tissue. For each section, we simulated steady diffusive transport between the fetal capillary and intervillous space boundaries to obtain a physics-based diffusive length scale as a reference case. Using the same geometries, we applied standard line-intercept stereology to measure harmonic-mean barrier thickness and boundary-length densities, from which a stereological estimate of diffusive length scale was derived. ResultsAcross both villi, stereology systematically overestimated the diffusive length scale by approximately 15-25%, depending on villus and section. We identified sources of this discrepancy, including interface curvature and assumptions underpinning the stereological correction factors, using idealised models of villus structure. ConclusionThese findings highlight the need for stereological approaches that account for curvature when interpreting placental structure-function relationships.

The arteriovenous fistula (AVF) is the preferred method of vascular access for hemodialysis; however, 30-50% of AVFs undergo primary failure and are unsuitable for clinical use. As disturbed hemodynamics initiate endothelial injury and intimal hyperplasia, we designed an endovascular flow-conditioning anastomotic device (FCAD) to directly improve AVF hemodynamics and protect the anastomotic region. Using computational fluid dynamics, we characterized the flow field and wall shear stress (WSS) profiles in idealized AVF models with and without the FCAD. Incorporation of the FCAD into a brachiocephalic AVF model reduced regions of oscillatory WSS and generated a symmetrical flow profile in the draining vein compared to a reference AVF. Parametric studies also identified an FCAD geometry with a tab angle, height, and aspect ratio of 30{degrees}, 0.1 diameters, and 1.0 restored time-averaged WSS along the inner venous wall, achieving a physiological level without inducing regions of oscillatory flow throughout the cardiac cycle. Similar findings were observed with an in vitro model using particle imaging velocimetry. This study demonstrates the feasibility of the FCAD to normalize venous flow and WSS while imposing minimal resistance to blood flow. Restoring physiological WSS levels on the venous wall is expected to preserve endothelial function and improve AVF maturation.

PurposeTo investigate the interplay between biomechanics, fluid dynamics, and solute transport in Diabetic Macular Oedema (DMO) using a mechanics-based computational model, aiming to elucidate mechanisms behind variable treatment outcomes. MethodsWe developed a multiphysics model of the retina within a porous media framework. The model integrates OCT-derived geometry, vascular leakage, retinal biomechanics (including Muller cell fibre architecture), retinal pigment epithelium (RPE) function, and anti-VEGF transport. We simulated oedema development and therapeutic response by varying these parameters systematically. ResultsModel results showed that active RPE pumping is essential for maintaining retinal dehydration. Our simulations revealed a critical trade-off related to Muller cell architecture: the physiological z-shaped orientation protects against oedema but impedes anti-VEGF drug delivery to leaky vessels. In contrast, a pathological, vertical Muller cell alignment increases oedema susceptibility but allows for a faster therapeutic response due to improved drug diffusion. ConclusionsMuller cell orientation presents a trade-off between biomechanical protection and therapeutic efficacy, offering a novel mechanistic explanation for the variable patient responses to anti-VEGF therapy observed clinically. This in-silico framework is a powerful tool for dissecting DMO pathophysiology and has the potential to guide the development of personalised treatment strategies.

SignificanceMastectomy skin flap necrosis remains a major complication in implant-based breast reconstruction due to inadequate tissue blood flow. Existing diagnostic technologies are limited by shallow depth sensitivity, dye-related risks, contact requirements, and an inability to continuously assess blood flow. AimThis study aimed to translate a noncontact, dye-free, depth-sensitive speckle contrast diffuse correlation tomography (scDCT) technique to a clinically relevant porcine skin flap model for assessing flap blood flow and viability. ApproachThe scDCT system was optimized to image blood flow over seven days in four porcine skin flaps including Sham (SH), Implant (IM), Half Necrosis (HN), and Full Necrosis (FN). Measurements were compared with indocyanine green angiography (ICG-A) as a reference standard. ResultsscDCT enabled longitudinal monitoring of flap blood flow, revealing significant flow differences among flap types and over time. FN flaps consistently exhibited the most severe flow impairment, while other flap types showed partial or complete recovery over time, distinguishing nonviable from viable tissue. scDCT measurements demonstrated moderate to strong correlations with ICG-A across time points. ConclusionsThe findings support scDCT as a promising perioperative imaging modality for improving flap necrosis risk stratification and surgical decision-making, with future work focused on large-scale validation and clinical translation.

