Jared H Hara1, Ashley Wu1, Javier E Villanueva-Meyer2, Gilmer Valdes1, Vikas Daggubati1, Sabine Mueller3, Timothy D Solberg1, Steve E Braunstein1, Olivier Morin1, David R Raleigh4. 1. Department of Radiation Oncology, University of California, San Francisco, San Francisco, California. 2. Department of Radiology, University of California, San Francisco, San Francisco, California. 3. Department of Neurological Surgery, University of California, San Francisco, San Francisco, California. 4. Department of Radiation Oncology, University of California, San Francisco, San Francisco, California; Department of Neurological Surgery, University of California, San Francisco, San Francisco, California. Electronic address: david.raleigh@ucsf.edu.
Abstract
PURPOSE: To investigate the prognostic utility of quantitative 3-dimensional magnetic resonance imaging radiomic analysis for primary pediatric embryonal brain tumors. METHODS AND MATERIALS: Thirty-four pediatric patients with embryonal brain tumor with concurrent preoperative T1-weighted postcontrast (T1PG) and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance images were identified from an institutional database. The median follow-up period was 5.2 years. Radiomic features were extracted from axial T1PG and FLAIR contours using MATLAB, and 15 features were selected for analysis based on qualitative radiographic features with prognostic significance for pediatric embryonal brain tumors. Logistic regression, linear regression, receiver operating characteristic curves, the Harrell C index, and the Somer D index were used to test the relationships between radiomic features and demographic variables, as well as clinical outcomes. RESULTS: Pediatric embryonal brain tumors in older patients had an increased normalized mean tumor intensity (P = .05, T1PG), decreased tumor volume (P = .02, T1PG), and increased markers of heterogeneity (P ≤ .01, T1PG and FLAIR) relative to those in younger patients. We identified 10 quantitative radiomic features that delineated medulloblastoma, pineoblastoma, and supratentorial primitive neuroectodermal tumor, including size and heterogeneity (P ≤ .05, T1PG and FLAIR). Decreased markers of tumor heterogeneity were predictive of neuraxis metastases and trended toward significance (P = .1, FLAIR). Tumors with an increased size (area under the curve = 0.7, FLAIR) and decreased heterogeneity (area under the curve = 0.7, FLAIR) at diagnosis were more likely to recur. CONCLUSIONS: Quantitative radiomic features are associated with pediatric embryonal brain tumor patient age, histology, neuraxis metastases, and recurrence. These data suggest that quantitative 3-dimensional magnetic resonance imaging radiomic analysis has the potential to identify radiomic risk features for pediatric patients with embryonal brain tumors. Published by Elsevier Inc.
PURPOSE: To investigate the prognostic utility of quantitative 3-dimensional magnetic resonance imaging radiomic analysis for primary pediatric embryonal brain tumors. METHODS AND MATERIALS: Thirty-four pediatric patients with embryonal brain tumor with concurrent preoperative T1-weighted postcontrast (T1PG) and T2-weighted fluid-attenuated inversion recovery (FLAIR) magnetic resonance images were identified from an institutional database. The median follow-up period was 5.2 years. Radiomic features were extracted from axial T1PG and FLAIR contours using MATLAB, and 15 features were selected for analysis based on qualitative radiographic features with prognostic significance for pediatric embryonal brain tumors. Logistic regression, linear regression, receiver operating characteristic curves, the Harrell C index, and the Somer D index were used to test the relationships between radiomic features and demographic variables, as well as clinical outcomes. RESULTS:Pediatric embryonal brain tumors in older patients had an increased normalized mean tumor intensity (P = .05, T1PG), decreased tumor volume (P = .02, T1PG), and increased markers of heterogeneity (P ≤ .01, T1PG and FLAIR) relative to those in younger patients. We identified 10 quantitative radiomic features that delineated medulloblastoma, pineoblastoma, and supratentorial primitive neuroectodermal tumor, including size and heterogeneity (P ≤ .05, T1PG and FLAIR). Decreased markers of tumor heterogeneity were predictive of neuraxis metastases and trended toward significance (P = .1, FLAIR). Tumors with an increased size (area under the curve = 0.7, FLAIR) and decreased heterogeneity (area under the curve = 0.7, FLAIR) at diagnosis were more likely to recur. CONCLUSIONS: Quantitative radiomic features are associated with pediatric embryonal brain tumorpatient age, histology, neuraxis metastases, and recurrence. These data suggest that quantitative 3-dimensional magnetic resonance imaging radiomic analysis has the potential to identify radiomic risk features for pediatric patients with embryonal brain tumors. Published by Elsevier Inc.
Authors: Olivier Morin; William C Chen; Farshad Nassiri; Matthew Susko; Stephen T Magill; Harish N Vasudevan; Ashley Wu; Martin Vallières; Efstathios D Gennatas; Gilmer Valdes; Melike Pekmezci; Paula Alcaide-Leon; Abrar Choudhury; Yannet Interian; Siavash Mortezavi; Kerem Turgutlu; Nancy Ann Oberheim Bush; Timothy D Solberg; Steve E Braunstein; Penny K Sneed; Arie Perry; Gelareh Zadeh; Michael W McDermott; Javier E Villanueva-Meyer; David R Raleigh Journal: Neurooncol Adv Date: 2019-08-28