Detecting pseudo versus true progression of glioblastoma via accurate quantitative DCE-MRI using point-of-care portable perfusion phantoms: a pilot study
Following P4-based error correction, a quantitative DCE-MRI parameter, <i>K<sup>trans</sup></i> , demonstrated 100% accuracy in discriminating between pseudo and true progression when TM or ETM were employed.
Authors
- Daniel P. Barboriak (ORCID: https://orcid.org/0000-0002-2536-6266)
- Chetana Krishnan (ORCID: https://orcid.org/0009-0003-1409-8723)
- Kristen Owen Riley (ORCID: https://orcid.org/0000-0001-5895-6855)
- Wei Huang (ORCID: https://orcid.org/0000-0001-8279-6345)
- Burt Nabors (ORCID: https://orcid.org/0000-0001-5926-2230)
- Houman Sotoudeh (ORCID: https://orcid.org/0000-0002-5510-7062)
- John B. Fiveash (ORCID: https://orcid.org/0000-0002-1129-2884)
- Harrison Kim (ORCID: https://orcid.org/0000-0002-9126-1964)
- M. Holland
Institutions
- Duke University (US)
- University of Alabama at Birmingham (US)
Publication Details
- Journal
- Quantitative Imaging in Medicine and Surgery
- Published
- 2025-04-30
- DOI
- https://doi.org/10.21037/qims-2024-2566
- Citations
- 2
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 2.72