Fan Y, Liu Z, Hou B, et al. - In this investigation, researchers developed and validated an MRI-based radiomic signature for preoperative prediction of treatment response in invasive functional pituitary adenoma (IFPA). The study sample consisted of 163 patients with IFPA and divided into primary (n = 108) and validation cohorts (n = 55) according to time point. According to postoperative hormone levels, IFPA patients were divided into remission and non-remission. In order to construct the radiomic signature, seven radiomic characteristics were chosen to achieve an area under the curve (AUC) of 0.834 and 0.808 on the primary and validation cohorts. With AUCs of 0.832 and 0.811 for the primary and validation cohorts respectively, the radiomic model incorporating the radiomic signature and Knosp grade showed good discrimination capabilities and calibration. Findings suggested that this radiomic model can assist neurosurgeons to predict before surgery the treatment responses of IFPA patients and identify individual treatment strategies.