作者: Tyler C. Steed , Jeffrey M. Treiber , Kunal Patel , Valya Ramakrishnan , Alexander Merk
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摘要: // Tyler C. Steed 1 , Jeffrey M. Treiber Kunal Patel 1,2 Valya Ramakrishnan Alexander Merk 3 Amanda R. Smith Bob S. Carter Anders Dale 4,5 Lionel L. Chow and Clark Chen Center for Theoretical Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center, University California, San Diego, La Jolla, CA, USA 2 Weill-Cornell Medical College, New York Presbyterian Hospital, York, NY, Blood Diseases Institute, Cincinnati Children’s Hospital Cincinnati, OH, 4 Multimodal Imaging Laboratory, California 5 Department Radiology, Correspondence to: Chen, email: Keywords : glioblastoma, MR imaging, subventricular zone, subtypes, automatic tumor segmentation Received February 23, 2016 Accepted March 26, Published April 01, Abstract Introduction: The zone (SVZ) has been implicated in the pathogenesis glioblastoma. Whether molecular subtypes glioblastoma arise from unique niches brain relative to SVZ remains largely unknown. Here, we tested whether these occupy distinct regions cerebrum examined localization relation SVZ. Methods: Pre-operative images 217 patients Archive were segmented automatically into contrast enhancing (CE) volumes using Iterative Probabilistic Voxel Labeling (IPVL). maps location generated each subtype distances calculated centroid CE Glioblastomas that arose a Genetically Modified Murine Model (GEMM) model also analyzed with regard distance subtype. Results: Classical mesenchymal glioblastomas more diffusely distributed located farther In contrast, proneural neural likely be closer proximity Moreover, GFAP-CreER ; Pten loxP/loxP Trp53 Rb1 Rbl1 -/- GEMM where can spontaneously different cerebrum, tumors near ( p < 0.0001). Conclusions: Glioblastoma vary These findings harbor implications pertaining subtypes.