title: Computer-Extracted Texture Features to Distinguish Cerebral Radionecrosis from Recurrent Brain Tumors on Multiparametric MRI: A Feasibility Study.
abstract: Despite availability of advanced imaging, distinguishing radiation necrosis from recurrent brain tumors noninvasively is a big challenge in neuro-oncology. Our aim was to determine the feasibility of radiomic (computer-extracted texture) features in differentiating radiation necrosis from recurrent brain tumors on routine MR imaging (gadolinium T1WI, T2WI, FLAIR).
  
  
  
  A retrospective study of brain tumor MR imaging performed 9 months (or later) post-radiochemotherapy was performed from 2 institutions. Fifty-eight patient studies were analyzed, consisting of a training (n = 43) cohort from one institution and an independent test (n = 15) cohort from another, with surgical histologic findings confirmed by an experienced neuropathologist at the respective institutions. Brain lesions on MR imaging were manually annotated by an expert neuroradiologist. A set of radiomic features was extracted for every lesion on each MR imaging sequence: gadolinium T1WI, T2WI, and FLAIR. Feature selection was used to identify the top 5 most discriminating features for every MR imaging sequence on the training cohort. These features were then evaluated on the test cohort by a support vector machine classifier. The classification performance was compared against diagnostic reads by 2 expert neuroradiologists who had access to the same MR imaging sequences (gadolinium T1WI, T2WI, and FLAIR) as the classifier.
  
  
  
  On the training cohort, the area under the receiver operating characteristic curve was highest for FLAIR with 0.79; 95% CI, 0.77-0.81 for primary (n = 22); and 0.79, 95% CI, 0.75-0.83 for metastatic subgroups (n = 21). Of the 15 studies in the holdout cohort, the support vector machine classifier identified 12 of 15 studies correctly, while neuroradiologist 1 diagnosed 7 of 15 and neuroradiologist 2 diagnosed 8 of 15 studies correctly, respectively.
  
  
  
  Our preliminary results suggest that radiomic features may provide complementary diagnostic information on routine MR imaging sequences that may improve the distinction of radiation necrosis from recurrence for both primary and metastatic brain tumors.
authors.affiliation: From the Department of Biomedical Engineering (P.T., P.P., G.S., A.M.), Case Western Reserve University, Cleveland, Ohio pallavi.tiwari@case.edu.
authors.forename: P
authors.identifier: 0000-0001-9477-4856
authors.initials: P
authors.lastname: Tiwari
authors.affiliation: From the Department of Biomedical Engineering (P.T., P.P., G.S., A.M.), Case Western Reserve University, Cleveland, Ohio.
authors.forename: P
authors.identifier: 0000-0002-3068-3573
authors.initials: P
authors.lastname: Prasanna
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: L
authors.identifier: 0000-0001-7996-6155
authors.initials: L
authors.lastname: Wolansky
authors.affiliation: University of Texas Southwestern Medical Center (M.P., K.J.H.), Dallas, Texas.
authors.forename: M
authors.identifier: 0000-0002-4645-1638
authors.initials: M
authors.lastname: Pinho
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: M
authors.identifier: 0000-0002-9678-5521
authors.initials: M
authors.lastname: Cohen
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: A P
authors.identifier: 0000-0001-6846-2074
authors.initials: AP
authors.lastname: Nayate
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: A
authors.identifier: 0000-0001-5345-6763
authors.initials: A
authors.lastname: Gupta
authors.affiliation: From the Department of Biomedical Engineering (P.T., P.P., G.S., A.M.), Case Western Reserve University, Cleveland, Ohio.
authors.forename: G
authors.identifier: 0000-0003-4291-9026
authors.initials: G
authors.lastname: Singh
authors.affiliation: University of Texas Southwestern Medical Center (M.P., K.J.H.), Dallas, Texas.
authors.forename: K J
authors.identifier: 0000-0002-9910-9828
authors.initials: KJ
authors.lastname: Hatanpaa
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: A
authors.identifier: 0000-0001-9607-5063
authors.initials: A
authors.lastname: Sloan
authors.affiliation: University Hospitals Case Medical Center (A.P.N., A.G., L.W., M.C., A.S., L.R.), Cleveland, Ohio.
authors.forename: L
authors.identifier: 0000-0003-0942-2691
authors.initials: L
authors.lastname: Rogers
authors.affiliation: From the Department of Biomedical Engineering (P.T., P.P., G.S., A.M.), Case Western Reserve University, Cleveland, Ohio.
authors.forename: A
authors.identifier: 0000-0002-5741-0399
authors.initials: A
authors.lastname: Madabhushi
mesh_terms: D019540:Area Under Curve; D001921:Brain / Q000000981:diagnostic imaging / Q000528:radiation effects*; D001932:Brain Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D008279:Magnetic Resonance Imaging / Q000379:methods; D008297:Male; D008875:Middle Aged; D012372:ROC Curve; D011832:Radiation Injuries / Q000000981:diagnostic imaging* / Q000473:pathology; D011878:Radiotherapy / Q000009:adverse effects*; D012189:Retrospective Studies; D060388:Support Vector Machine