The multivariate logistic regression model based on clinical features and preoperative MRI characterization to the grading of ISFT

Motivation: Retrospective study. Goal(s): To investigate the clinical features of intracranial solitary fibrous tumor (ISFT) of grade Ⅱ to Ⅲ and the significance of preoperative MRI characterization in grading. Approach: Intergroup comparison was conducted according to postoperative pathological grade. Binary logistic regression was performed to identify effective imaging indexes that could predict pathological grade. Results: Difference analysis between groups showed significant differences intumor location, skull invasion, tumor across midline, maximum apparent diffusion coefficient (ADCmax), mean ADC value (ADCave), minimum ADC value (ADCmin) between grade Ⅱ and grade Ⅲ patients Impact: A multivariate logistic regression analysis model was constructed to diagnose ISFT grading, and it was found that ADCmax and ADCave value could be used as effective predictors, which would provide an important reference for preoperative imaging grading of ISFT patients.