title: Associating spatial diversity features of radiologically defined tumor habitats with epidermal growth factor receptor driver status and 12-month survival in glioblastoma: methods and preliminary investigation.
abstract: We analyzed the spatial diversity of tumor habitats, regions with distinctly different intensity characteristics of a tumor, using various measurements of habitat diversity within tumor regions. These features were then used for investigating the association with a 12-month survival status in glioblastoma (GBM) patients and for the identification of epidermal growth factor receptor (EGFR)-driven tumors. T1 postcontrast and T2 fluid attenuated inversion recovery images from 65 GBM patients were analyzed in this study. A total of 36 spatial diversity features were obtained based on pixel abundances within regions of interest. Performance in both the classification tasks was assessed using receiver operating characteristic (ROC) analysis. For association with 12-month overall survival, area under the ROC curve was 0.74 with confidence intervals [0.630 to 0.858]. The sensitivity and specificity at the optimal operating point ([Formula: see text]) on the ROC were 0.59 and 0.75, respectively. For the identification of EGFR-driven tumors, the area under the ROC curve (AUC) was 0.85 with confidence intervals [0.750 to 0.945]. The sensitivity and specificity at the optimal operating point ([Formula: see text]) on the ROC were 0.76 and 0.83, respectively. Our findings suggest that these spatial habitat diversity features are associated with these clinical characteristics and could be a useful prognostic tool for magnetic resonance imaging studies of patients with GBM.
authors.affiliation: University of Texas , MD Anderson Cancer Center, Department of Bioinformatics and Computational Biology, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
authors.forename: Joonsang
authors.initials: J
authors.lastname: Lee
authors.affiliation: University of Texas , MD Anderson Cancer Center, Department of Bioinformatics and Computational Biology, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
authors.forename: Shivali
authors.initials: S
authors.lastname: Narang
authors.affiliation: University of Texas , MD Anderson Cancer Center, Department of Neurosurgery, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
authors.forename: Juan J
authors.initials: JJ
authors.lastname: Martinez
authors.affiliation: University of Texas , MD Anderson Cancer Center, Department of Neurosurgery, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
authors.forename: Ganesh
authors.initials: G
authors.lastname: Rao
authors.affiliation: University of Texas , MD Anderson Cancer Center, Department of Bioinformatics and Computational Biology, 1515 Holcombe Boulevard, Houston, Texas 77030, United States.
authors.forename: Arvind
authors.initials: A
authors.lastname: Rao
keywords: glioblastoma; imaging-genomics; radiomics; spatial diversity; tumor habitats
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