Purpose: Bolus-based dynamic contrast agent (CA) perfusion measurements of the heart are subject to systematic errors due to CA bolus dispersion in the coronary arteries. To better understand these effects on quantification of myocardial blood flow and myocardial perfusion reserve (MPR), an in-silico model of the coronary arteries down to the pre-arteriolar vessels has been developed. Methods: In this work, a computational fluid dynamics analysis is performed to investigate these errors on the basis of realistic 3D models of the left and right porcine coronary artery trees, including vessels at the pre-arteriolar level. Using advanced boundary conditions, simulations of blood flow and CA transport are conducted at rest and under stress. These are evaluated with regard to dispersion (assessed by the width of CA concentration time curves and associated vascular transport functions) and errors of myocardial blood flow and myocardial perfusion reserve quantification. Results: Contrast agent dispersion increases with traveled distance as well as vessel diameter, and decreases with higher flow velocities. Overall, the average myocardial blood flow errors are −28% ± 16% and −8.5% ± 3.3% at rest and stress, respectively, and the average myocardial perfusion reserve error is 26% ± 22%. The calculated values are different in the left and right coronary tree. Conclusion: Contrast agent dispersion is dependent on a complex interplay of several different factors characterizing the cardiovascular bed, including vessel size and integrated vascular length. Quantification errors evoked by the observed CA dispersion show nonnegligible distortion in dynamic CA bolus-based perfusion measurements. We expect future improvements of quantitative perfusion measurements to make the systematic errors described here more apparent.
CITATION STYLE
Martens, J., Panzer, S., van den Wijngaard, J., Siebes, M., & Schreiber, L. M. (2020). Influence of contrast agent dispersion on bolus-based MRI myocardial perfusion measurements: A computational fluid dynamics study. Magnetic Resonance in Medicine, 84(1), 467–483. https://doi.org/10.1002/mrm.28125
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