Quantitative Analysis of Carpal Kinematics Using 3D Dynamic MRI

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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.