Assessment of arterial arrival times derived from multiple inversion time pulsed arterial spin labeling MRI.

Journal article

The purpose of this study was to establish a normal range for the arterial arrival time (AAT) in whole-brain pulsed arterial spin labeling (PASL) cerebral perfusion MRI. Healthy volunteers (N = 36, range: 20 to 35 years) provided informed consent to participate in this study. AAT was assessed in multiple brain regions, using three-dimensional gradient and spin echo (GRASE) pulsed arterial spin labeling at 3.0 T, and found to be 641 +/- 95, 804 +/- 91, 802 +/- 126, and 935 +/- 108 ms in the temporal, parietal, frontal, and occipital lobes, respectively. Mean gray matter AAT was found to be 694 +/- 89 ms for females (N = 15), which was significantly shorter than for men, 814 +/- 192 ms (N = 21; P < 0.0003), and significant after correcting for brain volume (P < 0.001). Significant AAT sex differences were also found using voxelwise permutation testing. An atlas of AAT values across the healthy brain is presented here and may be useful for future experiments that aim to quantify cerebral blood flow from ASL data, as well as for clinical comparisons where disease pathology may lead to altered AAT. Pulsed arterial spin labeling signals were simulated using an identical sampling scheme as the empiric study and revealed AAT can be estimated robustly when simulated arrival times are well beyond the normal range.

Authors: MacIntosh, B; Filippini, N; Chappell, M; Woolrich, M; Mackay, C

• Publication status: Published
• Journal: Magnetic resonance in medicine : official journal of the Society of Magnetic Resonance in Medicine / Society of Magnetic Resonance in Medicine
• Volume: 63
• Issue: 3
• Pages: 641-647
• Publication date: 2010-03-01
• DOI: 10.1002/mrm.22256
• EISSN: 1522-2594
• ISSN: 0740-3194
• Language: English
• Keywords: Image Enhancement; Reproducibility of Results; Cerebrovascular Circulation; Sensitivity and Specificity; Spin Labels; Magnetic Resonance Angiography; Adult; Cerebral Arteries; Humans; Brain; Blood Flow Velocity; Image Interpretation, Computer-Assisted; Young Adult; Female; Male; Algorithms