RationaleRespiratory diseases are a source of immense socioeconomic burden globally. In silico approaches can predict changes in human lung function due to disease or response to therapy. By stratifying patient-specific response a priori, these models can enable clinical-scale deployment of precision medicine strategies. Key to this is developing accurate organ geometries on which the models can be simulated. However, we lack analyses assessing the clinical applicability of reported airway dimension estimates. ObjectiveTo investigate physiologically-/anatomically-relevant airway dimension estimates and evaluate consistency across reported literature. MethodsWe conducted a systematic review of 37 published datasets. Airway wall thickness estimates were mined for healthy subjects and patients, and standardised to the Horsfield order airway generations. We simulated dynamic lung function to quantitatively assess their physiological relevance. We created an online database to make all datasets available to the research community. Measurements and Main ResultsReported human airway wall thickness estimates are inconsistent across studies. K-means clustering divided estimates for healthy subjects and patients into three and four clusters, respectively. Only one of the clusters in each category yielded anatomically-relevant estimates. Pressure-volume curves generated to assess physiological relevance also showed that only one cluster in each category exhibited plausible physiology. Principal Component Analysis weakly implicated imaging modalities to explain this inconsistency. ConclusionsReported airway dimension estimates are inconsistent and lack standardisation. To support future modelling efforts, we report physiologically-relevant estimates and introduce an open-access airway-dimension database to help standardise geometric inputs and quantify how measurement variability propagates to functional predictions.

Background and ObjectivesLung cancer is one of the most frequently diagnosed cancers worldwide. While non-surgical treatment options have increased in number and efficacy, lung resection for primary cancers is still a mainstay of treatment. Lung resection has been shown to impair right ventricular function, although the mechanism for the impairment remains unclear. Wave intensity is increasingly used as a metric for increased post-operative afterload. Here, we develop a computational framework to assess the impact of simulated lung resection on wave intensity to establish that post-operative changes in wave intensity are attributable to the change in pulmonary artery morphometry. MethodsWe analyse a 48 pulmonary arterial surfaces segmented from CT images in patients with no evidence of lung disease to obtain 1D representations of the pulmonary vasculature. For each pulmonary vasculature we sequentially remove vessel branches to mimic post-operative morphometric changes to the arterial network. Using an established 1D computational flow model, we simulate pulsate blood flow in 44 pre-operative cases and 1596 post-operative cases. We compute wave intensity in the main, right, and left pulmonary arteries for all simulations. ResultsWe compare the change in computed wave intensities pre-versus post-operatively to the results of an experimental clinical study comparing pre- and post-operative wave intensity in a 27 patient cohort. We see good agreement between the changes in the parameters of wave intensity between this study and those reported in the clinical study. Further, we capture flow distribution the changes pre-versus post-operatively which indicates that the computational model behaves as expected. ConclusionsIn this preliminary study on a computational framework to capture changes in pulmonary arterial haemodynamics following lung resection, we have shown that our model and analysis pipeline is capable of capturing post-operative changes to wave intensity and flow redistribution between the pulmonary arteries following lung resection. These results motivate further research to develop and validate a patient specific model which is an area of active research for us.

PurposeEndovascular therapy is preferred over open surgery due to its minimally invasive nature, faster recovery, and lower perioperative risk; however, fluoroscopy guided procedures are limited by radiation exposure, high equipment costs, and reliance on highly skilled operators. This study aims to develop and evaluate a lightweight, portable robotic system for autonomous guidewire navigation to improve safety, accessibility, and operator independence. MethodsA compact 400 g robotic device was designed with millimeter scale positioning accuracy, servo current based real-time haptic feedback, precise axial rotation, automated retraction advance control, and compatibility with standard endovascular tools. Miniature linear actuated servomotors replicate skilled manual maneuvers using impedance control. Upon tip contact, the system advances the guidewire by 1 mm, measures current changes, classifies lesion stiffness (soft, medium, stiff), and adapts virtual mass-spring-damper gains to regulate push speed and applied force. Bench experiments were conducted using flexible tubing with inserts simulating 20-80% stenosis and two current thresholds (75 mA and 94 mA). ResultsRetraction frequency increased with stenosis severity, validating the autonomous control strategy. Lesion stiffness classification achieved F-scores of 0.83, 0.77, and 0.95 for soft, medium, and stiff conditions, respectively, demonstrating reliable discrimination and adaptive force modulation. ConclusionsThe proposed system enables autonomous and adaptive guidewire advancement with high classification accuracy using low-cost, current based sensing and impedance control. Its lightweight and portable design reduces dependence on continuous manual operation and specialized imaging infrastructure, supporting safer and faster interventions and potential deployment in prehospital or resource-limited settings. This prototype advances the development of more accessible and operator-independent endovascular therapy.

