APA
Click to copy
Bell, L., Semmineh, N., An, H., Eldeniz, C., Wahl, R., Schmainda, K., … Quarles, C. (2020). 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. Tomography.
Chicago/Turabian
Click to copy
Bell, L., N. Semmineh, H. An, C. Eldeniz, R. Wahl, K. Schmainda, M. Prah, et al. “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.” Tomography (2020).
MLA
Click to copy
Bell, L., et al. “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.” Tomography, 2020.
BibTeX Click to copy
@article{l2020a,
title = {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},
journal = {Tomography},
author = {Bell, L. and Semmineh, N. and An, H. and Eldeniz, C. and Wahl, R. and Schmainda, K. and Prah, M. and Erickson, B. and Korfiatis, P. and Wu, Chengyue and Sorace, A. and Yankeelov, T. and Rutledge, N. and Chenevert, T. and Malyarenko, D. and Liu, Yichu and Brenner, A. and Hu, Leland S. and Zhou, Yuxiang and Boxerman, J. and Yen, Yi-Fen and Kalpathy-Cramer, Jayashree and Beers, Andrew L and Muzi, M. and Madhuranthakam, A. and Pinho, M. and Johnson, Brian and Quarles, C.}
}
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.
