Title |
Diagnostic and prognostic value of cardiovascular magnetic resonance in non-ischaemic cardiomyopathies
|
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Published in |
Critical Reviews in Diagnostic Imaging, August 2012
|
DOI | 10.1186/1532-429x-14-54 |
Pubmed ID | |
Authors |
Chirine Parsai, Rory O’Hanlon, Sanjay K Prasad, Raad H Mohiaddin |
Abstract |
Cardiovascular Magnetic Resonance (CMR) is recognised as a valuable clinical tool which in a single scan setting can assess ventricular volumes and function, myocardial fibrosis, iron loading, flow quantification, tissue characterisation and myocardial perfusion imaging. The advent of CMR using extrinsic and intrinsic contrast-enhanced protocols for tissue characterisation have dramatically changed the non-invasive work-up of patients with suspected or known cardiomyopathy. Although the technique initially focused on the in vivo identification of myocardial necrosis through the late gadolinium enhancement (LGE) technique, recent work highlighted the ability of CMR to provide more detailed in vivo tissue characterisation to help establish a differential diagnosis of the underlying aetiology, to exclude an ischaemic substrate and to provide important prognostic markers. The potential application of CMR in the clinical approach of a patient with suspected non-ischaemic cardiomyopathy is discussed in this review. |
X Demographics
Geographical breakdown
Country | Count | As % |
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United States | 1 | 33% |
Unknown | 2 | 67% |
Demographic breakdown
Type | Count | As % |
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Members of the public | 3 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
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Germany | 3 | 2% |
United States | 2 | 1% |
United Kingdom | 1 | <1% |
Unknown | 169 | 97% |
Demographic breakdown
Readers by professional status | Count | As % |
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Researcher | 27 | 15% |
Student > Ph. D. Student | 24 | 14% |
Other | 23 | 13% |
Student > Doctoral Student | 19 | 11% |
Student > Master | 16 | 9% |
Other | 37 | 21% |
Unknown | 29 | 17% |
Readers by discipline | Count | As % |
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Medicine and Dentistry | 108 | 62% |
Engineering | 7 | 4% |
Computer Science | 4 | 2% |
Nursing and Health Professions | 4 | 2% |
Unspecified | 4 | 2% |
Other | 8 | 5% |
Unknown | 40 | 23% |