Alexander Mathiessen1, Erin L Ashbeck2, Emily Huang3, Edward John Bedrick4, C Kent Kwoh2, Jeffrey Duryea3. 1. Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, and Diakonhjemmet Hospital and University of Oslo, Oslo, Norway. 2. University of Arizona College of Medicine, Tucson. 3. Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts. 4. Mel and Enid Zuckerman College of Public Health, University of Arizona, Tucson.
Abstract
OBJECTIVE: Local-area cartilage segmentation (LACS) software was developed to segment medial femur (MF) cartilage on magnetic resonance imaging (MRI). Our objectives were 1) to extend LACS to the lateral femur (LF), medial tibia (MT), and lateral tibia (LT), 2) to compare LACS to an established manual segmentation method, and 3) to visualize cartilage responsiveness over each cartilage plate. METHODS: Osteoarthritis Initiative participants with symptomatic knee osteoarthritis (OA) were selected, including knees selected at random (n = 40) and knees identified with loss of cartilage based on manual segmentation (Chondrometrics GmbH), an enriched sample of 126 knees. LACS was used to segment cartilage in the MF, LF, MT, and LT on sagittal 3D double-echo steady-state MRI scans at baseline and at 2-year follow-up. We compared LACS and Chondrometrics average thickness measures by estimating the correlation in each cartilage plate and estimating the standardized response mean (SRM) for 2-year cartilage change. We illustrated cartilage loss topographically with SRM heatmaps. RESULTS: The estimated correlation between LACS and Chondrometrics measures was r = 0.91 (95% confidence interval [95% CI] 0.86, 0.94) for LF, r = 0.93 (95% CI 0.89, 0.95) for MF, r = 0.97 (95% CI 0.96, 0.98) for LT, and r = 0.87 (95% CI 0.81, 0.91) for MT. Estimated SRMs for LACS and Chondrometrics measures were similar in the random sample, and SRM heatmaps identified subregions of LACS-measured cartilage loss. CONCLUSION: LACS cartilage thickness measurement in the MF and LF and tibia correlated well with established manual segmentation-based measurement, with similar responsiveness to change, among knees with symptomatic knee OA. LACS measurement of cartilage plate topography enables spatiotemporal analysis of cartilage loss in future knee OA studies.
OBJECTIVE: Local-area cartilage segmentation (LACS) software was developed to segment medial femur (MF) cartilage on magnetic resonance imaging (MRI). Our objectives were 1) to extend LACS to the lateral femur (LF), medial tibia (MT), and lateral tibia (LT), 2) to compare LACS to an established manual segmentation method, and 3) to visualize cartilage responsiveness over each cartilage plate. METHODS: Osteoarthritis Initiative participants with symptomatic knee osteoarthritis (OA) were selected, including knees selected at random (n = 40) and knees identified with loss of cartilage based on manual segmentation (Chondrometrics GmbH), an enriched sample of 126 knees. LACS was used to segment cartilage in the MF, LF, MT, and LT on sagittal 3D double-echo steady-state MRI scans at baseline and at 2-year follow-up. We compared LACS and Chondrometrics average thickness measures by estimating the correlation in each cartilage plate and estimating the standardized response mean (SRM) for 2-year cartilage change. We illustrated cartilage loss topographically with SRM heatmaps. RESULTS: The estimated correlation between LACS and Chondrometrics measures was r = 0.91 (95% confidence interval [95% CI] 0.86, 0.94) for LF, r = 0.93 (95% CI 0.89, 0.95) for MF, r = 0.97 (95% CI 0.96, 0.98) for LT, and r = 0.87 (95% CI 0.81, 0.91) for MT. Estimated SRMs for LACS and Chondrometrics measures were similar in the random sample, and SRM heatmaps identified subregions of LACS-measured cartilage loss. CONCLUSION: LACS cartilage thickness measurement in the MF and LF and tibia correlated well with established manual segmentation-based measurement, with similar responsiveness to change, among knees with symptomatic knee OA. LACS measurement of cartilage plate topography enables spatiotemporal analysis of cartilage loss in future knee OA studies.
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