An, Kai‐Nan

Abstract Background/Purpose Diagnosing wrist ligament injuries is challenging; early detection and treatment are important to prevent osteoarthritis progression. Interosseous proximity maps, a proxy measure for joint space, can be generated from volumetric imaging data and may provide important information about wrist health. Artificial intelligence (AI) could enhance accuracy of noninvasive diagnosis based on imaging-derived metrics. This work demonstrates feasibility of AI training using synthetic proximity map data generated from finite element models (FEMs). Methods Personalized wrist FEMs for two asymptomatic participants were created from four-dimensional computed tomography-derived anatomic and kinematic data. Monte Carlo sampling varied 22 ligament material properties and simulated 7,500 unique injury scenarios generating 9,000,000 labeled red, green, and blue (RGB) images of interosseous proximity vector fields from FEM-derived motions. Images were associated with 17 descriptive metrics, including gross wrist angles and bone surface pairs, and used to develop mixed-input convolutional neural networks (CNNs). Model performance was evaluated for identifying specific ligament injuries. Results Average area under receiver operating characteristic curve (AUROC) for CNNs was 0.757 across all injury types and kinematics. In a subset with clinically-relevant functional angles, the average AUROC was 0.824. Best-performing individual ligament AUROCs ranged from 0.807 to 0.999. Sensitivities and specificities exceeded 0.99 for some ligament injury simulations under specific wrist angles and bone surface pairs. Conclusion This study demonstrates the feasibility of using synthetic data from FEMs to train AI models for classifying wrist ligament injuries. Proximity-based RGB images may be a relevant biomarker of ligamentous injury.

Abstract Background Computational modeling is a tool being deployed for orthopaedic solutions but its use in the hand and wrist remains limited. This work used a model to simulate a clinically relevant provocative scaphoid shift maneuver (SSM) with different levels of scapholunate interosseous ligament (SLIL) injuries to observe the effect on different metrics. Methods A personalized model simulated the full SSM motion cycle from ulnar deviation with extension to radial deviation with flexion informed by the participant’s motion obtained from dynamic computed tomography. Models repeated the SSM under different levels of SLIL injury and reported changes in joint kinematics, contact mechanics, and ligament forces. Results The fully injured model increased scaphoid dorsal translation, flexion, and radial deviation compared to the intact condition and caused a subluxation of the scaphoid. Radioscaphoid contact areas were approximately 200% greater in the fully injured model compared with all others and the fully injured model was the only condition where contact force decreased across the motion cycle. Ligament forces in the intact condition were on average 33.0 N and 54.2 N for the volar and dorsal SLIL, respectively. Lastly, the long radiolunate, an extrinsic stabilizer, had forces that increased following SLIL injury. Conclusions Computational models can successfully recreate clinically observed behaviors of an SSM, including scaphoid subluxation, while providing new insights via quantification of contact mechanics and ligament forces. Contact mechanics metrics may be important for understanding the long-term progression of untreated SLIL injuries to osteoarthritis. Additionally, ligament force metrics may explain the progression of SLIL injuries from volar SLIL to dorsal SLIL and highlight the importance of repairing extrinsic stabilizers of the joint, due to increased force sharing following SLIL injury. This work provides a pathway to future studies investigating the effects of SLIL injury and repair, both acutely and chronically.

ABSTRACT Calcific tendinopathy is a common musculoskeletal disorder marked by calcium deposition within tendons, often accompanied by pain, impaired mobility, and in severe cases, ossification. However, the mechanisms underlying tendon mineralization remain poorly understood. In contrast to pathological human calcification, turkeys naturally develop tendon mineralization during growth without signs of inflammation or ossification. This study had two phases: an observational phase to assess onset and progression of calcification, and an interventional phase to evaluate the role of mechanical loading. In the observational phase, flexor tendons were collected from turkeys aged 1–16 weeks in a serial sacrifice study and analyzed by Von Kossa staining and biomechanical testing. Calcification began at 7 weeks, localized within organized collagen matrices, progressed through Weeks 8–14, and peaked by 16 weeks. In the interventional phase, nine female turkeys were randomized at 4 weeks into a transection group ( n = 3), sham group ( n = 3), and control group ( n = 3). Transection at the muscle–tendon junction eliminated mechanical loading. At 16 weeks, tendons were analyzed by histology, quantitative RT‐PCR, ICP‐MS, and biomechanical testing. Transected tendons showed a near‐complete absence of mineralization, reduced expression of osteogenic markers (osteopontin, osteocalcin, Runx‐2), and significantly lower calcium, magnesium, and phosphorus levels. Biomechanical testing indicated reduced stress relaxation, stiffness, and Young's modulus in the transected group. Tendon calcification in turkeys functioned as a mechanically regulated, nonpathological process. The study established a relevant model for early tendon mineralization and offered a basis for developing load‐dependent therapies for human tendon disease.

