Osteoporotic vertebral compression fracture (OVCF) is a common degenerative disease in the elderly. Biomechanical stimulation plays a key role in regulating bone remodeling and healing. In this study, a solid-liquid two-phase poroelastic finite element model was used to simulate bone remodeling in severely osteoporotic vertebrae under five functional loading modes: standing, flexion, extension, lateral bending, and axial rotation. Changes in tissue differentiation, mean elastic modulus, and interstitial fluid velocity in cortical and cancellous bone were quantitatively analyzed over the 77-day healing period. The results showed that standing and axial rotation significantly increased the elastic modulus of cortical bone and promoted osteogenic maturation, whereas flexion exhibited the weakest osteogenic effect. Cancellous bone regeneration was driven mainly by mesenchymal stem cell diffusion and was less affected by loading patterns. Biophysical stimuli (deviatoric strain and fluid flow) gradually decreased with tissue maturation, and the tissue differentiation follows a typical sequence: fibrous tissue, cartilage, immature bone, mature bone. This study reveals the biomechanical mechanism of bone remodeling under different rehabilitation loads and provides in silico theoretical reference for exploring personalized rehabilitation strategies, and cannot be directly applied as clinical treatment guideline.
Robin Sequence (RS) is a congenital condition in which patients experience dynamic, periodic obstruction or collapse of the upper airway due to an underdeveloped jaw and a posteriorly displaced tongue. Current clinical techniques for evaluating airway obstruction do not provide quantifiable data and fail to account for the dynamic nature of obstruction or collapse. There is no standardized criterion to characterize obstruction or collapse severity. This study presents the first method that extracts airway motion from 4-dimensional computed tomography and performs a patient-specific, moving-mesh computational fluid dynamics (CFD) analysis of RS patients with complete airway collapse or obstruction. To quantify the effects of airway collapse, airflow dynamics are analyzed using both instantaneous metrics (velocity, pressure, and energy dissipation rate) and cycle-averaged metrics (resistive work of breathing). These results are compared between a collapsing airway and its synthetic non-collapsing counterpart. To validate the synthetic non-collapsing case, it is further compared with a patient-specific non-collapsing airway. The results show that, to achieve the same tidal volume, the collapsing case requires significantly greater computed breathing effort (7.55 mJ/cycle) than the synthetic non-collapsing case (3.68 mJ/cycle). The shorter inspiration time due to the collapse leads to a higher inlet velocity, resulting in 1.7 times the maximum velocity during peak inspiration (just prior to collapse) and a 2.7-fold higher pressure drop in the collapsing case compared to the synthetic non-collapsing case. At the onset of collapse, a sharp spike in localized energy dissipation rate is observed due to the abrupt deceleration and dissipation of peak flow velocities. This methodology provides a novel approach to understanding the airflow dynamics of RS patients with airway collapse. It enables quantitative comparison between collapsing and non-collapsing airways, thereby offering the potential to support more informed and objective clinical decision-making.
The risk of falling increases with age and orthostatic hypotension (OH) is a common cardiovascular contributor. Current OH diagnostics rely on intermittent blood pressure measurements, which may not adequately characterise haemodynamic responses during orthostatic stress. We developed a closed-loop cardiovascular lumped-parameter model and fitting pipeline for continuous beat-to-beat blood pressure and heart rate data during a supine-to-stand manoeuvre, enabling model-based evaluation of orthostatic haemodynamic responses in older adults. Our 23-compartment lumped model included baroreflex and cardiopulmonary reflex regulation and was calibrated using Finapres data from older adults (Nijmegen Radboud University PROHEALTH study). Using a stochastic ranking evolutionary strategy, we fitted 31 parameters to averaged cohort data, classifying participants as with or without a history of falls (≥ 1 fall in the previous year). The model reproduced systolic and diastolic blood pressure and heart rate responses at the population level, with normalised root mean squared errors of 10.6% and 9.6% for participants with and without a history of falls, respectively. Four model parameters differed significantly between the two population-average fits: baroreflex reference heart rate, a baroreflex transfer function parameter, transient external muscle pressure during standing, and total blood volume. These results demonstrate that a physiologically structured cardiovascular model can reproduce population-level orthostatic responses in older adults and highlight model-based parameter differences associated with fall history.
