Predictive validity of radiographic signs of complete discoid lateral meniscus in children using machine learning techniques.

The diagnostic utility of radiographic signs of complete discoid lateral meniscus remains controversial. This study aimed to investigate the diagnostic accuracy and determine which sign is most reliably detects the presence of a complete discoid lateral meniscus in children. A total of 141 knees (age 7-16) with complete discoid lateral meniscus and 141 age- and sex-matched knees with normal meniscus were included. The following radiographic signs were evaluated: lateral joint (LJ) space, fibular head (FH) height, lateral tibial spine (LTS) height, lateral tibial plateau (LTP) obliquity, lateral femoral condyle (LFC) squaring, LTP cupping, LFC notching, and prominence ratio of the femoral condyle. Prediction models were constructed using logistic regressions, decision trees, and random forest analyses. Receiver operating characteristic curves and area under the curve (AUC) were estimated to compare the diagnostic accuracy of the radiographic signs and model fit. The random forest model yielded the best diagnostic accuracy (AUC: 0.909), with 86.5% sensitivity and 82.2% specificity. LJ space height, FH height, and prominence ratio showed statistically large AUC compared with LTS height and LTP obliquity (P < .05 in all). The cut-off values for diagnosing discoid meniscus to be <12.55 mm for FH height, <0.804 for prominence ratio, and >6.6 mm for LJ space height when using the random forest model. On the basis of the results of this study, in clinical practice, LJ space height, FH height and prominence ratio could be easily used as supplementary tools for complete discoid lateral meniscus in children.