TY - JOUR T1 - A Simple Automated Method for Detecting Recurrence in High-Grade Glioma JF - American Journal of Neuroradiology JO - Am. J. Neuroradiol. DO - 10.3174/ajnr.A4873 AU - T.K. Yanagihara AU - J. Grinband AU - J. Rowley AU - K.A. Cauley AU - A. Lee AU - M. Garrett AU - M. Afghan AU - A. Chu AU - T.J.C. Wang Y1 - 2016/07/14 UR - http://www.ajnr.org/content/early/2016/07/14/ajnr.A4873.abstract N2 - SUMMARY: Our aim was to develop an automated multiparametric MR imaging analysis of routinely acquired imaging sequences to identify areas of focally recurrent high-grade glioma. Data from 141 patients treated with radiation therapy with a diagnosis of high-grade glioma were reviewed. Strict inclusion/exclusion criteria identified a homogeneous cohort of 12 patients with a nodular recurrence of high-grade glioma that was amenable to focal re-irradiation (cohort 1). T1WI, FLAIR, and DWI data were used to create subtraction maps across time points. Linear regression was performed to identify the pattern of change in these 3 imaging sequences that best correlated with recurrence. The ability of these parameters to guide treatment decisions in individual patients was assessed in a separate cohort of 4 patients who were treated with radiosurgery for recurrent high-grade glioma (cohort 2). A leave-one-out analysis of cohort 1 revealed that automated subtraction maps consistently predicted the radiologist-identified area of recurrence (median area under the receiver operating characteristic curve = 0.91). The regression model was tested in preradiosurgery MRI in cohort 2 and identified 8 recurrent lesions. Six lesions were treated with radiosurgery and were controlled on follow-up imaging, but the remaining 2 lesions were not treated and progressed, consistent with the predictions of the model. Multiparametric subtraction maps can predict areas of nodular progression in patients with previously treated high-grade gliomas. This automated method based on routine imaging sequences is a valuable tool to be prospectively validated in subsequent studies of treatment planning and posttreatment surveillance.AbbreviationsFSLfMRI of the Brain Software LibraryGBMglioblastomaGKRSgamma knife radiosurgeryHGGhigh-grade gliomaROCreceiver operating characteristic ER -