Blood oxygen-level dependent functional assessment of cerebrovascular reactivity: Feasibility for intraoperative 3 Tesla MRI.
Saved in:
| Title: | Blood oxygen-level dependent functional assessment of cerebrovascular reactivity: Feasibility for intraoperative 3 Tesla MRI. |
|---|---|
| Authors: | Fierstra, Jorn1 jorn.fierstra@usz.ch, Burkhardt, Jan‐Karl1, van Niftrik, Christiaan Hendrik Bas1, Piccirelli, Marco2, Pangalu, Athina2, Kocian, Roman3, Neidert, Marian Christoph1, Valavanis, Antonios2, Regli, Luca1, Bozinov, Oliver1 |
| Source: | Magnetic Resonance in Medicine. Feb2017, Vol. 77 Issue 2, p806-813. 8p. |
| Abstract: | Purpose To assess the feasibility of functional blood oxygen-level dependent (BOLD) MRI to evaluate intraoperative cerebrovascular reactivity (CVR) at 3 Tesla field strength. Methods Ten consecutive neurosurgical subjects scheduled for a clinical intraoperative MRI examination were enrolled in this study. In addition to the clinical protocol a BOLD sequence was implemented with three cycles of 44 s apnea to calculate CVR values on a voxel-by-voxel basis throughout the brain. The CVR range was then color-coded and superimposed on an anatomical volume to create high spatial resolution CVR maps. Results Ten subjects (mean age 34.8 ± 13.4; 2 females) uneventfully underwent the intraoperative BOLD protocol, with no complications occurring. Whole-brain CVR for all subjects was (mean ± SD) 0.69 ± 0.42, whereas CVR was markedly higher for tumor subjects as compared to vascular subjects, 0.81 ± 0.44 versus 0.33 ± 0.10, respectively. Furthermore, color-coded functional maps could be robustly interpreted for a whole-brain assessment of CVR. Conclusion We demonstrate that intraoperative BOLD MRI is feasible in creating functional maps to assess cerebrovascular reactivity throughout the brain in subjects undergoing a neurosurgical procedure. Magn Reson Med 77:806-813, 2017. © 2016 International Society for Magnetic Resonance in Medicine [ABSTRACT FROM AUTHOR] |
| Copyright of Magnetic Resonance in Medicine is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.) | |
| Database: | Engineering Source |
Be the first to leave a comment!
