Initial investigation of free-breathing 3D whole-heart stress myocardial perfusion MRI
Author(s) -
Merlin J. Fair,
Peter Gatehouse,
Eliana Reyes,
Ganesh Adluru,
Jason Mendes,
Tina Khan,
Ranil de Silva,
Rick Wage,
Edward DiBella,
David Firmin
Publication year - 2020
Publication title -
global cardiology science and practice
Language(s) - English
Resource type - Journals
ISSN - 2305-7823
DOI - 10.21542/gcsp.2020.38
Subject(s) - medicine , perfusion , coronary artery disease , breathing , myocardial perfusion imaging , population , cardiology , radiology , nuclear medicine , anesthesia , environmental health
Objective: Myocardial first-pass perfusion imaging with MRI is well-established clinically. However, it is potentially weakened by limited myocardial coverage compared to nuclear medicine. Clinical evaluations of whole-heart MRI perfusion by 3D methods, while promising, have to date had the limit of breathhold requirements at stress. This work aims to develop a new free-breathing 3D myocardial perfusion method, and to test its performance in a small patient population. Methods: This work required tolerance to respiratory motion for stress investigations, and therefore employed a “stack-of-stars” hybrid Cartesian-radial MRI acquisition method. The MRI sequence was highly optimised for rapid acquisition and combined with a compressed sensing reconstruction. Stress and rest datasets were acquired in four healthy volunteers, and in six patients with coronary artery disease (CAD), which were compared against clinical reference information. Results: This free-breathing method produced datasets that appeared consistent with clinical reference data in detecting moderate-to-strong induced perfusion abnormalities. However, the majority of the mild defects identified clinically were not detected by the method, potentially due to the presence of transient myocardial artefacts present in the images. Discussion: The feasibility of detecting CAD using this 3D first-pass perfusion sequence during free-breathing is demonstrated. Good agreement on typical moderate-to-strong CAD cases is promising, however, questions still remain on the sensitivity of the technique to milder cases.
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