Rapid personalized computational modeling of the wrist

Computational modeling may help to develop new treatments for hand and wrist injuries, but at present, few models exist, as the time and expertise required is considerable. Moreover, most models do not allow for variation of material properties. We have developed an automated workflow combining morphing with algorithmic techniques to create personalized finite element models. Using this workflow, three personalized models were created from our existing four-dimensional computed tomography data. These were then used to demonstrate the usefulness of these models to investigate clinical questions, namely calibration of ligament properties to participant-obtained kinematics, and Monte Carlo analysis of the impacts of ligament injury on joint contact pressure, as an analogue for joint injury that may lead to osteoarthritis. New models can be created in 2 hours and individual simulations performed in 45 seconds. This work enables future patient-specific modeling. Lastly, to encourage reproducibility, we have made the data, models, and code publicly available online.

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Publication Details

Journal
Medical Engineering & Physics
Published
2026-07-02
DOI
https://doi.org/10.1088/1873-4030/ae8542
Primary Topic
Orthopedic Surgery and Rehabilitation
Type
article
Field-Weighted Citation Impact
0.00

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article

Rapid personalized computational modeling of the wrist

Sanjeev Kakar, Taylor P. Trentadue, Thor E. Andreassen, Kristin D. Zhao et al.
Medical Engineering & Physics
Orthopedic Surgery and Rehabilitation
article

Rapid personalized computational modeling of the wrist

Sanjeev Kakar, Taylor P. Trentadue, Thor E. Andreassen, Kristin D. Zhao, Andrew Thoreson, Kai-Nan An
article en

Abstract

Computational modeling may help to develop new treatments for hand and wrist injuries, but at present, few models exist, as the time and expertise required is considerable. Moreover, most models do not allow for variation of material properties. We have developed an automated workflow combining morphing with algorithmic techniques to create personalized finite element models. Using this workflow, three personalized models were created from our existing four-dimensional computed tomography data. These were then used to demonstrate the usefulness of these models to investigate clinical questions, namely calibration of ligament properties to participant-obtained kinematics, and Monte Carlo analysis of the impacts of ligament injury on joint contact pressure, as an analogue for joint injury that may lead to osteoarthritis. New models can be created in 2 hours and individual simulations performed in 45 seconds. This work enables future patient-specific modeling. Lastly, to encourage reproducibility, we have made the data, models, and code publicly available online.

Medical Engineering & Physics
Mayo Clinic (US)
National Institute of General Medical Sciences, National Institute of Arthritis and Musculoskeletal and Skin Diseases
Gender equality
Openalex Percentile: Top 6%
Orthopedic Surgery and Rehabilitation
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