BackgroundTranscranial focused ultrasound (tFUS) is an emerging noninvasive neuromodulation modality with the ability to target deep brain structures with high spatial precision. Despite its promise, rigorous evaluation of its efficacy is limited by the absence of reliable, fully double-blind sham methodologies. ObjectiveTo develop and validate a pair of visually and mechanically indistinguishable acoustic coupling pads that enable true double-blind tFUS neuromodulation studies by providing either efficient ultrasound transmission or robust ultrasound blocking without altering participant or operator experience. MethodsTwo coupling pads were engineered: a transmitting pad designed to allow <5% pressure amplitude loss relative to free-water propagation, and a non-transmitting pad designed to attenuate ultrasound by [&ge;]40 dB. Both pads used a Dragon Skin 10 NV silicone base and were identical in size, appearance, flexibility, and handling. The non-transmitting pad incorporated an encapsulated air-based blocking layer using an open-cell polyethylene foam insert. Acoustic performance was evaluated in a water tank using a 650 kHz BrainSonix transducer and a calibrated needle hydrophone. Sound speed of the silicone material was measured using pulse-echo techniques. ResultsTwenty-three matched transmitting and non-transmitting pad pairs were fabricated and tested. Transmitting pads demonstrated a mean attenuation of -0.41 {+/-} 0.53 dB, satisfying the design criterion of minimal acoustic loss.Non-transmitting pads demonstrated a mean attenuation of -48.61 {+/-} 4.33 dB, exceeding the required -40 dB threshold for effective sham conditions. The Dragon Skin 10 NV substrate exhibited a sound speed of 964.72 m/s and produced <2 mm axial focal shift for standard pad thicknesses, with no measurable change in focal width. Both pad types were visually and tactually indistinguishable, could not be differentiated by experienced operators or participants, and maintained mechanical integrity after repeated cleaning ConclusionThese acoustically engineered coupling pads provide a practical and validated solution for achieving true single- and double-blind conditions in tFUS neuromodulation studies. By preserving identical sensory and procedural experiences while enabling precise control over ultrasound transmission, this approach addresses a critical methodological gap in human ultrasound neuromodulation research.

ObjectivePulsed field ablation (PFA) relies on irreversible electroporation to create nonthermal cardiac lesions, yet real-time indicators of electroporation progression and validated lethal electric field thresholds remain limited. This study aimed to develop a bioimpedance-based metric for real-time monitoring of cardiac electroporation, evaluate the impact of myocardial anisotropy under electroporation conditions, and derive waveform-specific lethal electric field thresholds. IntroductionCurrent PFA procedures lack direct intraoperative feedback on lesion formation, and uncertainty remains regarding the role of myocardial fiber orientation in shaping electric field distributions. Because electroporation dynamically alters tissue electrical properties, monitoring these changes during treatment may improve prediction of ablation outcomes. MethodsPFA was delivered to fresh ex vivo porcine ventricular tissue using clinically relevant and energy-matched waveforms with pulse widths from 1 to 100 {micro}s. Inter-burst broadband electrical impedance spectroscopy was performed using a low-voltage diagnostic waveform to quantify burst-resolved impedance changes. Lesions were visualized using metabolic staining, then finite element models incorporating nonlinear electroporation-dependent conductivity were used to compare anisotropic and homogenized electric field distributions. Lethal electric field thresholds were estimated by fitting simulated contours to measured lesion areas and validated using uniform electric fields generated by a parallel electrode array. ResultsAcross all waveforms, impedance measurements showed a rapid initial decrease followed by stabilization, indicating early electroporation saturation. Burst-to-burst percent change in impedance slope provided a consistent, waveform-agnostic metric of electroporation progression. Lesion morphology was not systematically influenced by fiber orientation, and modeling demonstrated that electroporation-induced conductivity increases homogenized tissue anisotropy. Lethal electric field thresholds increased with decreasing pulse width, ranging from 517 {+/-} 46 V/cm (100 {micro}s) to 1405 {+/-} 55 V/cm (1 {micro}s), and were validated under uniform field conditions. ConclusionBioimpedance-assisted monitoring enables real-time assessment of cardiac electroporation, while electroporation-induced homogenization supports simplified modeling and standardized PFA treatment design.

