Automatic analysis of the scapholunate distance using 4DCT imaging: normal values in the healthy wrist.

ABSTRACT

AIM: Early diagnosis of scapholunate ligament (SLL) injuries is crucial to prevent progression to debilitating osteoarthritis. Four-Dimensional Computed Tomography (4DCT) is a promising dynamic imaging modality for assessing such injuries. Capitalizing on the known correlation between SLL injuries and an increased scapholunate distance (SLD), this study aims to develop a fully automatic approach to evaluate the SLD continuously during wrist motion and to apply it to a dataset of healthy wrists to establish reference values. MATERIALS AND METHODS: 50 healthy wrists were analysed in this study. All subjects performed radioulnar deviation (RUD), flexion-extension (FE), and clenching fist (CF) movements during 4DCT acquisition. A novel, automatic method was developed to continuously compute the SLD at five distinct locations within the scapholunate joint, encompassing a centre, volar, dorsal, proximal, and distal measurement. RESULTS: The developed algorithm successfully processed datasets from all subjects. Our results showed that the SLD remained below 2 mm and exhibited minimal changes (median ranges between 0.3 mm and 0.65 mm) during RUD and CF at all measured locations. During FE, the volar and dorsal SLD changed significantly, with median ranges of 0.90 and 1.27 mm, respectively. CONCLUSION: This study establishes a unique database of normal SLD values in healthy wrists during wrist motion. Our results indicate that, aside from RUD and CF, FE may also be important in assessing wrist kinematics. Given the labour-intensive and time-consuming nature of manual analysis of 4DCT images, the introduction of this automated algorithm enhances the clinical utility of 4DCT in diagnosing dynamic wrist injuries.