The Ross procedure represents a promising alternative to conventional valve replacement techniques in young patients with aortic valve disease. Unlike mechanical or bioprosthetic substitutes, the pulmonary autograft retains living properties allowing growth and remodeling to systemic blood pressures. However, in aortic position, the mechanobiological adaptation processes of the pulmonary tissue can be unpredictable. Long-term failure of the Ross procedure is frequently associated with autograft dilation, inducing valve leakage and possible reoperation. The present work develops an image-based finite element pipeline to predict autograft growth and remodeling and its impact on leaflet closure. Realistic geometries are reconstructed from preoperative sheep MRI scans using automated scripts. Meshed autografts are combined with experimentally determined material properties to simulate the evolution of the pulmonary root under pulsatile systemic pressure conditions. The time-varying autograft diameter is then coupled with leaflet simulations to compute the regurgitant orifice area over time, a quantitative indicator of valve competence. Results demonstrate the ability of the model to reproduce in vivo autograft dilation in sheep, capturing both geometrical and biomechanical aspects. The predicted evolution of leaflet coaptation provides new insights into valve dysfunction after the Ross procedure. This framework has the potential to support surgical decision-making and optimize long-term outcomes by tailoring operative strategies to patient-specific physiology.
In modern days, drug-eluting stent (DES) acts as a kingpin for the treatment of coronary artery disease (CAD) and it has a dramatic reduction rate of in-stent restenosis (ISR) in compare to a bare metal stent (BMS). To replicate the drug release from therapeutic devices and its corresponding transportation in the physiological atmosphere, mathematical and computational simulations have become an effective technique. The present article is developed by a thorough comparative analysis of drug transport mechanisms between half-embedded trapezoidal-shaped and circular-shaped struts and also its optimality in stent-based drug delivery. The geometry of the implanted struts (trapezoidal-shaped and circular-shaped) is modeled in a two-dimensional axi-symmetric environment and the target lesion is considered as a single homogeneous layer with identical diffusivity. Due to the hydrostatic pressure of blood, plasma filtration is allowed through the blood-tissue interface along the transmural direction and the flow of interstitial fluid within the porous arterial wall is governed by the unsteady Navier-Stokes equation and the equation of continuity. While the drug is distributed within the arterial wall, tissue receptors grip the drug molecules, so the present study includes the binding of drug along with free drug. An unsteady convection-diffusion-reaction process demonstrates the transportation of free drug, but only reaction process manifests the transportation of bound drug. The mathematical equations of interstitial fluid flow and the transportation of drug along with pertinent initial and boundary conditions are penciled by using a two-dimensional (2D) cylindrical polar coordinate system. A staggered grid generation technique is also leveraged to discretize all the governing equations and boundary conditions, which are then successfully solved numerically by using Marker-and-Cell (MAC) method. The coefficient of variance (CV), a statistical parameter, is introduced in this present drug delivery system to access the consistency of the drug distribution. The study incorporates several necessary factors, such as drug efficacy, tissue drug content, and therapeutic effectiveness to optimize the choice of strut shape and the overall performance of the stent. To achieve the best possible outcomes, a robust sensitivity analysis of several perturbed parameters is carried out by implementing one-way ANOVA. The results highlight that, for long-term safety and efficacy, trapezoidal-shaped struts may be a good choice in compared to circular ones. Furthermore, the tailored combination of strut shape and drug delivery strategy presented herein offers a significant advancement in designing the next-generation DES.
Digital twins have transformed design and verification workflows in engineering, yet their adoption within medical device development remains limited. Conventional build-and-test approaches restrict design space exploration and often delay identification of mechanically critical risks. This paper presents a case study on the development of a calibrated, design-phase behavioral digital twin for a capsule-based biomedical delivery system used in dentistry, with the annular snap-fit nozzle-to-body interface selected as a representative mechanically sensitive feature. Empirical testing, analytical snap-fit theory and nonlinear Finite Element Analysis (FEA) were integrated to characterize mating force, strain and structural safety during assembly. Strong pre-calibration agreement was observed between the analytical and numerical models and back-calculation of an effective polymer-to-polymer coefficient of friction (μ = 0.12) reduced prediction error relative to empirical measurements to within experimental repeatability, establishing a validated behavioral digital twin. Design optimization employed a Taguchi orthogonal array to efficiently explore strain-constrained geometric variation. Results identified undercut depth, governed by nozzle inner diameter, as the dominant contributor to retention strength. An optimized configuration achieved a 65%-75% increase in mating force relative to the baseline design while remaining within permissible strain limits. Numerical verification predicted peak mating force of 190 N and identified localized stress concentrations in the nozzle neck region, highlighting reinforcement requirements before production tooling. Physical verification and validation of the optimized system confirmed the predicted increase in structural performance. Consistent with the digital twin maturity continuum, the framework is positioned as a design-phase, behavioral digital twin. It operates with offline one-way physical-to-digital data flow during the product realization stage, with automated bidirectional synchronization identified as the next stage of development. These findings demonstrate how digital twins can shift biomedical device development from reactive validation towards predictive, manufacturability-aware design, strengthening patient safety, clinician confidence and regulatory assurance in Class II medical devices.