The effects of specific footwear features on biomechanical parameters are often confounded by simultaneous changes in other shoe conditions, making it difficult to identify the isolated effect of material and design properties on relevant biomechanical outcomes. This study aimed to propose a tool, namely the Modular Footwear Setup (MFS), to assess the effects of midsole modifications on lower limb joint kinematics and in-shoe plantar pressure. The MFS uses a micro-hook-and-loop fastening system and a custom alignment device to enable fast, strong, and reliable midsole attachment/detachment to/from the upper. Accuracy and repeatability of the MFS in replicating the biomechanical outcomes of a control shoe featuring the same upper and midsole were tested in 10 healthy participants (5M,5F; age=33.2{+/-}9.2 yrs; BMI=21.5{+/-}2.8 kg/m2). Participants were asked to walk wearing both the MFS and the standard control shoe in three sessions. Kinematics of lower limb joints were measured via inertial measurement units, while capacitive pressure insoles were used to measure in-shoe plantar pressure. Intraclass correlation coefficient (ICC) was used to assess the repeatability of kinematic and pressure measurements between sessions. Statistical Parametric Mapping analysis did not identify significant differences in joint kinematics between conditions. While the MFS exhibited slightly lower peak pressure at the rearfoot, pressure parameters were not statistically different in the other foot regions. The MFS demonstrated good-to-excellent inter-session repeatability (ICC 0.84-0.97) for peak and mean pressure. Participants reported similar levels of comfort and stability in both shoes. The findings of the present study suggest the MFS has the potential to be a reliable and accurate tool for evaluating the effect of midsole features on relevant biomechanical parameters. This modular approach may improve data-driven footwear design by providing a consistent platform for testing the effects of midsole designs and materials across various applications, including therapeutic, safety, and athletic shoes.

It is increasingly necessary to both study biology in 3D and obtain quantitative measurements. Not all 3D-reconstructions are created equal, particularly when using the anatomical model as a basis for force calculations, i.e. computational modeling. Here, we compare 3D anatomical reconstructions from two emerging imaging modalities: 4D ultrasound (4DUS) and light sheet fluorescent microscopy (LSFM) against our previous nano-computed tomography (nanoCT) cohort data, using the tortuous highly intricate pharyngeal arch artery system of the chick embryo as a test bed. We highlight modality-specific morphological image acquisition discrepancies and their influence on subsequent computational fluid dynamics results. Overall, LSFM accurately captured quantitative volumetric measurements of small rapidly-changing vascular morphologies while 4DUS systematically inflated small tortuous vessels. Differences in image-based morphology changes led to significant changes in computationally-obtained force magnitudes and flow patterns linked to vessel angle and tortuosity. This validates LSFM as a comparative preclinical vascular quantitative imaging tool and suggests that 4DUS needs extensive 3D anatomical validation for non cardiac chamber vessels.

