ABSTRACT Triply periodic minimal surface (TPMS) scaffolds possess significant application potential in bone tissue engineering owing to their smooth and continuous surface morphology and highly interconnected pore networks. However, in conventional parametric modeling of TPMS scaffolds, porosity and pore size usually vary in a coupled manner, restricting the systematic evaluation of scaffold structure–function relationships. In this study, a decoupled single‐variable design strategy was adopted to construct homogeneous sheet‐based TPMS scaffolds, including diamond sheet (DS), gyroid sheet (GS), and primitive sheet (PS) topologies, with independently controlled porosities (50%–90%) and pore sizes (500–900 μm). A sequential multiphysics framework integrating static compression finite element analysis (FEA), computational fluid dynamics (CFD), the discrete phase model (DPM), and mechano‐regulation analysis was established to evaluate osteogenic potential during the early post‐implantation hematoma stage. Results demonstrated that porosity primarily governed apparent stiffness, while permeability was highly sensitive to topological changes and pore size enlargement. The initial capture efficiency of mesenchymal stem cells (MSCs) was closely associated with the specific surface area (SSA) and dynamically regulated by flow trajectories and wall accessibility. Furthermore, mechano‐regulation stimulus factor analysis, combining wall shear stress (WSS) and octahedral shear strain (OSS), revealed that WSS contributed dominantly to the local osteogenic microenvironment. Osteogenic differentiation efficiency was not maximized by any single structural parameter, but rather emerged from an optimal balance between the capacity to capture MSCs and adequate mechanical stimulation. These findings validate a “capture‐then‐differentiate” mechanism for early osteogenesis in sheet‐based TPMS scaffolds, providing a quantitative multiphysics strategy for the topological optimization of bone scaffolds.
ABSTRACT Varus deformity is a pathological knee condition described by outward bowing of the joint and increased medial compartment loading, both of which contribute to the development and progression of knee osteoarthritis. This study presents a subject‐specific musculoskeletal modelling framework to investigate ligamentous characteristics and tibiofemoral contact mechanics for subjects having a varus deformity. A cohort of osteoarthritic subjects with varus deformity and undergoing total knee replacement surgery was analyzed in a standing posture. For each subject, musculoskeletal models with subject‐specific knee joint anatomy were developed. A Taguchi‐based experimental design was implemented to quantify the influence of individual ligament group slack lengths on the varus alignment. Subsequently, subject‐specific ligament slack lengths combinations were predicted using a search‐based optimisation that minimises the muscle‐volume‐weighted sum of squared muscle activations. The MCL‐G and LCL‐G groups were identified as the dominant influencers of varus angles. Optimisation revealed that specific varus alignments were associated with distinct laxity of medial and lateral soft tissue. These ligamentous adjustments corresponded to a significant medial shift in the tibiofemoral contact centre relative to a neutral alignment. Furthermore, higher degrees of varus malalignment correlated with a substantial increase in the mean total knee joint reaction force and a concurrent increase in the knee adduction moment. The proposed framework provides a subject‐specific in silico approach for quantifying ligament adaptations and contact forces associated with varus deformity.
ABSTRACT The 70%–90% mortality rate of ruptured abdominal aortic aneurysms (AAAs) demonstrates the necessity of investigating progression and rupture. The progression and rupture risks of AAAs are influenced by the physiological states of patients, such as exercise and intense emotions. Understanding this association aids in the management of AAAs, but related research remains limited. This study aims to explore the impact of physiological states on progression and rupture risks of AAAs. Different physiological states of a selected AAA patient (characterized by heart rate (HR), stroke volume (SV), blood pressure (BP), pulse pressure (PP), and the rest and exercise conditions) were simulated by altering the inflow and outflow conditions in computational fluid dynamics and in vitro experiments, and hemodynamics were obtained and analyzed. When HR ≥ 105 bpm, systolic pressure of AAA exceeded 140 mmHg (hypertension). SV ≤ 17 mL induced low time‐averaged wall shear stress (TAWSS) (< 0.4 Pa) and high oscillatory shear index (OSI) (> 0.25); SV ≥ 26 mL induced systolic pressure ≥ 155 mmHg. Increasing BP from 100/60 to 140/100 mmHg and PP from 20 to 60 mmHg, raised the pressure on AAA vascular wall by 53.42% and 15.09%, respectively. Exercise induced higher TAWSS than rest (2.103 vs. 0.644 Pa). These findings rely on a patient‐specific model to preliminarily explore the mechanisms and trends of physiological states affecting AAA progression and rupture risks. Large sample studies are needed in the future to validate the conclusions of this study and establish clinical reference risk thresholds.
ABSTRACT Prosthetic foot design remains relatively rudimentary, as high‐strength materials such as metals and carbon‐fiber composites limit fabrication methods and design freedom. Conventional approaches rely on size optimization of simple geometries, which do not fully capture anatomical boundaries or natural force transmission through the foot. Here, we adopt an initial design domain derived from the side profile of an actual human leg, providing a more anatomically consistent and patient‐specific basis for topology optimization. We present a fully automated, open‐source framework for prosthetic foot design that incorporates ISO 10328 boundary conditions to ensure reliability. Topology optimization is used to determine the optimal material distribution, followed by geometry smoothing for 3D printing. A key outcome is a universal design curve obtained through nondimensionalization: , linking material stiffness, foot size, and patient weight. This enables direct design selection without rerunning optimization for each patient, cutting out design time and cost. Overall, the framework provides a fast, scalable approach to personalized prosthetic design.
ABSTRACT We present a computational modeling framework coupling a poroelastic left ventricle (LV) with lumped‐parameter descriptions of the coronary and systemic circulations in a closed‐loop system. The finite element method, with P1‐P1‐P0 discretization of the displacement, Darcy flow and pore‐pressure fields, is used to solve the boundary value problem associated with the poroelastic formulation. We show that simulation of the isolated non‐contractile poroelastic LV can reproduce perfusion‐induced stiffening features found in measurements of pressure‐volume relationships with less than 1 mmHg error. Simulations coupling the poroelastic LV with systemic and coronary circulatory models also show that the framework can produce phasic changes in coronary flow rate and myocardial wall volume that agree with the experiments. Using the framework, we investigate the effects of coronary sinus (CS) resistance on myocardial perfusion. We show that increasing CS resistance attenuates coronary flow rate, increases myocardial pore pressure, and promotes myocardial swelling.
