Literature DB >> 33107141

Highly accelerated aortic 4D flow MRI using compressed sensing: Performance at different acceleration factors in patients with aortic disease.

Ashitha Pathrose1, Liliana Ma1,2, Haben Berhane3, Michael B Scott1,2, Kelvin Chow1,4, Christoph Forman5, Ning Jin4, Ali Serhal1, Ryan Avery1, James Carr1,2, Michael Markl1,2.   

Abstract

PURPOSE: To systematically assess the feasibility and performance of a highly accelerated compressed sensing (CS) 4D flow MRI framework at three different acceleration factors (R) for the quantification of aortic flow dynamics and wall shear stress (WSS) in patients with aortic disease.
METHODS: Twenty patients with aortic disease (58 ± 15 y old; 19 M) underwent four 4D flow scans: one conventional (GRAPPA, R = 2) and three CS 4D flows with R = 5.7, 7.7, and 10.2. All scans were acquired with otherwise equivalent imaging parameters on a 1.5T scanner. Peak-systolic velocity (Vmax ), peak flow (Qmax ), and net flow (Qnet ) were quantified at the ascending aorta (AAo), arch, and descending aorta (DAo). WSS was calculated at six regions within the AAo and arch.
RESULTS: Mean scan times for the conventional and CS 4D flows with R = 5.7, 7.7, and 10.2 were 9:58 ± 2:58 min, 3:40 ± 1:19 min, 2:50 ± 0:56 min, and 2:05 ± 0:42 min, respectively. Vmax , Qmax , and Qnet were significantly underestimated by all CS protocols (underestimation ≤ -7%, -9%, and -10% by CS, R = 5.7, 7.7, and 10.2, respectively). WSS measurements showed the highest underestimation by all CS protocols (underestimation ≤ -9%, -12%, and -14% by CS, R = 5.7, 7.7, and 10.2).
CONCLUSIONS: Highly accelerated aortic CS 4D flow at R = 5.7, 7.7, and 10.2 showed moderate agreement with the conventional 4D flow, despite systematically underestimating various hemodynamic parameters. The shortened scan time may enable the clinical translation of CS 4D flow, although potential hemodynamic underestimation should be considered when interpreting the results.
© 2020 International Society for Magnetic Resonance in Medicine.

Entities:  

Keywords:  4D flow; aorta; cardiovascular; compressed sensing

Year:  2020        PMID: 33107141      PMCID: PMC7846046          DOI: 10.1002/mrm.28561

Source DB:  PubMed          Journal:  Magn Reson Med        ISSN: 0740-3194            Impact factor:   4.668


  45 in total

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