Quantitative contrast-enhanced myocardial perfusion magnetic resonance imaging: simulation of bolus dispersion in constricted vessels.
Quantification of myocardial blood flow (MBF) by means of T1-weighted first-pass magnetic resonance imaging (MRI) requires knowledge of the arterial input function (AIF), which is usually estimated from the left ventricle (LV). Dispersion of the contrast agent bolus may occur between the LV and the tissue of interest, which leads to systematic underestimation of the MBF. The aim of this study was to simulate the dispersion along a simplified coronary artery with different stenoses. To analyze the dispersion in vessels with typical dimensions of coronary arteries, simulations were performed using the computational fluid dynamics approach. Simulations were accomplished on straight vessels with integrated stenoses of different degrees of area reduction and length as well as two different shapes-an axial symmetric and an asymmetric. Two boundary conditions were used representing myocardial blood flow at rest and under hyperemic conditions. The results under steady boundary conditions show that the dispersion is more pronounced in resting condition than during hyperemia yielding an underestimation of the MBF around 15% in the resting state and around 8% under stress conditions. At the outlet of the vessel an axial symmetric stenosis results in increased dispersion whereas an asymmetric stenosis yields a reduction. Due to the more severe dispersion, resting MBF may be more underestimated in quantitative myocardial perfusion MRI studies compared with MBF under stress conditions. In consequence the myocardial perfusion reserve may be overestimated. The amount of systematic error depends in a complex way on the shape and degree of stenoses.
Graafen
Dirk
D
Section of Medical Physics, Department of Radiology, Johannes Gutenberg University Medical Center, 55131 Mainz, Germany. graafen@uni-mainz.de
Münnemann
Kerstin
K
Weber
Stefan
S
Kreitner
Karl-Friedrich
KF
Schreiber
Laura M
LM
D000465:Algorithms; D001783:Blood Flow Velocity; D003198:Computer Simulation; D017023:Coronary Angiography / Q000379:methods*; D003326:Coronary Circulation; D023921:Coronary Stenosis / Q000175:diagnosis* / Q000000981:diagnostic imaging / Q000503:physiopathology; D006940:Hyperemia / Q000175:diagnosis / Q000000981:diagnostic imaging / Q000503:physiopathology; D016014:Linear Models; D018810:Magnetic Resonance Angiography / Q000379:methods*; D008954:Models, Biological; D055414:Myocardial Perfusion Imaging / Q000379:methods*; D013312:Stress, Physiological / Q000502:physiology