Unconstrained Kinematic MRI Tracking of Wrist Carpal Bones

TL;DR

This study demonstrates a novel MRI-based method for tracking wrist carpal bone motion during unconstrained movements, achieving accurate kinematic profiling with specific acquisition parameters in healthy subjects.

Contribution

Introduces a new MRI technique combining under-sampled 3D imaging and point-cloud registration for dynamic wrist kinematic analysis.

Findings

Achieved 2.57s temporal resolution per volume.

Errors in rotation angles were approximately 1.9°.

Errors in displacement profiles were around 0.3mm.

Abstract

In this preliminary study technical methodology for kinematic tracking and profiling of wrist carpal bones during unconstrained movements is explored. Heavily under-sampled and fat-saturated 3D Cartesian MRI acquisition were used to capture temporal frames of the unconstrained moving wrist of 5 healthy subjects. A slab-to-volume point-cloud based registration was then utilized to register the moving volumes to a high-resolution image volume set collected at a neutral resting position. Comprehensive error analyses for different acquisition parameter settings were performed to evaluate the performance limits of several derived kinematic metrics. Computational results suggested that sufficient volume coverage for the dynamic acquisitions was reached when collecting 12 slice-encodes at 2.5mm resolution, which yielded a temporal resolution of and 2.57 seconds per volumetric frame. These acquisition parameters resulted in total absolute errors of 1.9$^\circ\pm$1.8$^\circ$ (3$^\circ\pm$4.6$^\circ$) in derived rotation angles and 0.3mm$\pm$0.47mm (0.72mm$\pm$0.8mm) in center-of-mass displacement kinematic profiles within ulnar-radial (flexion-extension) motion. The results of this study have established the feasibility of kinematic metric tracking of unconstrained wrist motion using 4D MRI. Temporal metric profiles derived from ulnar-radial deviation motion demonstrated better performance than those derived from flexion/extension movements. Future work will continue to explore the use of these methods in deriving more complex kinematic metrics and their application to subjects with symptomatic carpal dysfunction.