RT Journal Article SR Electronic T1 A Simple Automated Method for Detecting Recurrence in High-Grade Glioma JF American Journal of Neuroradiology JO Am. J. Neuroradiol. FD American Society of Neuroradiology DO 10.3174/ajnr.A4873 A1 T.K. Yanagihara A1 J. Grinband A1 J. Rowley A1 K.A. Cauley A1 A. Lee A1 M. Garrett A1 M. Afghan A1 A. Chu A1 T.J.C. Wang YR 2016 UL http://www.ajnr.org/content/early/2016/07/14/ajnr.A4873.abstract AB 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