Abstract
OBJECTIVE: This study aimed to determine the optimal index for distinguishing ankylosing spondylitis (AS) from non-AS by employing texture analysis of bone marrow edema (BME) in lumbar spine MR images. METHODS: We conducted a retrospective analysis, involving patients meeting specific criteria with positive BME signs in lumbar spine MRI. We compared 72 cases (78 lesions) from the AS group with 67 cases (84 lesions) from the non-AS group. Image acquisition was single-blind, and we defined the region of interest (ROI) at the lumbar spine's maximal BME level using ImageJ software. Texture analysis parameters were extracted from Gray Level Histogram(GLH) and Gray-Level Co-occurrence Matrix(GLCM) of STIR and T2WI sequences in both groups. We generated Receiver Operating Characteristic(ROC) curves based on statistically significant parameters and calculated the area under the curve (AUC). RESULTS: In BME STIR GLH analysis, AS group had higher Mean, Mode, Min, and Skew parameters than the non-AS group (p < 0.001), with Min exhibiting the highest diagnostic efficacy (AUC = 0.768). T2WI GLH analysis showed that only Min was significantly higher in the AS group (p = 0.014,AUC = 0.612). Analysis of BME zones in the STIR GLCM revealed significant differences in ASM and Ent parameters between the AS and non-AS groups, with ASM displaying the highest diagnostic accuracy (p < 0.001,AUC = 0.656). For T2WI GLCM analysis, all four parameters (ASM, Cor, IDM, and Ent) were significantly different in the AS group (p < 0.001), with ASM demonstrating the highest diagnostic accuracy (AUC = 0.731). CONCLUSIONS: Lumbar BME texture analysis effectively distinguishes AS from non-AS, with significant variations in multiple parameter values. The STIR GLH parameter Min provides the highest diagnostic accuracy.