Drew A Lansdown1, Gregory L Cvetanovich2, Nikhil N Verma3, Brian J Cole3, Bernard R Bach3, Gregory Nicholson3, Anthony Romeo4, Robert Dawe5, Adam B Yanke3. 1. Department of Orthopedic Surgery, University of California, San Francisco, San Francisco, California, U.S.A.. Electronic address: drew.lansdown@ucsf.edu. 2. Department of Orthopaedics, The Ohio State University Wexner Medical Center, Columbus, Ohio. 3. Department of Orthopedic Surgery, Rush University Medical Center, Chicago, Illinois, U.S.A. 4. Department of Orthopedic Surgery, Rothman Institute-New York, New York, New York, U.S.A. 5. Rush Alzheimer's Disease Center, Rush University Medical Center, Chicago, Illinois, U.S.A.
Abstract
PURPOSE: To evaluate clinical measurements of glenoid bone loss based on 3-dimensional (3D) computed tomography (CT) and automatically segmented 3D reconstructions from Dixon fat-water magnetic resonance (MR) imaging. METHODS: Available CT and MR studies from 16 patients with recurrent anterior shoulder instability were retrospectively reviewed. Three-dimensional reconstructions were formed independently by 2 observers using freely available software and a simple threshold-based segmentation (3D Slicer, version 4.8.0; http://www.slicer.org). Bone loss was estimated with the perfect-circle method. Intra-user and interuser reproducibility was determined with intraclass correlation coefficients. Bland-Altman plots were used to evaluate the similarity between imaging modalities. RESULTS: Differences between MR and CT estimates of bone loss ranged from 0% to 6%. The individual intraclass correlation coefficients showed good to excellent reliability, with intraobserver comparisons between MR- and CT-based bone loss estimates ranging from 0.94 to 0.99. Bland-Altman plots showed 95% confidence intervals from -5% to 6% for differences between MR and CT estimates, with 88% of all measurements (42 of 48) showing a less than 2% difference between MR and CT estimates. CONCLUSIONS: The described methodology for obtaining an MR-based 3D reconstruction of the glenoid can evaluate glenoid bone loss similarly to the performance of a 3D CT reconstruction. The results may allow surgeons to simplify the preoperative imaging protocol for patients with recurrent shoulder stabilization and limit the number of shoulder CT scans. LEVEL OF EVIDENCE: Level III, retrospective therapeutic trial.
PURPOSE: To evaluate clinical measurements of glenoid bone loss based on 3-dimensional (3D) computed tomography (CT) and automatically segmented 3D reconstructions from Dixon fat-water magnetic resonance (MR) imaging. METHODS: Available CT and MR studies from 16 patients with recurrent anterior shoulder instability were retrospectively reviewed. Three-dimensional reconstructions were formed independently by 2 observers using freely available software and a simple threshold-based segmentation (3D Slicer, version 4.8.0; http://www.slicer.org). Bone loss was estimated with the perfect-circle method. Intra-user and interuser reproducibility was determined with intraclass correlation coefficients. Bland-Altman plots were used to evaluate the similarity between imaging modalities. RESULTS: Differences between MR and CT estimates of bone loss ranged from 0% to 6%. The individual intraclass correlation coefficients showed good to excellent reliability, with intraobserver comparisons between MR- and CT-based bone loss estimates ranging from 0.94 to 0.99. Bland-Altman plots showed 95% confidence intervals from -5% to 6% for differences between MR and CT estimates, with 88% of all measurements (42 of 48) showing a less than 2% difference between MR and CT estimates. CONCLUSIONS: The described methodology for obtaining an MR-based 3D reconstruction of the glenoid can evaluate glenoid bone loss similarly to the performance of a 3D CT reconstruction. The results may allow surgeons to simplify the preoperative imaging protocol for patients with recurrent shoulder stabilization and limit the number of shoulder CT scans. LEVEL OF EVIDENCE: Level III, retrospective therapeutic trial.
Authors: Madeleine A Salesky; Alan L Zhang; C Benjamin Ma; Brian T Feeley; Valentina Pedoia; Drew A Lansdown Journal: Arthrosc Sports Med Rehabil Date: 2022-02-13
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