Abstract
Weight bearing whole-leg radiograph (WLR) is essential to assess lower limb alignment such as weight bearing line (WBL) ratio. The purpose of this study was to develop a deep learning (DL) model that predicts the WBL ratio using knee standing AP alone. Total of 3997 knee AP & WLRs were used. WBL ratio was used for labeling and analysis of prediction accuracy. The WBL ratio was divided into seven categories (0, 0.1, 0.2, 0.3, 0.4, 0.5, and 0.6). After training, performance of the DL model was evaluated. Final performance was evaluated using 386 subjects as a test set. Cumulative score (CS) within error range 0.1 was set with showing maximum CS in the validation set (95% CI, 0.924–0.970). In the test set, mean absolute error was 0.054 (95% CI, 0.048–0.061) and CS was 0.951 (95% CI, 0.924–0.970). Developed DL algorithm could predict the WBL ratio on knee standing AP alone with comparable accuracy as the degree primary physician can assess the alignment. It can be the basis for developing an automated lower limb alignment assessment tool that can be used easily and cost-effectively in primary clinics.
Highlights
Osteoarthritis (OA), characterized by the degeneration of joints, is the single most common cause of disability in the elderly [1]
The disease burden of knee OA is quite high; OA ranked the eleventh burden of disease measured by the years lost due to disability (YLD) and knee OA accounts for approximately 85% of the burden [2,3]
From March 2003 to May 2018, a total of 72,258 patients suffering from knee pain and who subsequently underwent standing knee AP radiographs were searched by the clinical data warehouse in our hospital
Summary
Osteoarthritis (OA), characterized by the degeneration of joints, is the single most common cause of disability in the elderly [1]. The disease burden of knee OA is quite high; OA ranked the eleventh burden of disease measured by the years lost due to disability (YLD) and knee OA accounts for approximately 85% of the burden [2,3]. OA can develop due to wear and tear on any joint, and the joints that bear our weight such as the knee joint are more susceptible [4]. The medial compartment is the most commonly affected, and accompanying varus malalignment that serves as an important risk factor of development and progression of the disease with vicious cycle [5,6,7]. Since varus malalignment increases the load on the medial compartment, the knee joint with severe medial OA is inevitably more vulnerable to progression of varus malalignment [7,8,9]. For diagnosing and follow-up of the knee OA patients, assessment of the alignment is essential
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