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

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. BoxermanYi Fen Yen, Jayashree Kalpathy-Cramer, Andrew L. Beers, Mark Muzi, Ananth J. Madhuranthakam, Marco Pinho, Brian Johnson, C. Chad Quarles

Research output: Contribution to journalArticle

1 Scopus citations

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.

Original languageEnglish (US)
Pages (from-to)203-208
Number of pages6
JournalTomography (Ann Arbor, Mich.)
Volume6
Issue number2
DOIs
StatePublished - Jun 2020

Keywords

  • DSC-MRI
  • Digital reference object
  • Multisite consistency
  • Relative cerebral blood volume
  • Standardization
  • Treatment response
  • Tumor grading

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging

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    Bell, L. C., Semmineh, N., An, H., Eldeniz, C., Wahl, R., Schmainda, K. M., Prah, M. A., Erickson, B. J., Korfiatis, P., Wu, C., Sorace, A. G., Yankeelov, T. E., Rutledge, N., Chenevert, T. L., Malyarenko, D., Liu, Y., Brenner, A., Hu, L. S., Zhou, Y., ... Quarles, C. 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 (Ann Arbor, Mich.), 6(2), 203-208. https://doi.org/10.18383/j.tom.2020.00012