Ultrafast Brain MRI: Clinical Deployment and Comparison to Conventional Brain MRI at 3T

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J Neuroimaging
2016 Sep
26
5
503-10
10.1111/jon.12365
Epub Date: 
Tuesday, June 7, 2016
Journal Articles
PubMed ID: 
27273370

BACKGROUND AND PURPOSE: To compare an ultrafast brain magnetic resonance imaging (MRI) protocol to the conventional protocol in motion-prone inpatient clinical settings.
METHODS: This retrospective study was HIPAA compliant and approved by the Institutional Review Board with waived inform consent. Fifty-nine inpatients (30 males, 29 females; mean age 55.1, range 23-93 years)who underwent 3-Tesla brain MRI using ultrafast and conventional protocols, both including five sequences, were included in the study. The total scan time for five ultrafast sequences was 4 minutes 59 seconds. The ideal conventional acquisition time was 10 minutes 32 seconds but the actual acquisition took 15-20 minutes. The average scan times for ultrafast localizers, T1-weighted, T2-weighted, fluid-attenuated inversion recovery (FLAIR), diffusion-weighted, T2*-weighted sequences were 14, 41, 62, 96, 80, 6 seconds, respectively. Two blinded neuroradiologists independently assessed three aspects: (1) image quality, (2) gray-white matter (GM-WM) differentiation, and (3) diagnostic concordance for the detection of six clinically relevant imaging findings. Wilcoxon signed-rank test was used to compare image quality and GM-WM scores. Interobserver reproducibility was calculated.
RESULTS: The ultrafast T1-weighted sequence demonstrated significantly better image quality (P = .005) and GM-WM differentiation (P 85%) between both protocols for the detection of mass-like lesion, hemorrhage, diffusion restriction, WM FLAIR hyperintensities, subarachnoid FLAIR hyperintensities, and hydrocephalus.
CONCLUSIONS: The ultrafast protocol achieved at least comparable image quality and high diagnostic concordance compared to the conventional protocol. This fast protocol can be a viable option to replace the conventional protocol in motion-prone inpatient clinical settings.

Year: 
2016