Annals of Biomedical Engineering

Cerebral aneurysms are a serious clinical challenge, with [~]half resulting in death or disability. Treatment via endovascular coiling significantly reduces the chances of rupture, but the technique has failure rates between 25-40%. This presents a pressing need to develop a method for determining optimal coil deployment strategies. Quantification of aneurysm hemodynamics through computational fluid dynamics (CFD) has the potential to significantly improve the understanding of the mechanics of aneurysm coiling and improve treatment outcomes, but accurately representing the coil mass in CFD simulations remains a challenge. We have used the Finite Element Method (FEM) for simulating patient-specific coil deployment based on mechanical properties and coil geometries provided by the device manufacturer for n=4 ICA aneurysms for which 3D printed in vitro models were also generated, coiled, and scanned using ultra-high resolution synchrotron micro-CT. The physical and virtual coil geometries were voxelized onto a binary structured grid and porosity maps were generated for geometric comparison. The average binary accuracy score is 0.836 and the average error in porosity map is 6.3%. We then conduct patient-specific CFD simulations of the aneurysm hemodynamics using virtual coils geometries, micro-CT generated oil geometries, and using the porous medium method to represent the coil mass. Hemodynamic parameters of interest including were calculated for each of the CFD simulations. The average error across hemodynamic parameters of interest is [~]19%, a 58% reduction from the average error of the porous media simulations, demonstrating a marked improvement in the accuracy of CFD simulations using FEM generated coil geometries.

AO_SCPLOWBSTRACTC_SCPLOWThe placenta is a temporary and complex organ critical for fetal development through its subtle but convoluted harmonization of endocrine, vascular, haemodynamic and exchange adaptations. Yet, due to experimental, technological and ethical constraints, this unique organ remains poorly understood. In silico tools are emerging as a powerful means to overcome these challenges and have the potential to actualize novel breakthroughs. Here, we present an interdisciplinary framework combining in vitro experiments used to develop an elegant and scalable in silico model of oxygen diffusion. We then use in utero imaging of placental perfusion and oxygenation in both control and growth-restricted rodent placentas for validation of our in silico model. Our framework revealed the structure-function relationship in the feto-placental vasculature; oxygen diffusion is impaired in growth-restricted placentas, due to the diminished arborization of growth-restricted feto-placental vasculature and the lack of decelerated flow for adequate oxygen diffusion and exchange. We highlight the mechanisms of impairment in a rat model of growth restriction, underpinned by placental vascular impairment. Our framework reports and validates the prediction of blood flow deceleration impairment in growth restricted placentas with the placentas oxygen transfer capability being significantly impaired, both globally and locally.

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.

ObjectivesPatient-specific multiscale modeling simulates virtual surgeries of the Fontan procedure using three different graft options. Predictive modeling details post-operative outcomes that can help inform clinical decision support. MethodsSix patients underwent preoperative cardiac magnetic resonance imaging and catheterization. Virtual surgery is carried out for each patient to test the resulting hemodynamics of three Fontan graft options: ECC, 9mm Y-graft, and 12mm Y-graft. Results1) one-way ANOVA p>0.998 in all systemic pressures and flows between graft options, 2) p=0.706 for hepatic flow distribution between graft options, 3) local power loss differences do not affect the systemic circulation, 4) anastomosis positioning modification of the same Y-graft in the same patient changed left PA hepatic distribution from 0.66 to 0.49 ConclusionsSystemic pressures and blood flow after the Fontan procedure are not affected by graft selection but are well influenced by patient pulmonary vascular impedance. The hepatic distribution can be affected by anastomosis placement. Ultra-mini abstractWe present the first case series of patient-specific multiscale modeling of the Fontan procedure. Despite noticeable local power loss differences, graft selection does not affect systemic pressure and flow rates or other clinically relevant quantities. Anastomosis placement can affect hepatic distribution.

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.

