Applied Sciences (Jan 2023)

In-Vivo Quantification of Knee Deep-Flexion in Physiological Loading Condition trough Dynamic MRI

  • Michele Conconi,
  • Filippo De Carli,
  • Matteo Berni,
  • Nicola Sancisi,
  • Vincenzo Parenti-Castelli,
  • Giuseppe Monetti

DOI
https://doi.org/10.3390/app13010629
Journal volume & issue
Vol. 13, no. 1
p. 629

Abstract

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The in-vivo quantification of knee motion in physiological loading conditions is paramount for the understanding of the joint’s natural behavior and the comprehension of articular disorders. Dynamic MRI (DMRI) represents an emerging technology that makes it possible to investigate the functional interaction among all the joint tissues without risks for the patient. However, traditional MRI scanners normally offer a reduced space of motion, and complex apparatus are needed to load the articulation, due to the horizontal orientation of the scanning bed. In this study, we present an experimental and computational procedure that combines an open, weight-bearing MRI scanner with an original registration algorithm to reconstruct the three-dimensional kinematics of the knee from DMRI, thus allowing the investigation of knee deep-flexion under physiological loads in space. To improve the accuracy of the procedure, an MR-compatible rig has been developed to guide the knee flexion of the patient. We tested the procedure on three volunteers. The overall rotational and positional accuracy achieved are 1.8° ± 1.4 and 1.2 mm ± 0.8, respectively, and they are sufficient for the characterization of the joint behavior under load.

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