Coronary artery assessment using self-navigated free-breathing radial whole-heart magnetic resonance angiography in patients with congenital heart disease
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To evaluate a self-navigated free-breathing three-dimensional (SNFB3D) radial whole-heart MRA technique for assessment of main coronary arteries (CAs) and side branches in patients with congenital heart disease (CHD).
SNFB3D-MRA datasets of 109 patients (20.1±11.8 years) were included. Three readers assessed the depiction of CA segments, diagnostic confidence in determining CA dominance, overall image quality and the ability to freeze cardiac and respiratory motion. Vessel sharpness was quantitatively measured.
The percentages of cases with excellent CA depiction were as follows (mean score): left main, 92.6 % (1.92); left anterior descending (LAD), 88.3 % (1.88); right (RCA), 87.8 % (1.85); left circumflex, 82.8 % (1.82); posterior descending, 50.2 % (1.50) and first diagonal, 39.8 % (1.39). High diagnostic confidence for the assessment of CA dominance was achieved in 56.2 % of MRA examinations (mean score, 1.56). Cardiac motion freezing (mean score, 2.18; Pearson’s r=0.73, P<0.029) affected image quality more than respiratory motion freezing (mean score, 2.20; r=0.58, P<0.029). Mean quantitative vessel sharpness of the internal thoracic artery, RCA and LAD were 53.1, 52.5 and 48.7 %, respectively.
Most SNFB3D-MRA examinations allow for excellent depiction of the main CAs in young CHD patients; visualisation of side branches remains limited.
• Self-navigated free-breathing three-dimensional magnetic resonance angiography (SNFB3D-MRA) sufficiently visualises coronary arteries (CAs).
• Depiction of main CAs in patients with congenital heart disease is excellent.
• Visualisation of CA side branches using SNFB3D-MRA is limited.
• SNFB3D-MRA image quality is especially correlated to cardiac motion freezing ability.
KeywordsMagnetic resonance angiography Cardiac imaging Paediatric radiology Congenital heart disease Coronary angiography
Compliance with ethical standards
The scientific guarantor of this publication is Prof. Dr. U. Joseph Schoepf.
Conflict of interest
The authors of this manuscript declare relationships with the following companies: U. Joseph Schoepf is a consultant for and/or receives research support from Astellas, Bayer, Bracco, GE, and Siemens. Carlo N. De Cecco is a consultant for and/or receives research support from Guerbet and Siemens. Akos Varga-Szemes is a consultant for Guerbet. Davide Piccini is an employee of Siemens Healthcare.
The other authors of this manuscript declare no relationships with any companies whose products or services may be related to the subject matter of the article.
Part of this research was funded by the Swiss National Science Foundation Grant SNF 320030_143923.
Statistics and biometry
One of the authors has significant statistical expertise.
Institutional Review Board approval was obtained.
Written informed consent was waived by the Institutional Review Board.
• performed at one institution
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