Cardiopulmonary bypass (CPB), though indispensable in cardiac surgery, carries significant risks of systemic embolization and organ injury. While cerebral and cardiac complications have been thoroughly investigated, the impact of emboli on abdominal organs remains largely unexplored. This study integrates computational fluid dynamics (CFD) with Lagrangian particle tracking (LPT) to simulate emboli transport and hemodynamics under clinically relevant CPB conditions in a patient-specific aorta model. A validated OpenFOAM-based framework was used to assess the effects of CPB pump flow rate (3-5 LPM), hemodiluted blood viscosity (1.5-3.5 cP), and embolus size (0.5-2.5 mm) on embolic distribution across major abdominal branches, including the renal, hepatic, splenic, mesenteric, and iliac arteries. Key results showed that lower blood viscosity (1.5 cP) and higher flow rate (5 LPM) significantly affected embolic transport, both individually and combinedly. Under these combined conditions, renal artery emboli transport increased from 17% to 27%, and hepatic artery transport rose from 7.1% to 10.7%. Also, larger emboli (2.5 mm) consistently exhibited greater deviation from central flow and had higher side-branch entry, resulting in increased escape rates of 14% and 26% for renal and hepatic branches, respectively. These tendencies correlated well with clinical observations of post-CPB acute kidney and liver injury. This study presents the first CFD-based quantitative analysis of embolic transport to abdominal organs, revealing critical emboli pathways previously overlooked in both clinical and computational studies. The findings highlight the need for optimized CPB perfusion strategies to minimize embolic burden and enhance intraoperative protection of abdominal organs during cardiac surgery.

Uterine rupture is an intrinsically biomechanical process associated with high maternal and fetal mortality. A previous Cesarean section (C-section) is the main risk factor for uterine rupture in a subsequent pregnancy due to tissue failure at the scar region. Finite element modeling of the uterus and scar tissue presents a promising method to further understand and predict uterine ruptures. Using patient dimensions of an at-term uterus, a C-section scar was modeled with an applied intrauterine pressure to study how scars affect uterine stress. The scar positioning and uterine thickness were varied, and a defect was incorporated into the scar region. The modeled stress distributions confirmed clinical observations as the increased regions of stress due to scar positioning, thinning of the uterine walls, and the presence of a defect are consistent with clinical observations of features that increase the risk of uterine 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.

Identification and treatment of pregnancies at risk for preterm birth is a central challenge in obstetric research. Many of the known causes of preterm birth originate from mechanical failure in reproductive tissues. To better understand the biomechanical environment of the gravid uterus and its potential contribution to preterm birth, this computational study presents a parametric method for modeling maternal reproductive anatomy during the early second trimester. A finite element modeling approach was built using existing sonographic measurements from early second-trimester maternal anatomy and material properties from published mechanical tests. We applied the same physiologically relevant intrauterine pressure to all models and quantified the resulting tissue stretch. The sensitivity of the stretch in the proximal cervix was explored by varying material properties and sonographic maternal anatomy dimensions. Cervical material properties, particularly the fiber stiffness modulus and ground substance Youngs modulus, were found to have the greatest effect on proximal cervix stretch compared to other material properties and sonographic dimensions. Among the sonographic dimension measurements, those defining the region surrounding the proximal cervix had the greatest effect on proximal cervix stretch, including the curvature of the posterior uterine wall and the thickness of the lower uterine segment. The computational modeling approach presented here enables future patient-specific studies of gravid reproductive tissues to elucidate differences between individuals who do and do not deliver preterm. Additionally, this study is foundational for building digital twins to support future virtual clinical studies on diagnostic and therapeutic device design to prevent preterm birth.

Hypertensive pregnancy disorders, such as preeclampsia, are leading sources of both maternal and fetal morbidity in pregnancy. Non-invasive imaging, such as ultrasound and magnetic resonance imaging (MRI), is an important tool in predicting and monitoring these high risk pregnancies. While imaging can measure hemodynamic parameters, such as uterine artery pulsatility and resistivity indices, the interpretation of such metrics for disease assessment rely on ad-hoc standards, which provide limited insight to the physical mechanisms underlying the emergence of hypertensive pregnancy disorders. To provide meaningful interpretation of measured hemodynamic data in patients, advances in computational fluid dynamics can be brought to bear. In this work, we develop a patient-specific computational framework that combines Bayesian inference with a reduced-order fluid dynamics model to infer remodeling parameters, such as vascular resistance, compliance and vessel cross-sectional area, known to be related to the development of hypertension. The proposed framework enables the prediction of hemodynamic quantities of interest, such as pressure and velocity, directly from sparse and noisy MRI measurements. We illustrate the effectiveness of this approach in two systemic arterial network geometries: an aorta with carotid and a maternal pelvic arterial network. For both cases, the model can reconstruct the provided measurements and infer parameters of interest. In the case of the maternal pelvic arteries, the model can make a distinction between the pregnancies destined to develop hypertension and those that remain normotensive, expressed through the value range of the predicted absolute pressure.

