title: A Simple Automated Method for Detecting Recurrence in High-Grade Glioma.
abstract: 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.
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.) tky2102@columbia.edu.
authors.forename: T K
authors.identifier: http://orcid.org/0000-0001-7123-0637
authors.initials: TK
authors.lastname: Yanagihara
authors.affiliation: Radiology (J.G., K.A.C.).
authors.forename: J
authors.identifier: http://orcid.org/0000-0001-7658-6755
authors.initials: J
authors.lastname: Grinband
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).
authors.forename: J
authors.identifier: http://orcid.org/0000-0001-9690-7683
authors.initials: J
authors.lastname: Rowley
authors.affiliation: Radiology (J.G., K.A.C.).|Division of Neuroradiology (K.A.C.), Geisinger Medical Center, Danville, Pennsylvania.
authors.forename: K A
authors.identifier: http://orcid.org/0000-0002-0247-0650
authors.initials: KA
authors.lastname: Cauley
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).
authors.forename: A
authors.identifier: http://orcid.org/0000-0001-7499-574X
authors.initials: A
authors.lastname: Lee
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).
authors.forename: M
authors.identifier: http://orcid.org/0000-0002-9446-189X
authors.initials: M
authors.lastname: Garrett
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).|Department of Radiation Oncology (M.A.), Albany Medical Center, Albany, New York.
authors.forename: M
authors.identifier: http://orcid.org/0000-0001-6826-6938
authors.initials: M
authors.lastname: Afghan
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).
authors.forename: A
authors.identifier: http://orcid.org/0000-0003-4422-2441
authors.initials: A
authors.lastname: Chu
authors.affiliation: From the Departments of Radiation Oncology (T.K.Y., J.R., A.L., M.G., M.A., A.C., T.J.C.W.).|Herbert Irving Comprehensive Cancer Center (T.J.C.W.), Columbia University Medical Center, New York, New York.
authors.forename: T J C
authors.identifier: http://orcid.org/0000-0001-5809-3025
authors.initials: TJC
authors.lastname: Wang