Establishment and validation of a high-fidelity finite element model of the wrist joint

Abstract

BACKGROUND: Current finite element models of the wrist joint predominantly focus on osseous and ligamentous structures, with insufficient incorporation of musculotendinous components, thereby limiting their fidelity and accuracy. OBJECTIVE: To establish a high-fidelity finite element model of the wrist joint, providing a reference for in-depth biomechanical investigations. METHODS: Upper limb CT and MRI data from a 33-year-old healthy male volunteer were imported into Mimics 20.0. Threshold-based selection, region growing, and image segmentation techniques were employed to reconstruct wrist-related bones and soft tissues (including muscles). The model underwent surface optimization, patch generation, and meshing in SolidWorks 2020 and HyperMesh 14.0. Material property assignment and ligament-cartilage contact interfaces were implemented in ABAQUS 6.13 to construct a three-dimensional finite element model of the wrist joint. Stress distribution across wrist structures under axial compression was analyzed. RESULTS AND CONCLUSION: (1) A three-dimensional finite element model encompassing the ulna, radius, distal humerus, carpal bones, metacarpals, pronator teres, pronator quadratus, supinator, lateral muscle group, volar muscle group, dorsal muscle group, interosseous membrane, major ligaments, and cartilage structures was successfully established, comprising 759 191 elements and 245 510 nodes. The stress distribution pattern at the radiocarpal joint under axial compression was obtained and compared with cadaveric studies from the literature, validating the model's authenticity and effectiveness. (2) In summary, based on human CT and MRI imaging data, a more complete wrist joint bone and soft tissue structure was reconstructed through computer software simulation, establishing the origin and insertion points of forearm muscles and their contact with bones during muscle course, resulting in a more realistic finite element model of the wrist joint.

1. Introduction

Finite element analysis (FEA) can discretize complex human tissues into simple, finite elements connected at nodes, replacing the original tissue for biomechanical studies. In FEA models, forces are transmitted between elements through nodes, and by setting mechanical loading conditions, individual elements can be analyzed, yielding results that are difficult to obtain from physical experiments [1]. FEA offers advantages such as non-invasiveness, ease of operation, repeatability, controllable experimental conditions, and reliable data, leading to its rapid development in orthopedic research [2].

For instance, PURUSHOTHAMAN et al. [3] used FEA to evaluate the effects of four different artificial cervical disc designs on range of motion, disc pressure, and facet joint loading under various motion conditions, providing insights for implant selection in cervical disc replacement. Other researchers have developed time-dependent bone finite element models based on bone remodeling algorithms [4] to simulate changes in bone density and morphology under long-term loading, predicting adaptive changes around implants and assessing their long-term stability. SPANSWICK et al. [5] utilized high-resolution peripheral quantitative CT to collect wrist data from patients with stable distal radius fractures and established finite element models to compare stiffness between affected and healthy sides, accurately predicting fracture healing time. FEA has played a significant role in orthopedic implant and prosthesis design, bone and joint stress analysis, surgical planning, and fracture risk prediction [6-10].

Early finite element models of the wrist joint were primarily used for stress analysis of skeletal traumatic diseases, often being two-dimensional and structurally simple, such as models of distal radius fractures including only the radius, ulna, scaphoid, and lunate [11]. With advances in medical imaging and computer graphics, the modeling and analysis capabilities of FEA have undergone qualitative changes, and wrist joint finite element models have become increasingly realistic. However, previous wrist joint FEA studies often used only CT data, resulting in models that were either isolated bony structures or lacked surrounding soft tissues such as tendons, muscles, cartilage, and ligaments.