Author + information
- Tushar Kotecha, MBChBa,b,∗,
- Ana Martinez-Naharro, MDb,c,∗,
- Michele Boldrini, MDc,
- Daniel Knight, MDa,b,
- Philip Hawkins, PhDb,c,
- Sundeep Kalra, PhDb,
- Deven Patel, MDb,
- Gerry Coghlan, MDb,
- James Moon, MDa,d,
- Sven Plein, PhDe,
- Tim Lockie, PhDb,
- Roby Rakhit, MDa,b,
- Niket Patel, MDa,b,
- Hui Xue, PhDf,
- Peter Kellman, PhDf and
- Marianna Fontana, PhDb,c,∗ ()
- aInstitute of Cardiovascular Science, University College London, United Kingdom
- bRoyal Free Hospital, London, United Kingdom
- cDivision of Medicine, University College London, United Kingdom
- dBarts Heart Centre, London, United Kingdom
- eInstitute of Cardiovascular and Metabolic Medicine, University of Leeds, United Kingdom
- fNational Heart, Lung, and Blood Institute, National Institute of Health, Bethesda, Maryland
- ↵∗Address for correspondence:
Dr. Marianna Fontana, Department of Cardiovascular Magnetic Resonance, Royal Free Hospital, Rowland Hill Street, London NW3 2PF, United Kingdom.
Objectives The study sought to assess the performance of cardiovascular magnetic resonance (CMR) myocardial perfusion mapping against invasive coronary physiology reference standards for detecting coronary artery disease (CAD, defined by fractional flow reserve [FFR] ≤0.80), microvascular dysfunction (MVD) (defined by index of microcirculatory resistance [IMR] ≥25) and the ability to differentiate between the two.
Background Differentiation of epicardial (CAD) and MVD in patients with stable angina remains challenging. Automated in-line CMR perfusion mapping enables quantification of myocardial blood flow (MBF) to be performed rapidly within a clinical workflow.
Methods Fifty patients with stable angina and 15 healthy volunteers underwent adenosine stress CMR at 1.5T with quantification of MBF and myocardial perfusion reserve (MPR). FFR and IMR were measured in 101 coronary arteries during subsequent angiography.
Results Twenty-seven patients had obstructive CAD and 23 had nonobstructed arteries (7 normal IMR, 16 abnormal IMR). FFR positive (epicardial stenosis) areas had significantly lower stress MBF (1.47 ± 0.48 ml/g/min) and MPR (1.75 ± 0.60) than FFR-negative IMR-positive (MVD) areas (stress MBF: 2.10 ± 0.35 ml/g/min; MPR: 2.41 ± 0.79) and normal areas (stress MBF: 2.47 ± 0.50 ml/g/min; MPR: 2.94 ± 0.81). Stress MBF ≤1.94 ml/g/min accurately detected obstructive CAD on a regional basis (area under the curve: 0.90; p < 0.001). In patients without regional perfusion defects, global stress MBF <1.82 ml/g/min accurately discriminated between obstructive 3-vessel disease and MVD (area under the curve: 0.94; p < 0.001).
Conclusions This novel automated pixel-wise perfusion mapping technique can be used to detect physiologically significant CAD defined by FFR, MVD defined by IMR, and to differentiate MVD from multivessel coronary disease. A CMR-based diagnostic algorithm using perfusion mapping for detection of epicardial disease and MVD warrants further clinical validation.
- cardiovascular magnetic resonance
- coronary artery disease
- index of microcirculatory resistance
- microvascular dysfunction
- myocardial blood flow
↵∗ Drs. Kotecha and Martinez-Naharro contributed equally to this work.
This study was supported by the National Amyloidosis Centre, University College London, and the National Institute for Health Research University College London Hospitals Biomedical Research Centre. All authors have reported that they have no relationships relevant to the contents of this paper to disclose.
- Received October 8, 2018.
- Revision received December 3, 2018.
- Accepted December 6, 2018.
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