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.

Type-B Aortic Dissection is a cardiovascular disease in which a tear develops in the intimal layer of the descending aorta, allowing pressurized blood to delaminate the layers of the vessel wall. In medically managed patients, long-term aneurysmal dilatation of the false lumen (FL) is considered virtually inevitable and is associated with poorer disease outcomes. While the pathophysiological mechanisms driving FL dilatation are not yet understood, hemodynamic factors are believed to play a key role. Computational Fluid Dynamics (CFD) and 4D-Flow MRI (4DMR) analyses have revealed correlations between flow helicity, oscillatory wall shear stress, and aneurysmal dilatation of the FL. In this study, we compare CFD simulations using a patient-specific, three-dimensional, three-component inlet velocity profile (3D IVP) extracted from 4DMR data against simulations with flow rate-matched uniform and axial velocity profiles that remain widely used in the absence of 4DMR. We also evaluate the influence of measurement errors in 4DMR data by scaling the 3D IVP to the degree of imaging error detected in prior studies. We observe that oscillatory shear and helicity are highly sensitive to inlet velocity distribution and flow volume throughout the FL and conclude that the choice of IVP may greatly affect the future clinical value of simulations.

PurposeMost computational fluid dynamics (CFD) studies on arteriovenous grafts (AVGs) adopt idealised geometries and simplified boundary conditions (BCs), potentially resulting in misleading conclusions when attempting to predict neointimal hyperplasia (NIH) development. Moreover, they often analyse a limited range of hemodynamic indices, lack validation, and fail to link the graft-altered hemodynamics with follow-up data. This study develops a novel patient-specific CFD workflow for AVGs using pathophysiological BCs. It validates the CFD results with patient medical data and assesses the co-localisation between CFD results and NIH regions at follow-up. MethodsContrast-enhanced computed tomography angiography images were used to segment the patients AVG geometry. A uniform Doppler ultrasound (DUS)-derived velocity profile was imposed at the inlet, and three-element Windkessel models were applied at the arterial outlets of the domain. Transient, rigid-wall simulations were performed using the k-{omega} SST turbulence model. The CFD-derived flow waveform was compared with the patients DUS image to ensure validation. Turbulent kinetic energy (TKE), helicity and near-wall hemodynamic descriptors were calculated and linked with regions presenting NIH from a 4-month follow-up fistulogram. ResultsIn the analysed patient, areas presenting high TKE and balanced helical flow structures at baseline exhibit NIH growth at follow-up. Transverse wall shear stress index is a stronger predictor of NIH than other commonly analysed near-wall hemodynamic indices, since luminal areas subjected to high values greatly co-localise with observed areas of remodelling. ConclusionThis patient-specific computational workflow for AVGs could be applied to a larger cohort to unravel the link between altered hemodynamics and NIH progression in vascular access.

ObjectiveTo implement and validate a 3D volume imaging sequence and 3D strain estimation procedure for enhanced biaxial mechanical testing of excised ventricular myocardium. MethodsOne right- and one left-ventricular excised porcine myocardium specimens were tested using dual-loading protocol quasi-static biaxial mechanical testing. During biaxial testing, volume ultrasound images were acquired using a row-column addressed array probe using a synthetic aperture imaging sequence. Volume ultrasound images were used to compute tissue deformation using 3D correlation-based ultrasound speckle tracking. Ultrasound-derived tissue strains were validated against repeated measurements using typical standard optical camera imaging of the surface deformation of the specimen. ResultsSynthetic aperture imaging with the RCA yielded artifact-free and uniform ultrasound speckle for high-fidely speckle tracking of tissue deformation. Ultrasound-derived tissue strain is in good agreement with ground-truth camera-derived surface strain measurements (root-mean-square error is 1.6% strain). ConclusionHigh-fidelity 3D strain measurement with ultrasound imaging is accurate and can enhance biomechanical insights from biaxial experimentation, especially in large tissues such as porcine and human myocardium where assumptions of plane stress and incompressibility may not apply.