Osteolytic vertebrae containing central lesions are associated with a high risk of burst fracture, as the presence of such lesions indicates substantial bone destruction. The present study aimed to investigate fracture patterns in a clinically relevant case of a lumbar vertebra with an osteolytic cavity under various loading conditions using a computational modeling approach. Osteolytic damage progression was simulated through a virtual thermal flux approach, while stiffness degradation was represented using a continuum damage mechanics framework. Potential crack locations within the vertebra were defined based on an established clinical classification, and crack propagation was evaluated using the Virtual Crack Closure Technique (VCCT). The results demonstrated that the mechanical competence and fracture patterns of the osteolytic vertebra were strongly dependent on the intensity of osteolytic damage and the applied loading conditions. The earliest onset of instability occurred under lateral bending loading when the average osteolytic damage reached approximately 50%. Under kyphotic loading, vertical cracks propagated around the osteolytic cavity and could significantly compromise vertebral stability when combined with compressive and bending loads associated with daily activities. Such loading conditions may promote the connection of horizontal endplate cracks with vertical cracks, resulting in a burst fracture pattern. Therefore, vertebrae containing osteolytic cavities should be carefully protected against lateral bending loads during the treatment period, and exposure to heavy loading postures should be strictly avoided. Future studies should investigate the sensitivity of vertebral load-carrying capacity to variations in the size, shape, and location of osteolytic lesions.
Hemodynamic metrics provide critical insights into the interplay between flow physics and endothelial cell (EC) function in arterial pathologies. Among these, wall shear stress (WSS) is a central regulator of EC function and a key determinant of vascular disease progression. In this study, we review 35 hemodynamic metrics and assess their association with hypertension and atherosclerosis, aneurysms, and thrombosis. Metrics are categorized by magnitude, direction, energy, stagnation time and flow rate to identify those most relevant to specific pathological conditions. We simulate disturbed flow in a novel microfluidic endothelium-on-chip platform using computational fluid dynamics (CFD) and analyze 16 key hemodynamic metrics. The most comprehensive description of the complex flow environments is provided by shear rosettes, polar plots of WSS magnitude and direction over the cardiac cycle. The anisotropy ratio (AR) metric, derived from the shear rosette, offers a robust characterization of the multidirectional secondary flow but cannot distinguish steady from unidirectional oscillatory flows. The R-Ratio and minimized transverse WSS (TransWSSmin) metrics effectively quantify bidirectional WSS when computed along principal flow directions. In contrast, transWSS and directional OSI (DOSI) are limited in their ability to quantify bidirectional WSS in regions of low mean WSS or stagnation. A unified metric integrating WSS magnitude and flow bidirectionality is currently lacking. Combining AR with magnitude-sensitive metrics, such as TAWSS, TransWSS_min, or |TAWSSSC|, may address these limitations. Together, CFD and microfluidic platforms provide a powerful framework to assess EC responses to disturbed flows and advance understanding of vascular disease progression.
Cannulated screws are often used for internal fixation after a femoral neck fracture to ensure the smooth rehabilitation of patients. Patients frequently have various complications, such as avascular necrosis, during the recovery period. Reasonable rehabilitation training after surgery is necessary for patient rehabilitation. Multiple studies have proved a relationship between bone growth repair and blood vessel growth, and the blood supply system provides various oxygen and nutrients for bone remodeling to promote the smooth progress of bone remodeling. As a new therapeutic method, electrical stimulation has been widely used in osteoporosis, bone nonunion, and other diseases, and has achieved good therapeutic effects. Therefore, the internal fixation model of femoral neck fracture was established in this paper, and the influence of load training on postoperative rehabilitation was discussed. At the same time, the blood supply system was coupled with bone remodeling analysis, and electrical stimulation was added to investigate the change in bone density. The simulation results demonstrate a novel method for simulating bone remodeling during postoperative rehabilitation that incorporates electrical stimulation. In this method, mechanical loading promotes an increase in bone density; the addition of angiogenic factors leads to a diminished increase in bone density, whereas the inclusion of electrical stimulation results in an enhanced increase in bone density.
