Evaluating the Use of rCBV as a Tumor Grade and Treatment Response Classifier Across NCI Quantitative Imaging Network Sites: Part II of the DSC-MRI Digital Reference Object (DRO) Challenge
Year: 2020
Type: article
Abstract: We have previously characterized the reproducibility of brain tumor relative cerebral blood volume (rCBV) using a dynamic susceptibility contrast magnetic resonance imaging digital reference object across 12 sites using a range of imaging protocols and software platforms. As expected, reproducibility was highest when imaging protocols and software were consistent, but decreased when they were variable. Our goal in this study was to determine the impact of rCBV reproducibility for tumor grade and treatment response classification. We found that varying imaging protocols and software platforms produced a range of optimal thresholds for both tumor grading and treatment response, but the performance of these thresholds was similar. These findings further underscore the importance of standardizing acquisition and analysis protocols across sites and software benchmarking.
Source: Tomography
Authors: Laura C. Bell, Natenael Semmineh, Hongyu An, Cihat Eldeniz, Richard Wahl, Kathleen M. Schmainda, Melissa A. Prah, Bradley J. Erickson, Panagiotis Korfiatis, Chengyue Wu, Anna G. Sorace, Thomas E. Yankeelov, Neal Rutledge, Thomas L. Chenevert, Dariya Malyarenko, Yichu Liu, Andrew Brenner, Leland S. Hu, Yuxiang Zhou, Jerrold L. Boxerman, Yi-Fen Yen, Jayashree Kalpathy-Cramer, Andrew L. Beers, Mark Muzi, Ananth J. Madhuranthakam, Marco Pinho, Brian Johnson, C. Chad Quarles
Institutions: Barrow Neurological Institute, Washington University in St. Louis, Medical College of Wisconsin, Mayo Clinic, The University of Texas at Austin, University of Alabama at Birmingham, University of Michigan, The University of Texas at San Antonio Health Science Center, Mayo Clinic in Arizona, Brown University, Rhode Island Hospital, Massachusetts General Hospital, Athinoula A. Martinos Center for Biomedical Imaging, University of Washington, The University of Texas Southwestern Medical Center
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $2,896
OpenAlex ID: W3033746703