Stent-artery interactions are influenced by the mechanical properties of self-expanding Nitinol stents, but data on these characteristics remain limited. Eleven stents (Absolute Pro, S.M.A.R.T. Control, Misago, Zilver, Complete SE, EverFlex, Innova, Pulsar-18, LifeStent, S.M.A.R.T. Flex, and Supera) used to treat peripheral arterial disease (PAD) were subjected to axial tension, compression, three-point bending, and torsion tests, and the data on reaction forces and moments were compared with finite element simulations of the same experiments. Inverse computational analysis was used to determine austenite and martensite elasticity, transformation stretch, stresses at the start and end of transformation loading, and the start of transformation stress in compression. Uniaxial tensile tests were done on isolated struts from Absolute Pro and Zilver stents to verify the results of the inverse analysis. Our study demonstrate that Nitinol material properties are significantly different across devices. Austenite elasticity ranged 7.5-85 GPa, martensite elasticity 10-47.8 GPa, transformation stretch 1.03-1.08, the start of transformation loading stress 386-465 MPa, the end of transformation loading stress 411-535 MPa, and the start of transformation stress in compression 150-900 MPa. Nitinol of S.M.A.R.T. Control and S.M.A.R.T. Flex devices had the softest response, while Pulsar-18 had the hardest. The presented Nitinol mechanical properties of commonly used PAD stents can improve the fidelity of computational models investigating stent-artery interactions and may help improve clinical outcomes of endovascular PAD repairs through better device design.

Angiogenesis drives the formation and remodeling of capillary networks throughout tissue repair, regulating the vascular environment that supports healing and tissue remodeling. Experimental characterization of these processes is commonly performed using CD31-stained histological tissue sections to quantify capillary surface density and morphology throughout healing. However, these measurements provide only two-dimensional characterization of an underlying three-dimensional (3D) vascular network, limiting direct estimation of volumetric capillary density and vascular architecture. To address this limitation, an experimentally informed framework was developed to generate representative 3D capillary networks, enabling estimation of volumetric capillary density from histologically quantified vascular measurements. CD31-stained histological sections obtained from a longitudinal porcine lumpectomy study were analyzed to quantify the percentage of CD31-positive area (%CD31+) and capillary morphology within healthy tissue and healing surgical cavities. Histologically quantified morphology distributions and literature-informed vascular branching characteristics were incorporated into a capillary network generation framework to construct representative 3D vascular networks. Capillary branches were iteratively generated within representative tissue volumes until virtual histological sections reproduced experimental %CD31+ measurements, enabling estimation of volumetric capillary density. Generated capillary networks demonstrated good agreement with experimentally characterized 3D vascular architecture, while simulated histological sections accurately reproduced experimentally quantified capillary counts and vascularization measurements. Application of the framework to the porcine lumpectomy dataset captured temporal changes in vascular remodeling throughout healing, revealing progressive increases in volumetric capillary density and vascular maturation. Collectively, this framework provides an experimentally informed methodology for relating histological vascular measurements to volumetric capillary density estimates, supporting future computational studies of angiogenesis and tissue repair.

