Magnetic Resonance Imaging-Based Diagnostic Protocol and Risk Prediction for Epidural Lipomatosis in Degenerative Lumbar Spondylolisthesis.

This protocol presents a standardized magnetic resonance imaging (MRI)-based diagnostic approach for epidural lipomatosis in patients with degenerative lumbar spondylolisthesis (DLS) and describes the development of a clinical risk prediction model. Consecutive patients with DLS underwent standardized MRI evaluation, including T1-weighted sequences for epidural lipomatosis detection, Goutallier grading of multifidus fatty infiltration, and radiographic assessment. The study cohort was partitioned into a modeling cohort (n = 248) and a validation cohort (n = 106). Independent predictors were identified through univariate screening followed by multivariable binary logistic regression. For transparent reporting, the effects of age and body mass index (BMI) are expressed per 10-year and per 5 kg/m2 increases, respectively. The bedside prediction equation is presented using algebraically equivalent raw-unit coefficients so that age (years) and BMI (kg/m2) can be entered directly. Five independent predictors were identified: age (odds ratio [OR] = 1.510 per 10-year increase), female sex (OR = 2.354), BMI (OR = 1.874 per 5 kg/m2 increase), L5 segment involvement (OR = 3.766), and Goutallier grade 3-4 (OR = 3.184). The model achieved area under the receiver operating characteristic curve values of 0.834 in the modeling cohort and 0.815 in the validation cohort. Calibration and decision curve analyses supported the model as an exploratory clinical decision-support tool; however, external validation is required before broad clinical implementation. This protocol provides a reproducible MRI-based framework for epidural lipomatosis assessment with an integrated bedside prediction tool that combines clinical and radiographic parameters to facilitate standardized evaluation and individualized risk prediction in patients with DLS.