• Jacob L Jaremko, Meaghan Pitts, Walter P Maksymowych, and Robert G Lambert.
• From the Department of Radiology and Diagnostic Imaging and the Department of Rheumatology, Faculty of Medicine, University of Alberta, Edmonton, Alberta, Canada.J.L. Jaremko, FRCPC; M. Pitts, FRCPC, Department of Radiology and Diagnostic Imaging, Faculty of Medicine, University of Alberta; W.P. Maksymowych, FRCPC, Department of Rheumatology, Faculty of Medicine, University of Alberta; R.G. Lambert, FRCPC, Department of Radiology and Diagnostic Imaging, Faculty of Medicine, University of Alberta. jjaremko@ualberta.ca.
• J Rheumatol. 2016 Jan 1; 43 (1): 223-31.

ObjectiveSemiquantitative arthritis scoring assesses disease burden by scoring presence/extent of features such as bone marrow lesion (BML) or effusion in multiple anatomic regions at a joint. An image overlay clarifying region borders may enhance feasibility and reliability of these scoring systems. To be scalable for use in large clinical trials, systematic computer-based user training is desirable. We developed an overlay and user training module for magnetic resonance imaging (MRI)-based scoring of hip osteoarthritis (OA).MethodsWe designed a semitransparent 2-dimensional image overlay applied to individual MRI slices to facilitate hip OA scoring [HIMRISS (Hip Inflammation MRI Scoring System)], initially using freeware and then in a customized HTML Web browser environment. We developed a systematic knowledge translation package including instructional presentation, fully scored expert consensus cases, and video tutorials for training in the use of these scoring systems with the overlays. Three musculoskeletal radiologists who had not used this scoring system before each performed a scoring exercise with no overlay, then repeated this with overlays after completing the training module. Based on postexercise interviews and a reader survey, we identified and corrected problems in the module. The entire training process was then repeated using 3 new readers.ResultsOverlays were considered useful, particularly when integrated into a Web browser. The knowledge translation module was considered conceptually valuable, but as initially implemented was too lengthy and not sufficiently interactive.ConclusionSemitransparent image overlays and standardized knowledge translation modules for reader training show promise to facilitate reader calibration using MRI-based scoring systems. Based on our experience, knowledge translation modules should emphasize close feedback evaluating performance and reader time efficiency.

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