Knott, KD;
Fernandes, JL;
Moon, JC;
(2019)
Automated Quantitative Stress Perfusion in a Clinical Routine.
Magnetic Resonance Imaging Clinics of North America
, 27
(3)
pp. 507-520.
10.1016/j.mric.2019.04.003.
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Abstract
Cardiovascular magnetic resonance (CMR) perfusion imaging is a robust noninvasive technique to evaluate ischemia in patients with coronary artery disease (CAD). Although qualitative and semiquantitative methods have shown that CMR has high accuracy in diagnosing flow-obstructing lesions in CAD, quantitative ischemic burden is an important variable used in clinical practice for treatment decisions. Quantitative CMR perfusion techniques have evolved significantly, with accuracy comparable with both PET and microsphere evaluation. Routine clinical use of these quantitative techniques has been facilitated by the introduction of automated methods that accelerate the work flow and rapidly generate pixel-based myocardial blood flow maps.
| Type: | Article |
|---|---|
| Title: | Automated Quantitative Stress Perfusion in a Clinical Routine |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1016/j.mric.2019.04.003 |
| Publisher version: | http://doi.org/10.1016/j.mric.2019.04.003 |
| Language: | English |
| Additional information: | This version is the author accepted manuscript. For information on re-use, please refer to the publisher’s terms and conditions. |
| Keywords: | Myocardial perfusion, Stress, Ischemia, MR imaging, Cardiovascular magnetic resonance, Quantification, Automation |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > Institute of Cardiovascular Science > Clinical Science |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10076830 |
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