Computationally Efficient Magnetic Resonance Imaging Based Surface Contact Modeling as a Tool to Evaluate Joint Injuries and Outcomes of Surgical Interventions Compared to Finite Element Modeling

摘要: Computational modeling is very useful in biomechanics to simulate normal and pathologic joint function. It also determine the efficacies of various surgical procedures performed treat pathologies their outcomes. Models can be used estimate situ measures such as contact pressure distributions that are difficult acquire through experiments noninvasively. Currently, computational only technique available noninvasively evaluate vivo mechanics [1]. However, most models make use input parameters derived from general sources literature, standards, or are, therefore, limited for patient-specific applications [2]. Joint injuries, whether ligaments articular surface, a significant problem there still need tools effectively injuries associated sequelae [3]. The ability monitor initiation progression instability after injury may aid determining prognosis, leading better treatment algorithms. In order refine develop treatments targeted toward individuals, it important focus on subject-specific models. Several techniques exist mechanics. common include image-based FEM [4–13], rigid body spring modeling/discrete element analysis (RBSM) [14–16], SCM [17–19]. either displacement driven force driven. Generally, model geometries acquired modalities computed tomography (CT) [4–8,14,15,19] MRI [9–11,17,18]. Kinematics determined external (surface markers) internal (biplanar radiography) measures, while tendon forces estimated corresponding musculature electromyography (EMG) cross-sectional area, ground reaction measured using platforms [11,20]. These loads boundary conditions into infer kinetics/kinematics resulting surface and/or volumetric stresses strains. FEM accurate method [11,20,21]. depending complexity problem, process developing mesh laborious obtaining converged solution computationally intensive [22], which limits its clinical applicability. Depending type (for instance, deformable versus rigid), more simplified analyses based relevant assumptions appropriate solutions. This basis RBSM techniques. Using these methods, evaluated efficient manner compared [23], makes them applications. underlying question methods competent provide data sufficiently intended application. The accurately has wide implications, especially complex joints wrist. possible changes result intervention alone. achieved technique, without [24]. not been extensively orthopedic applications. Computational applied lower extremity [4–11,18]. wrist, studies have during functional activities [12,14,16,17] simulated effects some carpal fractures fusions [13,15,19]. Scapholunate (SL) ligament commonly occurring wrist lead SL progressive degenerative [25–28]. Prior work repair appears [29,30]. Hence, we investigated differences radiocarpal obtained wrists, injury, results “gold standard.” We did intend comparisons between normal, injured, postoperative states. Our goal was show outcomes would comparable those similar regardless state demonstrate feasibility applicability technique.