AutoCOR: autonomous condylar offset ratio calculator for post-operative total knee arthroplasty radiographs

Abstract

Background: This study aims to automate the measurement process of posterior condylar offset ratio (PCOR) and anterior condylar offset ratio (ACOR) to improve the Total Knee Arthroplasty (TKA) evaluation. Accurate calculation of PCOR and ACOR, performed manually by orthopedic surgeons, is crucial for assessing postoperative range of motion and implant positioning. Manual measurements, however, are time-consuming, prone to human error, and subject to variability. Automating this process could improve precision in clinical practice. Methods: We developed AutoCOR, a software system that autonomously calculates PCOR and ACOR by utilizing built-in function, employing k-means clustering, from the OpenCV library for image segmentation. The software detects key anatomical landmarks on true postoperative lateral radiographs. The definitions of PCOR and ACOR are PCO (posterior condylar offset) divided by femoral diameter, and ACOR is defined as ACO (anterior condylar offset) divided by femoral diameter, respectively. We tested the algorithm on 50 postoperative lateral radiographs of 32 patients from the Istanbul Kosuyolu Medipol Hospital, which included data from. The assessment process included calculating the mean, standard deviation and plotting the Bland-Altman plots, comparing AutoCOR's results against ground truth values. Results: The mean PCOR was 0.984 (SD 0.235) for AutoCOR and 0.972 (SD 0.164) for ground truth values, showing a strong correlation (Pearson r = 0.845, p < 0.0001). The mean ACOR was 0.107 (SD 0.092) for AutoCOR and 0.107 (SD 0.070) for ground truth values, with moderate correlation (Spearman's rs = 0.519, p = 0.0001). Conclusion: AutoCOR provides accurate measurements and shows potential to reduce variability in TKA evaluation, improving precision in clinical practice.