Objective: Lower limb malalignment accelerates the progression of knee osteoarthritis (KOA). Knee realignment osteotomy is a well-established treatment for unicompartmental KOA with malalignment. Traditional planning in KOA patients corrects deformities with an osteotomy at the metaphysis but overlooks Paley’s approach, which targets the center of rotation angulation (CORA). Osteotomy at the metaphysis may induce secondary translational deformities, which remain unstudied in KOA patients. This study aims to identify the CORA in KOA patients with tibial malalignment. Methods: Thirty tibiae (10 varus, 10 neutral, 10 valgus) from the IMI-APPROACH cohort were analyzed using computed tomography (CT) scans. The CORA, defined as the intersection of the proximal and distal mechanical axes, was identified. Translational deformity was calculated by multiplying the CORA-to-osteotomy distance by the tangent of the correction angle. Results: Among the varus tibiae, 9 out of 10 CORAs were located in the diaphysis, while 8 out of 10 valgus tibiae had their CORA in the diaphysis. When osteotomies were performed in the proximal metaphysis instead of the CORA location, secondary translational deformities of up to 3 cm were induced. Conclusion: In KOA patients with tibial malalignment, the CORA is predominantly located in the diaphysis rather than in the proximal metaphysis, where osteotomies are typically performed. This discrepancy leads to iatrogenic translational deformities. Future research should investigate the clinical impact of these deformities to optimize osteotomy planning and potentially improve long-term surgical outcomes.

Objective: This study aimed to divide leg malalignment into different categories of valgus and varus of the femur, tibia, and intra-articular knee joint and investigates whether knee osteoarthritis (OA) patients are susceptible for changes of such leg deformities over time. Design: This study included 317 radiographs and CT-images on baseline and 24 months of 169 patients (median age 67, 78.2 % female) of the prospective European IMI-APPROACH cohort, enrolled for knee OA. Femoral, tibial, and intra-articular geometry was determined. Different categories were analysed based on varus or valgus in the femur, in the tibia, or within the intra-articular joint. Changes of these variables over time and their correlations were determined with mixed model analysis. Results: Femurs tended to become more varus-like over the two-year follow up (0.3°, 95 % CI 0.6°–0.1°, p = 0.02), bony valgus femurs became more varus shaped (1.1°, 95 % CI:1.7°–0.5°, p < 0.001). Patients with bone varus and a normal joint line convergence angle (JLCA) showed a significant increase in intra-articular joint varus, with a mean JLCA increase of 1.1°(95 % CI:0.4°–1.7°, p = 0.005). By two years, they reached the threshold for defining intra-articular joint varus deformity, with a JLCA of 2.0°. Conclusions: Substantial intra-articular joint and bone varus progression was observed within two years. This study shows that bone deformity is to some extent a dynamic process and there is a growing varus malalignment in the intra-articular knee joint and bones. Thereby this study emphasizes the importance of leg malalignment for progression of intra-articular knee joint changes in early OA.

Objective: Herewith, we report the development of Orthopedic Digital Image Analysis (ODIA) software that is developed to obtain quantitative measurements of knee osteoarthritis (OA) radiographs automatically. Manual segmentation and measurement of OA parameters currently hamper large-cohort analyses, and therefore, automated and reproducible methods are a valuable addition in OA research. This study aims to test the automated ODIA measurements and compare them with available manual Knee Imaging Digital Analysis (KIDA) measurements as comparison. Design: This study included data from the CHECK (Cohort Hip and Cohort Knee) initiative, a prospective multicentre cohort study in the Netherlands with 1,002 participants. Knee radiographs obtained at baseline of the CHECK cohort were included and mean medial/lateral joint space width (JSW), minimal JSW, joint line convergence angle (JLCA), eminence heights, and subchondral bone intensities were compared between ODIA and KIDA. Results: Of the potential 2,004 radiographs, 1,743 were included for analyses. Poor intraclass correlation coefficients (ICCs) were reported for the JLCA (0.422) and minimal JSW (0.299). The mean medial and lateral JSW, eminence height, and subchondral bone intensities reported a moderate to good ICC (0.7 or higher). Discrepancies in JLCA and minimal JSW between the 2 methods were mostly a problem in the lateral tibia plateau. Conclusions: The current ODIA tool provides important measurements of OA parameters in an automated manner from standard radiographs of the knee. Given the automated and computerized methodology that has very high reproducibility, ODIA is suitable for large epidemiological cohorts with various follow-up time points to investigate structural progression, such as CHECK or the Osteoarthritis Initiative (OAI).