Estimating Flow Direction of Circle of Willis Using Dynamic Arterial Spin Labeling Magnetic Resonance Angiography.

BACKGROUND AND PURPOSE: The Circle of Willis (COW) is a crucial mechanism for cerebral collateral circulation. This proof-ofconcept study aims to develop and assess an analysis method to characterize the hemodynamics of the arterial segments in COW using arterial spin labeling (ASL) based non-contrast enhanced dynamic magnetic resonance angiography (dMRA). MATERIALS AND METHODS: The developed analysis method uses a graph model, bootstrap strategy, and ensemble learning methodologies to determine the time-curve shift from ASL dMRA to estimate the flow direction within the COW. The performance of the method was assessed on 52 subjects, using the flow direction, either antegrade or retrograde, derived from 3D phase contrast (PC) MRI as the reference. RESULTS: A total of 340 arterial segments in COW were evaluated, among which 30 (8.8%) had retrograde flow according to 3D PC. The ASL dMRA-based flow direction estimation has an accuracy, sensitivity, and specificity of 95.47%, 80%, and 96.34%, respectively. CONCLUSIONS: Using ASL dMRA and the developed image analysis method to estimate the flow direction in COW is feasible. This study provides a new method to assess the hemodynamics of the COW, which could be useful for the diagnosis and study of cerebrovascular diseases. ABBREVIATIONS: COW = Circle of Willis; ASL = arterial spin labeling; dMRA =dynamic magnetic resonance angiography; PC = phase contrast.

Intra-examination agreement between multi-echo gradient echo and confounder-corrected chemical shift-encoded MR sequences for R2* estimation as a biomarker of liver iron content in patients with a wide range of T2*/R2* and proton density fat fraction values.

PURPOSE: To investigate the intra-examination agreement between multi-echo gradient echo (MEGE) and confounder-corrected chemical shift-encoded (CSE) sequences for liver T2*/R2* estimations in a wide range of T2*/R2* and proton density fat fraction (PDFF) values. Exploratorily, to search for the T2*/R2* value where the agreement line breaks and examine differences between regions of low and high agreement. METHODS: Consecutive patients at risk for liver iron overload who underwent MEGE and CSE sequences within the same exam at 1.5 T were retrospectively selected. Regions of interest were drawn in the right and one in the left liver lobes on post-processed images for R2*(sec-1) and PDFF (%) estimation. Agreement between MEGE-R2* and CSE-R2* was evaluated using intra-class correlation coefficient (ICC) and Bland-Altman analysis. 95% confidence intervals (CI) were computed. Segment-and-regression analysis was performed to find the point where the agreement between sequences is interrupted. Regions of low and high agreement were examined using tree-based partitioning analyses. RESULTS: 49 patients were included. Mean MEGE-R2* was 94.2 s-1 (range: 31.0-737.1) and mean CSE-R2* 87.7 (29.7-748.1). Mean CSE-PDFF was 9.12% (0.1-43.3). Agreement was strong for R2* estimations (ICC: 0.992,95%CI 0.987,0.996), but the relation was nonlinear and possibly heteroskedastic. Lower agreement occurred when MEGE-R2* > 235 s-1, with MEGE-R2* values consistently lower than CSE-R2*. Higher agreement was observed when PDFF < 14%. CONCLUSION: MEGE-R2* and CSE-R2* strongly agree, though at higher iron content, MEGE-R2* is consistently lower than CSE-R2*. In this preliminary dataset, a breaking point for agreement was found at R2* > 235. Lower agreement was observed in patients with moderate to severe liver steatosis.