Abstract
Knee Image Digital Analysis (KIDA) is standardized radiographic analysis software for measuring osteoarthritis (OA) characteristics. It was validated in mild OA, but used for severe OA as well. The current goal was to evaluate the performance of KIDA in severe OA. Of 103 patients, standardized radiographs were performed before and one and 2years after treatment for severe OA. All radiographs were evaluated on subchondral bone density, joint space width (JSW), osteophytes, eminence height, and joint angle, twice within years by the same observer. Part of the radiographs were randomly selected for reevaluation twice within 1month and evaluation by another observer. The intraclass correlation coefficient (ICC), smallest detectable difference (SDD) and coefficient of variation (CV) were calculated; the SDD and CV were compared to those in mild OA. The relation of severity with KIDA parameters and with observer differences was calculated with linear regression. Intra-observer ICCs were higher in the 98 severe radiographs reanalyzed within 1month (all >0.8) than the 293 reanalyzed within years (all >0.5; most >0.8) and than inter-observer ICCs (all >0.7). SDDs and CVs were smaller when reanalyzed within a month and comparable to those in mild OA. Some parameters showed bias between readings. Severity showed significant relation with osteophytes and JSW parameters, and with the observer variation in these parameters (all P<0.04). KIDA is a well-performing tool also for severe OA. In order to decrease variability and SDDs, images should be analyzed in a limited time frame and randomized order.
Highlights
Osteoarthritis (OA) is a degenerative joint disease characterized by structural changes like cartilage degeneration, osteophyte formation, and subchondral bone changes[1]
The usefulness and validity of the Knee Image Digital Analysis (KIDA) parameters was initially demonstrated for patients with relatively mild knee OA, as indicated by their average Kellgren & Lawrence (K&L) grade of 1.3, and measurements were shown to distinguish these patients from healthy controls
In a randomized controlled trial (RCT), where knee joint distraction (KJD) was compared with total knee arthroplasty (TKA), 20 end-stage knee OA patients indicated for TKA were treated with KJD
Summary
Osteoarthritis (OA) is a degenerative joint disease characterized by structural changes like cartilage degeneration, osteophyte formation, and subchondral bone changes[1]. With the exception of joint space width (JSW) as a surrogate measure of cartilage thickness, radiography-based knee OA characteristics are most often evaluated using a grading system, such as the Kellgren & Lawrence (K&L) grade and Altman score[3,4] While these grading systems have been validated and proven useful, stepwise scoring of OA-related parameters makes results less sensitive to small changes over time. The usefulness and validity of the Knee Image Digital Analysis (KIDA) parameters was initially demonstrated for patients with relatively mild knee OA, as indicated by their average K&L grade of 1.3, and measurements were shown to distinguish these patients from healthy controls Such distinction in mild OA is key for early detection of presence and progression of radiographic changes. Both the inter- and intra-observer variability were proven to be relatively low, and the smallest detectable difference (SDD)
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