Automated MRI assessment confirms cartilage thickness modification in patients with knee osteoarthritis: post-hoc analysis from a phase II sprifermin study

Osteoarthritis and Cartilage(2020)

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摘要
Background: Sprifermin is under investigation as a potential disease-modifying osteoarthritis drug. Previously, 2-year results from the FORWARD study showed significant dose-dependent modification of cartilage thickness in the total femorotibial joint (TFTJ), medial and lateral femorotibial compartments (MFTC, LFTC), and central medial and lateral TFTJ subregions, by quantitative magnetic resonance imaging (qMRI) using manual segmentation. Objective: To determine whether qMRI findings from FORWARD could be reproduced by an independent method of automated segmentation using an identical dataset and similar anatomical regions in a post-hoc analysis. Method: Cartilage thickness was assessed at baseline and 6, 12, 18 and 24 months, using automated cartilage segmentation with active appearance models, a supervised machine learning method. Images were blinded for treatment and timepoint. Treatment effect was assessed by observed and adjusted changes using a linear mixed model for repeated measures. Results: Based on automated segmentation, statistically significant, dose-dependent structural modification of cartilage thickness was observed over 2 years with sprifermin vs placebo for TFTJ (overall treatment effect and dose response, both P < 0.001), MFTC (P = 0.004 and P = 0.044), and LFTC (both P < 0.001) regions. For highest dose, in the central medial tibial (P = 0.008), central lateral tibial (P < 0.001) and central lateral femoral (P < 0.001) regions. Conclusions: Cartilage thickness assessed by automated segmentation provided a consistent dose response in structural modification compared with manual segmentation. This is the first time that two independent quantification methods of image analysis have reached the same conclusions in an interventional trial, strengthening the conclusions that sprifermin modifies structural progression in knee osteoarthritis. (C) 2020 Osteoarthritis Research Society International. Published by Elsevier Ltd. All rights reserved.
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关键词
Osteoarthritis,DMOAD,Cartilage,Machine learning,Active appearance models
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