Thoracic aortic aneurysms often require large-diameter stent grafts; however, conventional designs exhibit poor wall apposition and limited adaptability to complex anatomies. Although auxetic metamaterials with a negative Poisson's ratio show promise for stent applications, the optimal design configuration remains unclear. Therefore, this study aimed to compare the mechanical performance of different auxetic stent designs and identify the most suitable configuration. Quasi-static experimental tests were conducted for validation, alongside finite element (FE) simulations under clinically relevant loading conditions, including parallel compression, radial compression, and radial expansion, to evaluate deployment behavior. Four auxetic designs, including rotating square (RS), re-entrant (RE), peanut (PN), and rotating triangle (RT), were investigated using magnesium alloy specimens. The results show that auxetic geometry significantly affects recoiling, stiffness, and deformation. The RT design demonstrated a more balanced mechanical response under the current evaluation criteria, with substantially lower radial stiffness (6291 N/m), representing an 84%-97% reduction compared to the other designs, and moderate foreshortening (7.10%), lower than RE (13.62%) and PN (9.61%) while comparable to RS (5.49%). Despite exhibiting a relatively higher recoil, these findings suggest its potential for controlled deployment and stable apposition.
Subject‐specific musculoskeletal (MSK) models with individualized anthropometric features are essential for accurate biomechanical analysis, given the considerable anatomical and mechanical variability across individuals. Marker‐based scaling provides a noninvasive, efficient, and cost‐effective strategy for personalizing generic MSK models, yet its reliability and accuracy remain insufficiently validated. This study proposes a hybrid scaling approach (FlexiScale), which combines segment‐wise linear scaling with global nonlinear morphing based on radial basis function (RBF) interpolation. This method enables simultaneous adjustment of relative segment orientations and overall skeletal geometry. To comprehensively evaluate its performance, two simpler baseline models were also constructed, including a uniform linear scaling model and a segmental linear scaling model. A reliability analysis was conducted by comparing knee joint contact forces predicted by the three scaling models with in vivo measurements obtained from an instrumented knee prosthesis under identical gait conditions. Furthermore, an accuracy validation was performed by comparing joint contact forces and muscle forces predicted by each scaling model against those derived from medical image–based subject‐specific models across three daily activities (level walking, stair ascent, and stair descent) in both male and female subjects. Compared to conventional linear methods, FlexiScale consistently produced the most accurate and reliable geometric and biomechanical predictions across tasks and subjects. These findings demonstrate that the proposed hybrid approach can generate geometrically and biomechanically more accurate and robust MSK models than conventional linear scaling methods, even without medical imaging, thereby supporting subject‐specific assessments and large‐scale applications in clinical and research settings.
Bladder outlet obstruction (BOO) is diagnosed through clinical urodynamics, an invasive method with many limitations, including side effects or surgical complications. This study introduces evaluation strategies for BOO recognition based on uroflowmetry test. In this study, a catheter-free male lower urinary tract (LUT) model was developed for hydrodynamics simulation. The pressure and velocity distributions in urethras with different obstruction degrees were analyzed under a fixed vesical pressure, and the effect of obstruction on urine flow under transient vesical pressure input was investigated. Dynamic analysis revealed that the assignments of urethral pressure and velocity were substantially influenced by the extent and location of obstruction. The global maximum pressure and velocity differences between obstructed and healthy urethra models reached 28.8 cm H2O and 2.41 m/s, respectively, at a constant bladder pressure input of 50 cm H2O. Vortices emerged at different segments along the obstruction, resulting in energy loss in the urine stream. Based on uroflowmetry data from 300 subjects, four dimensionless evaluation parameters were designed to distinguish healthy individuals from those with BOO, with p-values of < 0.001, 0.05, 0.001, and 0.02, respectively. The distributions of pressure, velocity, and vortex provide significant guidance for customized BOO surgery. In addition, the means and indicators of dimensionless evaluation have a crucial contribution to identify male BOO by uroflowmetry examination. Trial Registration: This experiment was certified by the Chinese Clinical Trial Registry (ChiCTR2200063467).