Deep vein thrombosis (DVT) is a prevalent vascular condition in which venous anatomy and flow disturbances contribute to the risk of thrombosis, but the mechanistic links between vessel shape and haemodynamics remain poorly quantified. Although computational fluid dynamics (CFD) can estimate flow-related risk metrics such as low wall shear stress (WSS), the influence of anatomical fidelity on these predictions is not well understood. Statistical shape modelling (SSM) offers a principled framework for characterising geometric variability, but its integration with CFD in venous applications is still emerging. This study investigates how different levels of anatomical representation--2D projections, simplified 3D extrusions, and full 3D reconstructions of the common iliac veins--influence both the statistical structure of venous shape variability and the haemodynamic metrics derived from CFD. Using patient-specific MRI/CT data from twelve cases, we constructed SSMs in Deformetrica and performed steady-state CFD simulations in ANSYS Fluent under standardised inflow conditions. We compared the variance structure of the 2D and 3D latent spaces and quantified correlations between principal shape modes and low-WSS burden across three thresholds ([&le;] 0.05, 0.10, 0.15 [Pa]). Idealised 3D geometries consistently produced larger low-WSS areas than patient-specific shapes, with average increases of 118-136% across thresholds. The 2D SSM exhibited a strongly hierarchical variance spectrum with one dominant mode that correlated significantly with WSS, whereas the 3D SSM showed a flatter spectrum with weaker univariate associations. These findings demonstrate that geometric fidelity and alignment strategy critically influence shape-flow relationships, highlighting the need for careful model selection when using CFD-based haemodynamic indicators in DVT research. Author summaryDeep vein thrombosis (DVT) is a common condition in which blood clots form in the deep veins of the leg and can lead to serious long-term complications. Although medical imaging captures important anatomical differences between patients, it remains unclear how these variations in vein shape influence local blood flow and the associated risk of clot formation. To address this challenge, we developed a computational framework that combines statistical shape modelling (SSM) with computational fluid dynamics (CFD) to analyse the relationship between venous geometry and haemodynamic risk factors. We examined the common iliac veins at three levels of anatomical detail: simplified two-dimensional projections, intermediate three-dimensional extrusions, and full three-dimensional reconstructions derived from MRI/CT data. By comparing these representations, we show that geometric fidelity strongly affects both the detected modes of anatomical variation and the resulting flow predictions. Simplified geometries consistently overestimated regions of low wall shear stress, a flow feature associated with thrombosis, compared to full 3D models. We also found that shape-flow associations depend heavily on how shapes are aligned and represented. Our findings highlight the importance of anatomical detail in computational venous modelling and provide a foundation for more personalised, simulation-based tools to support DVT treatment.

BackgroundPersonalized computational neuromusculoskeletal models have great potential for optimizing the design of clinical treatments for movement impairments. While many software tools address specific parts of the model personalization and treatment optimization processes, they typically require significant programming experience to use and do not cover the full breadth of these two processes. Furthermore, published neuromusculoskeletal modeling studies typically do not provide all of the minute methodological details needed for others to reproduce the work. Consequently, researchers seeking to develop skills in the model personalization and treatment optimization processes face a steep learning curve due to the lack of detailed training materials that demonstrate both processes for real-life clinical problems using real-life subject movement data. MethodsThis article presents detailed training tutorials for the model personalization and treatment optimization processes using two real-life clinical problems and the Neuromusculoskeletal Modeling (NMSM) Pipeline. The first clinical problem involves the design of personalized gait modifications and high tibial osteotomy surgery for an individual with bilateral medial knee osteoarthritis, where the goal is to reduce the peak adduction moment in both knees to a specified target level. The second clinical problem involves the design of a synergy-based functional electrical stimulation prescription for an individual post-stroke with impaired walking function, where the goal is to equalize the propulsive and braking impulses between the two legs. Both tutorials were evaluated as course projects given to novice users in a combined undergraduate/graduate mechanical engineering course. ResultsBoth tutorials produced personalized neuromusculoskeletal models and associated dynamically consistent tracking optimizations that closely reproduced subject-specific experimental joint angles, joint moments, ground reaction forces and moments, and (if applicable) muscle activations measured during walking. Subsequent design optimizations predicted personalized treatments that achieved target values of peak knee adduction moments or propulsive and braking impulses. ConclusionsThe detailed step-by-step tutorials presented with this article are the first to walk users step-by-step through the entire process of creating personalized neuromusculoskeletal models and then using them to design personalized treatments for clinical problems. These tutorials can be used to introduce new users to the NMSM Pipeline and as projects in neuromusculoskeletal modeling courses.

