Project Summary/Abstract
The wrist is a complex and versatile structure, which allows a substantial degree of three-dimensional motion.
To adequately diagnose and treat carpal injuries, it is important to understand the basic science and clinical
relevance of functional kinematics of the wrist. However, the analysis of carpal kinematics is challenging due to
the multiplanar rotations and translations of the carpal bones, the irregularity of their shape, and the small
magnitudes of movements. Most studies have been performed in vitro on cadaveric wrists, and in vivo
approaches based on noninvasive imaging have been proposed only recently. Initial in vivo work used CT or
MRI to obtain three-dimensional (3D) images of carpal bones at multiple static poses of the hand to reconstruct
an animated movement pattern. Since true dynamic joint kinematics may deviate from its animated counterpart,
more recent work has explored the possibility of real-time imaging during continuous wrist motion using 4D CT,
fluoroscopy and two-dimensional (2D) dynamic MRI. However, these methods either involves ionizing radiation
or cannot capture out-of-plane translations and rotations that occur even during relatively simple wrist
movements, because of their 2D nature. In this project, we will develop a new technique for quantitative analysis
of carpal kinematics based, for the first time, on 3D dynamic MRI acquisitions. We will develop a processing
pipeline that will combine automated segmentation of the carpal bones and the extraction of their motion patterns
during ulnar-radial deviation and flexion-extension of the wrist. We will conduct a pilot validation study on healthy
volunteers and patients with clinical evidence of carpal instability, with the goal of characterizing normal wrist
kinematics and identifying quantitative metrics to detect pathologic wrist conditions. We will also investigate an
alternative imaging approach based on the combination of parallel MRI and compressed sensing to further
accelerate the 3D dynamic MRI. Toward the end of the project, we will validate this new dynamic imaging
technique to assess whether the improved temporal resolution is clinically significant for the analysis of carpal
kinematics. Successful completion of this project will provide a new, 3D MRI-based technique for in vivo
characterization and visualization of 3D skeletal kinematics, providing novel insights into normal wrist function
and pathophysiology of wrist instability. Our proposed automated image processing pipeline will facilitate clinical
translation. The ability to assess dynamic motion patterns will contribute to diagnosis, therapy, and prosthesis
development for wrist disorders, enabling to evaluate the long-term effects of healing and surgical intervention.
The proposed technique could also have an impact for the dynamic evaluation of other anatomical structures
such as, for example, the ankle.