In recent years, flexible needles have garnered significant research attention due to their outstanding steerable flexibility. Path planning of flexible needles is key to achieving intelligent navigation. However, existing path-planning methods for flexible needles are often trapped in local optima, failing to identify the globally optimal insertion trajectory. In order to solve this problem, this paper proposes a novel hybrid path planning algorithm by combining particle swarm optimization (PSO) and simulated annealing (SA) mechanism to enhance the global search capabilities. By integrating the probabilistic judgment and the annealing mechanism of SA, the particle diffusion mechanism can be changed and the inertia weight of PSO can be dynamically adjusted, which effectively reduces the risk of premature convergence of the algorithm. Simulations were conducted in a prostate-anatomy-mimicking environment, and the results demonstrated that the proposed algorithm can achieve superior planning outcomes compared to the traditional PSO. To verify the effectiveness of the proposed algorithm, five trials of insertion experiments were performed for each of two targets. For target1, the experimental results showed a mean error of 1.25 mm, a root mean square error of 1.43 mm, and a maximum error of 2.22 mm. For target2, the corresponding errors were 1.21 mm, 1.40 mm, and 2.19 mm, respectively. This level of accuracy met the requirements of general clinical procedures and supports the feasibility and accuracy of the proposed algorithm. This work advanced the clinical applications of the flexible needle and enhanced the development of intelligent navigation systems.
Spinal bone metastases often lead to vertebral fractures and other skeletal events that severely affect patients' quality of life. Predicting structural failure is essential for guiding treatment and preventing complications. However, conventional assessment tools have limited predictive power, highlighting the need for computational methods capable of simulating disease progression and its mechanical consequences. This study aimed to develop a fully automated, patient-specific methodology to predict vertebral structural behavior from computed tomography (CT) data, supporting clinical decision-making and treatment planning. The proposed pipeline integrates three main components: a deep neural network for semantic segmentation of vertebrae and metastatic regions from CT scans, the Coherent Point Drift (CPD) algorithm to ensure consistent alignment and automated definition of boundary conditions across datasets, and the Cartesian Grid Finite Element Method (cgFEM) to simulate the vertebral mechanical response under metastatic involvement. Model performance was evaluated by comparing the predicted outcomes with reference data, using precision, sensitivity, and specificity to assess reliability. The proposed workflow achieved full automation from CT imaging to fracture risk estimation. The segmentation module showed high accuracy across multiple metrics, enabling robust model generation. Geometric normalization and CPD-based boundary condition assignment standardized vertebral geometries across studies, while cgFEM simulations provided clinically interpretable metrics such as safety factors and stability variations associated with tumor size, location, and density. These analyses enabled the identification of scenarios linked to a higher fracture risk. The main limitations include the use of fixed boundary conditions and a predefined voxel threshold, which may reduce physiological realism and generate false positives. Overall, this work presents an end-to-end, patient-specific framework for automated fracture risk evaluation in metastatic vertebrae. By combining deep-learning-based segmentation, geometric normalization, CPD alignment, and cgFEM simulations, the method produces clinically relevant outputs that can guide therapeutic strategies. Future developments will focus on integrating patient-specific loading data and predictive modeling to support incorporation into clinical decision support systems.
Stable internal fracture fixation is essential for femoral neck fractures to achieve better healing and minimise post-operative (PO) complications. Though conventional Ti-alloy used in implant materials provides adequate strength, it induces high strain shielding and also requires secondary removal surgery. In contrast, biodegradable magnesium alloys demonstrate better biocompatibility and are emerging as promising alternatives for implant applications. To evaluate the biomechanical behaviour of femoral neck fractures (Pauwels Types I-III) in a subject-specific femoral model treated with the femoral neck system (FNS) made from Ti-alloy and time-dependent biodegradable Mg alloy. A femoral model was reconstructed from the CT-scan data of a healthy adult male and Pauwels Types I-III fracture patterns were subsequently generated. Finite element simulations were conducted under both normal walking and stair-climbing load conditions. Ti-alloy properties were constant, while Mg-alloy modulus was updated daily over 1 year using an exponential degradation model. Bone remodelling was simulated using a strain energy-based algorithm. Strain shielding at the equilibrium state decreased by as much as 45.55% in the Mg-alloy implant model compared with its immediate PO condition and a similar decrease of around 11.44% was observed in the Ti-alloyed model. The cut-out risk after reaching the equilibrium (AE) condition was reduced by up to 6.74% for the Mg-alloy case compared to the PO scenario. Mg-alloy implants demonstrated greater bone apposition (up to 1.13 g/cm3) compared to the Ti-alloyed implant in AE conditions. Micromotion remained below 150 μm in all models and decreased by approximately 24% after reaching equilibrium. Mg-alloy FNS implants enhance physiological load transfer, reduce shielding and maintain fixation stability during degradation, indicating strong potential as biodegradable alternatives to Ti-alloy implants for femoral neck fracture fixation.
