Abstract
Decisions regarding total knee arthroplasty are usually made using a patient's own assessment of pain and the structural disposition of the joint as seen on plain film radiographs. Pain severity can fluctuate, and radiographs can be misleading, with the apparent joint status affected by anatomical orientation. An important component of the surgical management of knee osteoarthritis (OA) is the timing of surgical intervention: knee arthroplasty performed too early in the course of the disease may increase the need for revision surgery.Femoral 3D bone shape (B-score) from MR images is an objective measure of OA severity and has been correlated with current and future risk of pain. We aimed to derive the B-score from CT images and compare it against the B-score derived from MR images.We used baseline and 24-month image data from the IMI-APPROACH 2-year prospective cohort study, comprising pairs of CT and MR images taken for each subject-timepoint. The femur was automatically segmented in both CT and MR modalities using an active appearance model, a machine-learning method, to measure the B-score. Linear regression was used to test for correlation between measures. Limits of agreement and bias were tested using Bland-Altman analysis.CT-MR pairs of the same knee were available from 424 participants (78 % women). B-scores from CT and MR were strongly correlated (CCC = 0.980) with negligible bias of 0.0106 (95 % CI: −0. 0281, +0.0493).The strong correlation and small B-score bias suggests that B-scores may be measured reliably using CT images. Since CT images are used in planning robot-assisted knee arthroplasty, with further study B-scores derived from CT surgical planning images could in principle provide a useful objective input to deciding the appropriateness, timing and type of knee arthroplasty.
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