The hierarchical organization of the connective tissue, more specifically, the musculoskeletal soft tissue, has been extensively studied. With advancements in experimental methodology, investigation of the structure–function relationship has provided more insight into how the mechanical integrity of the tissue is created. Such information is essential in the linking the macroscopic loading environment of the tissue to the microscopic level of the tissue to be experienced by the cell. The flexibility and elastic modulus of gross connective tissue, the fascicle, the fiber and then the collagen molecule are compared based on the data available in the literature.

AbstractThis study aimed to compare the clinically established autologous extrasynovial tendon graft to a newly developed tissue‐engineered allograft (Eng‐allograft) in terms of functional outcomes following flexor tendon reconstruction in a canine model. The second and fifth flexor digitorum profundus (FDP) tendons from 16 dogs were transected and repaired in Zone II. After 6 weeks of cage activity, the repaired tendons were intentionally ruptured, creating a clinically relevant model for reconstruction. The re‐ruptured FDP tendons were then reconstructed using either the clinically standard autologous extrasynovial tendon graft or the Eng‐allograft, which had been revitalized with autologous bone marrow‐derived mesenchymal stem cells (BMSCs) and synovialized using carbodiimide derivatized synovial fluid (cd‐SYN). Following 12 weeks of postoperative rehabilitation, the functional outcomes of the surgical digits were evaluated. The Eng‐allograft group exhibited improved digital function, including lower digit work of flexion and reduced adhesion status, while maintaining similar tendon gliding resistance compared to the autograft group. However, the failure load of both the distal and proximal host/graft conjunctions in the Eng‐allograft group was significantly lower than that of the autograft group with higher graft rupture at the host−graft junction. In conclusion, the decellularized allogenic intrasynovial tendon, when revitalized BMSCs and synovialized with cd‐SYN, demonstrates positive effects on digital function improvement and adhesion reduction. However, the healing at both proximal and distal graft/host junctions is far lower than the autograft. Further research is needed to enhance the healing capacity of allograft conjunctions, aiming to achieve a comparable level of healing seen with autografts.

AbstractPurposeAbnormal adherence at functional myofascial interfaces is hypothesized as an important phenomenon in myofascial pain syndrome. This study aimed to investigate the feasibility of MR elastography (MRE)–based slip interface imaging (SII) to visualize and assess myofascial mobility in healthy volunteers.MethodsSII was used to assess local shear strain at functional myofascial interfaces in the flexor digitorum profundus (FDP) and thighs. In the FDP, MRE was performed at 90 Hz vibration to each index, middle, ring, and little finger. Two thigh MRE scans were performed at 40 Hz with knees flexed and extended. The normalized octahedral shear strain (NOSS) maps were calculated to visualize myofascial slip interfaces. The entropy of the probability distribution of the gradient NOSS was computed for the two knee positions at the intermuscular interface between vastus lateralis and vastus intermedius, around rectus femoris, and between vastus intermedius and vastus medialis.ResultsNOSS map depicted distinct functional slip interfaces in the FDP for each finger. Compared to knee flexion, clearer slip interfaces and larger gradient NOSS entropy at the vastus lateralis–vastus intermedius interface were observed during knee extension, where the quadriceps are not passively stretched. This suggests the optimal position for using SII to visualize myofascial slip interface in skeletal muscles is when muscles are not subjected to any additional force.ConclusionThe study demonstrated that MRE‐based SII can visualize and assess myofascial interface mobility in extremities. The results provide a foundation for investigating the hypothesis that myofascial pain syndrome is characterized by changes in the mobility of myofascial interfaces.

Abstract An efficient 2-D continuum finite element method (FEM), including the rigid body algorithm and our previously developed contact element, was formulated for the contact stress analysis of articular joints. This FEM can calculate the contact pressure distribution on articular surfaces and stress distribution inside of cartilage. This method can model geometric and material nonlinearities for both the static and dynamic situations. The major advantage of this method is that only the soft cartilage requires finite element (FE) mesh, while the bony structure can be modeled as a rigid body due to its relatively rigid nature. Since much less degrees of freedom are now required in FEM, much faster computing speed can be achieved.

Abstract The methodological procedure for generating three-dimensional (3-D) finite element analysis (FEA) geometry models from CT or MRI medical imaging scan data was developed in this study. Medical images of a human scapula and a fifth proximal phalangeal bone were used to demonstrate the techniques of image processing and generation of 3-D FEA models. The biomedical imaging quality and its effects on the outcome of the FEA geometry model was also studied.