Title | Temporal clustering, tissue composition, and total variation for mapping oxygen extraction fraction using QSM and quantitative BOLD. |
Publication Type | Journal Article |
Year of Publication | 2021 |
Authors | Cho J, Spincemaille P, Nguyen TD, Gupta A, Wang Y |
Journal | Magn Reson Med |
Volume | 86 |
Issue | 5 |
Pagination | 2635-2646 |
Date Published | 2021 11 |
ISSN | 1522-2594 |
Keywords | Brain, Cerebrovascular Circulation, Cluster Analysis, Gray Matter, Humans, Magnetic Resonance Imaging, Oxygen, Oxygen Consumption |
Abstract | PURPOSE: To improve the accuracy of quantitative susceptibility mapping plus quantitative blood oxygen level-dependent magnitude (QSM+qBOLD or QQ) based mapping of oxygen extraction fraction (OEF) and cerebral metabolic rate of oxygen (CMRO ) using temporal clustering, tissue composition, and total variation (CCTV). METHODS: Three-dimensional multi-echo gradient echo and arterial spin labeling images were acquired from 11 healthy subjects and 33 ischemic stroke patients. Diffusion-weighted imaging (DWI) was also obtained from patients. The CCTV mapping was developed for incorporating tissue-type information into clustering of the previous cluster analysis of time evolution (CAT) and applying total variation (TV). The QQ-based OEF and CMRO were reconstructed with CAT, CAT+TV (CATV), and the proposed CCTV, and results were compared using region-of-interest analysis, Kruskal-Wallis test, and post hoc Wilcoxson rank sum test. RESULTS: In simulation, CCTV provided more accurate and precise OEF than CAT or CATV. In healthy subjects, QQ-based OEF was less noisy and more uniform with CCTV than CAT. In subacute stroke patients, OEF with CCTV had a greater contrast-to-noise ratio between DWI-defined lesions and the unaffected contralateral side than with CAT or CATV: 1.9 ± 1.3 versus 1.1 ± 0.7 (P = .01) versus 0.7 ± 0.5 (P < .001). CONCLUSION: The CCTV mapping significantly improves the robustness of QQ-based OEF against noise. |
DOI | 10.1002/mrm.28875 |
Alternate Journal | Magn Reson Med |
PubMed ID | 34110656 |
Grant List | R01NS090464 / NH / NIH HHS / United States R01NS095562 / NH / NIH HHS / United States R21AG067466 / NH / NIH HHS / United States S10OD021782 / NH / NIH HHS / United States R01NS105144 / NH / NIH HHS / United States K99NS123229 / NH / NIH HHS / United States R01NS090464 / NH / NIH HHS / United States R01NS095562 / NH / NIH HHS / United States R21AG067466 / NH / NIH HHS / United States S10OD021782 / NH / NIH HHS / United States R01NS105144 / NH / NIH HHS / United States K99NS123229 / NH / NIH HHS / United States |
Related Institute:
MRI Research Institute (MRIRI)