The purpose of this study was to investigate the impact of rotational speed and descending aortic flow on hemodynamics of a modular intra-aortic entrainment pump. A modular intra-aortic entrainment pump was placed in the descending aorta, and the hemodynamics of the intra-aortic entrainment pump were investigated by computational fluid dynamics methods in relation to rotational speed and descending aortic flow. This study shows that the modular intra-aortic entrainment pump can generate more cumulative flow at lower speeds. When cardiac function is limited and the rotational speed is too high, a portion of the blood that has just been pumped is reabsorbed into the blood pump, which may cause the cumulative flow through the pump to be greater than the flow through the descending aorta. There is a strong linear relationship between cumulative flow through the modular intra-aortic entrainment pump and rotational speed, but it is not sensitive to descending aortic flow. It provides a new direction for estimating pump flow rates for this type of device. It was also found that a high rotational speed leads to an increase in turbulent kinetic energy, shear stress volume fraction, and hemolysis index within the flow field near the modular intra-aortic entrainment pump, while a decrease in descending aortic flow results in a significant increase in hemolysis index. This shows that the rotational speed of the modular intra-aortic entrainment pump needs to be adjusted according to the degree of heart failure to avoid secondary blood damage and increased ventricular afterload.
The arterial wall undergoes continual growth and remodeling (G&R) in response to mechanical and biological cues via processes that can also contribute to pathological changes such as aneurysmal dilatation. Computational modeling has proven instrumental in investigating such phenomena. Here, we present a computational framework for arterial G&R based on a constrained mixture theory and applied to simulate aneurysm mechanics in the ascending or descending thoracic aorta. This framework supports curved, multilayered geometries and incorporates diverse tissue constituents, including elastic fibers, fibrillar collagens, smooth muscle cells, and glycosaminoglycans (GAGs). For the descending aorta, we implemented a bilayer configuration and compared the outcomes to prior models and murine data. This multilayered structure confirmed distinct remodeling patterns between the media and adventitia. Inclusion of GAGs, despite their low abundance in healthy tissue, was found to affect the mechanical responses, highlighting yet again their potential role in vascular biomechanics. For the ascending aorta, a parameter study was conducted to assess the impact of vessel curvature and material properties on the G&R process while introducing elastic fiber dysfunction at various locations. Simulations demonstrated that vessel curvature strongly affects both the spatial distribution and extent of remodeling, particularly when mechanical insults localize along the outer curvature. Together, these initial studies further demonstrate the capability and versatility of our modeling platform for investigating region-specific adaptation or disease progression in complex aortic geometries. This framework may support future mechanistic investigations focused on layered vessel structures and constituent-specific dysfunction, contributing to a deeper understanding of aneurysm development and progression.
