Automatic and Reproducible Positioning of Phase-Contrast MRI for the Quantification of Global Cerebral Blood Flow

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Automatic and Reproducible Positioning of Phase-Contrast MRI for the Quantification of Global Cerebral Blood Flow

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Title: Automatic and Reproducible Positioning of Phase-Contrast MRI for the Quantification of Global Cerebral Blood Flow
Author(s):
Liu, Peiying;
Lu, Hanzhang;
Filbey, Francesca M.;
Pinkham, Amy E.;
McAdams, Carrie J.;
Adinoff, Bryon;
Daliparthi, Vamsi;
Cao, Yan
Format: Text
Item Type: Article
Keywords: Show Keywords
Abstract: Phase-Contrast MRI (PC-MRI) is a noninvasive technique to measure blood flow. In particular, global but highly quantitative cerebral blood flow (CBF) measurement using PC-MRI complements several other CBF mapping methods such as arterial spin labeling and dynamic susceptibility contrast MRI by providing a calibration factor. The ability to estimate blood supply in physiological units also lays a foundation for assessment of brain metabolic rate. However, a major obstacle before wider applications of this method is that the slice positioning of the scan, ideally placed perpendicular to the feeding arteries, requires considerable expertise and can present a burden to the operator. In the present work, we proposed that the majority of PC-MRI scans can be positioned using an automatic algorithm, leaving only a small fraction of arteries requiring manual positioning. We implemented and evaluated an algorithm for this purpose based on feature extraction of a survey angiogram, which is of minimal operator dependence. In a comparative test-retest study with 7 subjects, the blood flow measurement using this algorithm showed an inter-session coefficient of variation (CoV) of 4.07 ± 3.03%. The Bland-Altman method showed that the automatic method differs from the manual method by between -8% and 11%, for 95% of the CBF measurements. This is comparable to the variance in CBF measurement using manually-positioned PC MRI alone. In a further application of this algorithm to 157 consecutive subjects from typical clinical cohorts, the algorithm provided successful positioning in 89.7% of the arteries. In 79.6% of the subjects, all four arteries could be planned using the algorithm. Chi-square tests of independence showed that the success rate was not dependent on the age or gender, but the patients showed a trend of lower success rate (p = 0.14) compared to healthy controls. In conclusion, this automatic positioning algorithm could improve the application of PC-MRI in CBF quantification.
Publisher: Public Library of Science
ISSN: 1932-6203
Persistent Link: http://hdl.handle.net/10735.1/4089
http://dx.doi.org/10.1007/JHEP07(2015)162
Terms of Use: CC-BY 4.0 (Attribution)
Sponsors: US National Institutes of Health (R01 MH084021; R01 NS067015; R21 AG034318; R01 AG042753; R21 NS078656; R01 DA023203). US National Science Foundation (DMS-0914910).

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CC-BY 4.0 (Attribution) Except where otherwise noted, this item's license is described as CC-BY 4.0 (Attribution)