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

Peiying Liu,Carrie J Mcadams,Vamsi Daliparthi,Amy E Pinkham,Yan Cao,Francesca M Filbey,Bryon Adinoff,Hanzhang Lu,Allan Siegel

doi:10.1371/journal.pone.0095721

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 . The Bland-Altman method showed that the automatic method differs from the manual method by between and , for 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.

Highlights

Phase-Contrast MRI (PC-MRI) is a noninvasive technique to visualize blood vessels and measure blood flow velocity
The knowledge of cerebral blood flow (CBF), combined with quantitative evaluation of cerebral arterial and venous oxygenation, provides direct assessment of a highly desirable index, cerebral metabolic rate of oxygen (CMRO2) [10,11,12,13,14,15]. It can be used for the calibration of other qualitative CBF methods such as Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) MRI, in which quantification is traditionally confounded by factors such as arterial input function or labeling efficiency [5,6]
The comparative test-retest study showed that the PC-MRI measured blood flow using the automatic positioning algorithm is precise and consistent with that measured with manual positioning by an experienced operator (p~0:34)

Summary

Introduction

Phase-Contrast MRI (PC-MRI) is a noninvasive technique to visualize blood vessels and measure blood flow velocity. The knowledge of CBF, combined with quantitative evaluation of cerebral arterial and venous oxygenation, provides direct assessment of a highly desirable index, cerebral metabolic rate of oxygen (CMRO2) [10,11,12,13,14,15]. It can be used for the calibration of other qualitative CBF methods such as Dynamic Susceptibility Contrast (DSC) and Arterial Spin Labeling (ASL) MRI, in which quantification is traditionally confounded by factors such as arterial input function or labeling efficiency [5,6]. One can acquire a relative PET CBF map without arterial sampling and utilizes global CBF measured from PC-MRI to obtain a PET-MR ‘‘hybrid’’ CBF map that is both quantitative and spatially resolved

Objectives

Methods

Results

Discussion

Conclusion