This study investigates the influence of fiber dispersion representation on the accuracy of the mechanical response of anisotropic hyperelastic material models for healthy and aneurysmal human aortic wall tissue under planar biaxial loading. Five fitting strategies were compared: (i) detailed integration of fiber orientation and dispersion data across the thickness; (ii) a single, thickness-averaged fiber distribution; (iii) two representative layers (media and adventitia); (iv) multiple layers discretized in the radial direction; and (v) a single layer with a symmetrical in-plane distribution of collagen fibers. The goodness of fit was calculated using the coefficient of determination averaged over all experimental tests. The most accurate fits were achieved with strategy (i), with a goodness of fit R avg 2 ≈ 0.96 ± 0.02 $$ {R}_{\mathrm{avg}}^2\approx 0.96\pm 0.02 $$ for the combined cohort of aneurysm patients and the healthy cohort; comparable accuracy was achieved by the two-layer model (iii), R avg 2 ≈ 0.91 ± 0.06 $$ {R}_{\mathrm{avg}}^2\approx 0.91\pm 0.06 $$ , but with significantly less complexity in model implementation. As a secondary objective of this study, regional parameters that correlate with the two-layer model (iii) and are intended for finite element analyses are presented. The method using a symmetrical single layer in model (v) yielded the lowest accuracy, R avg 2 ≈ 0.73 ± 0.14 $$ {R}_{\mathrm{avg}}^2\approx 0.73\pm 0.14 $$ , and highlighted the need to capture non-symmetric fiber families. The modeling of elastin as a separate anisotropic material was also investigated by comparing two different constitutive modeling approaches. While the healthy cohort showed the best fit by including elastin in model (i) ( R avg 2 ≈ 0.99 ± 0.01 $$ {R}_{\mathrm{avg}}^2\approx 0.99\pm 0.01 $$ ), separate treatment of elastin in the combined cohorts resulted in only a slight increase of R avg 2 $$ {R}_{\mathrm{avg}}^2 $$ of ≈ 0.02 $$ \approx 0.02 $$ . This marginal improvement is offset by the risk of overfitting due to additional parameters, which supports the inclusion of elastin in the ground matrix.
Understanding the mechanobiological mechanisms of spinal growth is essential for modeling progressive deformities, particularly adolescent idiopathic scoliosis (AIS). In this study, we present a novel finite element methodology for simulating mechanobiological growth governed by the Hueter-Volkmann law. The approach is developed in the large deformation framework and uses the Hueter-Volkmann law for the first time in a decomposition-based framework in which the growth is incorporated into the constitutive model via multiplicative decomposition of the deformation gradient. For comparison purposes, we also implement the sequential method widely used in the literature. Although both approaches are based on the Hueter-Volkmann law, which relates the normal compressive stress on the growth plate to local growth inhibition, they differ significantly in how this principle is integrated into the finite element framework. Unlike the sequential method, which requires successive growth computation and mechanical solution steps, along with repeated updates of the growth direction, the proposed decomposition-based approach solves stress-induced deformations and growth simultaneously. It is formulated in the Lagrangian configuration, eliminating the need to update the growth direction throughout the simulation. The proposed formulation not only offers superior numerical stability but also exhibits lower computational complexity compared to the sequential method, particularly under large deformations. The method is evaluated using a finite element model of a simplified Functional Spinal Unit (FSU) under symmetric and asymmetric compressive loading over a two-year growth period. While both approaches produce comparable wedge angle progression, the decomposition-based formulation, which more realistically resembles the actual growth process, results in smoother deformations, less element distortion, and substantially reduced computational cost. Additionally, a robust wedge angle calculation technique is introduced using least plane fitting to full endplate nodes of the vertebral bodies, improving geometric accuracy and reducing mesh sensitivity. Together, these features establish a reliable and efficient framework for long-term spinal growth simulations and offer a promising foundation for future patient-specific modeling and clinical applications.
Identification of cerebral aneurysms at risk of destabilization and rupture remains challenging. Although flow stagnation has been recognized as a risk factor, the underlying mechanisms and its predictive power are poorly understood. The purpose was to investigate possible associations between flow stagnation determined from computational fluid dynamics (CFD)-based virtual angiograms and aneurysm instability and rupture. A total of 312 aneurysms at the posterior communicating (PCOM) artery were analyzed with image-based CFD. Virtual angiograms were constructed by simulating contrast injections, and contrast retention metrics were calculated from time density curves of the aneurysm and their parent artery. These metrics were compared between 23 stable and 18 unstable aneurysms from a longitudinal dataset and between 129 unruptured and 142 ruptured aneurysms from a cross-sectional dataset. Aneurysmal contrast retention was significantly larger (p < 0.05) in ruptured compared to unruptured aneurysms as well as when considering only small aneurysms (size < 7 mm). Similar associations were obtained when comparing stable and growing aneurysms. Multivariate analysis showed that aneurysm instability can be forecasted from flow stagnation with good accuracy (AUC = 0.88), while aneurysm rupture with only moderate accuracy (AUC = 0.72) or marginal accuracy for small aneurysms (AUC = 0.66). Mean residence time was identified as a good predictor of aneurysm instability and rupture. Flow stagnation, determined by contrast retention in angiographies (virtual or real), is associated with PCOM aneurysm instability (growth or symptoms development) and can be used to identify aneurysms prone to further growth and potentially rupture. However, aneurysms can also rupture without exhibiting signs of flow stagnation.