PurposeComputational models of the uterus during pregnancy enable analysis of electro-chemo-mechanical pathways to predict labor timing and guide treatment planning. We aim to develop a robust image-based modeling pipeline to investigate uterine passive mechanics during late pregnancy. MethodsA parametric model of the uterus and cervix was created using a patients MRI measurements at 38 weeks of gestation. Inspired by advances in cardiac mechanics models, we created Laplace-Dirichlet solutions to inform tissue domains, fiber structure within the uterus and cervix, and spatially varying Robin boundary conditions. Prior imaging and mechanical testing data were used to fit material parameters. Boundary condition parameters were tuned to match the displacements of a previously established approach that employed contact with surrounding tissue. The tissue mechanical response to a physiologic load was assessed across varying material properties and fiber architectures. ResultsDiscrepancies in nodal displacements between the current approach and the contact-based model were limited to 3.4 {+/-} 1.8 mm, yielding nearly 90 % computational savings. Uterine tensile strains were more sensitive to ground substance elastic modulus (E) compared to fiber properties. Reduced E and fiber stiffness increased cervical strains and compression. Fiber dispersion and architecture modulated the opening of the cervical internal ostium but had a reduced impact on compression. ConclusionWe developed a novel workflow for modeling passive uterine mechanics, informed by patient-specific measurements and in vitro mechanical tests. The robust workflow may prove useful for studying labor progression and conducting longitudinal studies to enhance our understanding of normal and pathological pregnancies.

The miniaturization of implantable mechatronic systems is fundamentally limited by a pervasive design conflict: within a rigid spatial envelope, the requirements for high electromagnetic power density, physiological fluid pathways, and perfect biocompatibility compete irreconcilably. To resolve this, we propose a paradigm shift--the Electromagnetic Core-First (ECF) co-design framework. Unlike traditional sequential approaches that force performance compromise, ECF establishes a maximized electromagnetic core (via NSGA-III optimization under manufacturing constraints) as the immutable foundation. Fluid and thermal structures are then co-optimized in parallel within this fixed boundary, achieving global system synergy. Demonstrating its efficacy, we realized a fully magnetically levitated Fontan blood pump (O38.2 mm). The ECF-designed prototype, featuring a novel nested magnet topology, achieves: (1) 57.4% higher air-gap flux density vs. baseline designs and an 18.4 N static suspension force at only 4 W; (2) physiological flow matching (8.8 mmHg at 3.2 L/min); and (3) exceptional biocompatibility, with a hemolysis index of 0.0061 g/100 L and surface temperature rise <1.9{degrees}C. This work transcends the presentation of a single device; it establishes a systematic, physics-driven design paradigm that transforms extreme miniaturization from a constraint into a catalyst for performance, applicable to next-generation implantable mechatronic systems.

PurposeBlood pressure gradient ({Delta}P) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of{Delta} P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. MethodsMedical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N=17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations.{Delta} P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. ResultsThe 0D simulations were extremely efficient ([~]15 secs computation time) compared to 3D simulations ([~]30 hrs computation time on a cluster). However, the 0D{Delta} P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 {+/-} 9.9 mmHg vs 5.3 {+/-} 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as{Delta} P[&ge;] 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. ConclusionOverall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

PurposeThis study aimed to develop and validate a magnetic resonance imaging (MRI)-based biofidelic head-neck finite element (FE) model comprised of scalp, skull, CSF, brain, dura mater, pia mater, cervical vertebrae, and discs, 14 ligaments, and 42 neck muscles. MethodsWe developed this model using head and neck MRI images of a healthy male participant and by implementing a novel meshing algorithm to create finer hexahedral mesh structures of the brain. The model was validated by replicating four experimental studies: NBDLs high acceleration profile, Itos frontal impact cervical vertebrae study, Alshareefs brain sonomicrometry study, and Nahums impact study. ResultsThe results showed reasonable geometrical fidelity. Our simulated brain displacement and cervical disc strain results were close to their experimental counterparts. The intracranial pressure and brain stress data of our head-only model (excluding neck structures and constraining the base of the skull) were similar to Nahums reported results. As neck structures were not considered in Nahums study, the FE results of our head-neck model showed slight discrepancies. Notably, the addition of neck structures (head-neck model) reduced brain stress values and uncovered the brains intracranial pressure dynamics, which the head-only model failed to capture. Nevertheless, the FE simulation results showed a good agreement (r > 0.97) between the kinematic responses of the head-neck model and NBDLs experimental results. ConclusionThe developed head-neck model can accurately replicate the experimental results and has the potential to be used as an efficient computational tool for brain and head injury biomechanics research. Statements and DeclarationsThis work was primarily supported by the U.S. Department of Homeland Security (70RSAT21CB0000023). The MRI data acquisition was supported by the Texas Tech Neuroimaging Center.