Selecting suitable tribo-pairs is crucial for measuring the tribological properties of the blinking process, especially for dry eye disease research. The tribo-pairs, lubricants, loads, and sliding speeds used in the friction models reported so far vary greatly, which limits the development of artificial tear fomulations, that could be effective in treating the effects of dry eye disease. This study compares tribo-pairs under the same experimental conditions and provides a test model closer to the real physiological blinking environment. This study proposes a to use the porcine eyeball-eyelid tribo-pair as an ex vitro tissue friction model to explore the tribological behavior during blinking. Additionally, the presence of mucin on the eyelids and cornea was detected. The tribo-pair was compared with the eyeball-glass and eyeball-mucin coated glass tribo-pairs in terms of friction coefficient, relief time, and wear. Artificial tribo-pairs such as contact lens-glass or contact lens-mucin coated glass were not included because of their irrelevance to dry eye disease. The results showed that the static friction coefficient of the eyelid/eyeball tribo-pairs was significantly lower than that of the bare glass/eyeball group. In addition, its dynamic friction coefficient was higher than that of the glass/eyeball tribo-pairs, but the friction damage caused was lower than that of the glass/eyeball group. The relief period (RP) of the eyelid/eyeball tribo-pair was significantly higher than that of bare glass and mucin-coated glass, showing stronger hydrophilicity within this system. To conduct relevant dry eye disease (DED) research, it is critical to simulate the natural eyelid-eyeball friction system as realistically as possible. Despite its limitations, the use of the porcine eye as an in vitro model provides a structurally and biomechanically realistic platform to capture the key interactions between the eyelid and the ocular surface. This approach allows for a more accurate assessment of friction, tear film dynamics, and therapeutic interventions in dry eye.

BackgroundIn aortic arch surgery, bilateral selective antegrade cerebral perfusion (bSACP) maintains cerebral blood flow during circulatory arrest. bSACP is often delivered using a single pump with a Y-connector, dividing the flow. Current practice has veered towards perfusion of the left common carotid artery by cannula and the right subclavian artery or axillary artery by a vascular graft. Under this configuration, inflow distribution may be sensitive to left-sided cannula resistance, particularly in patients with limited collateral circulation, potentially reducing left-hemispheric pressure and flow despite bSACP. We investigated how cannula design influences perfusion pressure and arterial inflow distribution during bSACP. MethodsFour perfusion cannulas with different flow resistances were characterized using bench measurements (40-200 ml/min) and computational fluid dynamics (CFD). The CFD cannula models were then integrated into patient-specific CFD models of the cerebral circulation from three patients with varying collateral circulation/capacity. Both flow- and pressure-controlled pump strategies were simulated. ResultsBench measurements showed substantial variation in flow resistance between the cannulas, which was accurately reproduced by CFD. For the patient-specific analysis, cannula choice affected perfusion through roughly doubled pressure laterality and halved left-side inflow between the most extreme cannulas. Still, perfusion pressure was kept within recommended levels in two subjects but was low in one. Left-side arterial inflow varied between 70-150 ml/min. ConclusionsWe isolated the effects of cannula design on cerebral pressure and blood inflow distribution during bSACP, highlighting potential pitfalls in patients with limited collateral circulation.

ObjectiveAchilles tendon ruptures lead to long-term structural and functional deficits. Prior research that sought to identify optimal rehabilitation techniques was fundamentally limited by the inability to continuously monitor Achilles tendon loading during rehabilitation. Our objective was to develop a data-driven model that predicts per-step peak Achilles tendon loading from only a single, boot-mounted accelerometer. MethodsNineteen patients recovering from an acute Achilles tendon rupture completed in-lab walking trials while wearing an instrumented immobilizing boot. A boot-mounted inertial measurement unit provided acceleration signals used for prediction, while a force-sensing insole provided ground truth tendon-loading data through a validated ankle moment balance. We developed a stance-detection algorithm, as well as a personalized one-dimensional convolutional neural network (1D-CNN) to estimate per-step peak Achilles tendon load. Our training framework incorporated a small patient-specific personalization sample and was evaluated on held-out steps. ResultsThe stance detection algorithm identified stance phases with 99.8% precision and mean timing errors of 27.3 ms for heel strike and 61.9 ms for toe-off. The CNN estimated per-step peak Achilles tendon load with a mean absolute error of 0.14 bodyweights (R2=0.68) across rupture patients. ConclusionContinuous, objective estimation of Achilles tendon loading during early rehabilitation is feasible using a single, boot-mounted accelerometer. Model errors were small (9%) relative to the wide range of tendon loading exhibited during immobilizing boot walking. Our proposed approach enables clinicians to continuously monitor mechanical loading during a previously unobservable rehabilitation period and provides a foundation for personalized rehabilitation guidance after Achilles rupture.

