Article
A computational musculoskeletal model of the PIP joint generated with anatomical data from MR, CT and optical motion capture
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Published: | October 10, 2017 |
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Outline
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Objectives: The PIP joint is complex, with movement & stability controlled by bone contour, ligament tension & a kinetic chain of intrinsic & extrinsic tendons. PIP joint replacement has an uncertain outcome & high failure rate, compromised by
- disruption to normal anatomy by disease
- surgical inaccuracy in reproducing joint kinematics
- imperfect prosthetic joint geometry
Better understanding of the complex joint dynamics in health, disease & after arthroplasty through computational modelling will contribute to improved outcomes.
Method: We are developing a computational musculoskeletal model of the index finger which includes
- tendon-muscle: intrinsic & extrinsic muscles
- ligaments: ulnar & radial collateral ligaments, volar plates & retinacular ligaments
- bone: distal end of ulna & radius, carpal bones & phalanges.
In 9 healthy volunteers, we obtained bone & soft tissue data from CT & MR and hand kinematics from optical motion capture. All data were acquired in extension, partial flexion & flexion, standardised with 3D printed jig.
Using enhanced motion capture markers and AnyBody's force dependent kinematics (FDK), the simulated PIPJ model includes rotations & translations, thus more physiologically accurate than existing models.
Results: We will present high resolution dynamic 3D images representing the complexities of the PIPJ & its supporting soft tissue structures.
Conclusion: This model will allow better understanding of the PIPJ in health & disease. Pre-operative modelling will inform more accurate surgical cuts & even bespoke implant design. Post-operative analysis of failed arthroplasty will lead to better understanding of the bone & soft tissue imbalances and implant flaws which contribute to failure.