The present study presents a systematic approach for generating data-driven synthetic cerebral aneurysm geometries and evaluating their hemodynamics through computational fluid dynamics. Seven patient-specific aneurysm geometries from the right internal carotid artery were reconstructed from time-of-flight magnetic resonance angiography images and standardized through orientation alignment, followed by non-rigid registration onto a common spherical point cloud as a template. Principal component analysis (PCA) was then applied to the aligned point-cloud data to quantify morphological variability and parameterize shape deformation. The first four principal components captured over 90% of the total variance; however, higher-order components were required to capture the detailed geometrical features of the original geometries. Computational fluid dynamic simulations were performed on the PCA-based synthetic geometries under pulsatile flow conditions to investigate the influence of shape variations on intra-aneurysmal flow patterns, time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI). The first principal component score (PCS1), which was associated with changes in aneurysm height and dome width, had the strongest effects on TAWSS and OSI levels. Lower PCS1 values, which corresponded to taller and more oblique domes, produced slower adjacent flow and elevated OSI, whereas higher PCS1 values increased TAWSS. The second principal component score primarily modulated lateral geometric asymmetry and further influenced OSI distribution for the lower PCS1 values. Collectively, these findings indicate that PCA-based shape parameterization provides a practical approach for generating synthetic aneurysm datasets and systematically assessing how specific morphological features govern hemodynamic behavior. The proposed approach is expected to contribute to the future development of surrogate modeling and data-driven hemodynamic prediction.

Thoracic Endovascular Aortic Repair (TEVAR) is a minimally invasive procedure for the treatment of thoracic aortic pathologies, such as Thoracic Aortic Aneurysm (TAA). Computational simulations can provide valuable insights into TEVAR outcomes and complications prior to surgery, making them a useful tool in the procedural planning. In this work, Fluid-Structure Interaction (FSI) computational simulations are carried out in ten pre-TEVAR patient-specific TAA cases, for which post-TEVAR outcomes are known, to quantify the hemodynamic drag forces acting on the aortic wall. Based on these results, this study proposes a new risk factor R to predict the occurrence of type I and III endoleaks. The patient cohort is divided in a calibration set, used to associate specific R values with three different risk levels, and a validation set, to test the risk factor efficacy. Based on the risk factor values obtained for the calibration set, R[&le;] 0.33 is associated with low risk of endoleak formation, 0.33 < R[&le;] 0.67 with moderate risk, and R > 0.67 with high risk. Once it is applied to the validation set,the risk factor is able to predict the formation of a type Ia endoleak. The risk factor proposed in this work is capable of identifying all the endoleak cases analysed, as well as conditions known to increase the risk of TEVAR complications. This study represents a preliminary attempt to determine whether pre-TEVAR hemodynamics can effectively predict post-TEVAR complications and thereby aid clinicians in the pre-operative planning.

PurposeTo evaluate the hemodynamic impact of restoring a normal sino-tubular junction (STJ) following a novel Hegar dilator-based procedure in patients undergoing root-sparing ascending thoracic aortic aneurysm (ATAA) repair using computational modeling. MethodsWe retrospectively selected an ATAA patient who underwent pre- and postoperative gated computed tomography angiography (CTA). We developed a novel workflow to segment the lumen, thick-walled aorta, and aortic valve from CTA images for subsequent blood flow analysis using computational fluid dynamics (CFD) and fluid-structure interaction (FSI). Morphological and hemodynamic characteristics of the root were quantified and compared against those of a control subject, with no noted ascending aortic dilation. The models sensitivity to graft properties and leaflet material heterogeneity was analyzed. ResultsBoth CFD and FSI results showed that the postoperative geometry reconstructed with a normal STJ profile reintroduces sinus vortices during peak systole, similar to the control subject, but were absent pre-surgery. Accounting for aortic valve leaflets in FSI studies yielded qualitatively similar results to the CFD cases, albeit with locally elevated velocities, time-averaged wall shear stress (TAWSS), and energy dissipation, likely due to the dynamically changing orifice area and differing profiles of the left ventricular outflow tract (LVOT). ConclusionWe demonstrated that the novel Hegar dilator-based STJ reconstruction restores normal blood flow patterns, highlighting the importance of reprofiling the aortic sinuses and STJ. The study also highlights the models sensitivities, particularly the LVOT shape and leaflet morphology and mobility, and may assist planning STJ reconstruction to yield optimal hemodynamics before intervention.