Resting myocardial blood flow quantification using contrast‐enhanced magnetic resonance imaging in the presence of stenosis: A computational fluid dynamics study

Abstract

Purpose: The extent to which atherosclerotic plaques affect contrast agent (CA) transport in the coronary arteries and, hence, quantification of myocardial blood flow (MBF) using magnetic resonance imaging (MRI) is unclear. The purpose of this work was to evaluate the influence of plaque induced stenosis both on CA transport and on the accuracy of MBF quantification. Methods: Computational fluid dynamics simulations in a high‐detailed realistic vascular model were employed to investigate CA bolus transport in the coronary arteries. The impact of atherosclerosis was analyzed by inserting various medium‐ to high‐grade stenoses in the vascular model. The influence of stenosis morphology was examined by varying the stenosis shapes but keeping the area reduction constant. Errors due to CA bolus transport were analyzed using the tracer‐kinetic model MMID4. Results: Dispersion of the CA bolus was found in all models and for all outlets, but with a varying magnitude. The impact of stenosis was complex: while high‐grade stenoses amplified dispersion, mild stenoses reduced the effect. Morphology was found to have a marked influence on dispersion for a small number of outlets in the post‐stenotic region. Despite this marked influence on the concentration–time curves, MBF errors were less affected by stenosis. In total, MBF was underestimated by −7.9% to −44.9%. Conclusions: The presented results reveal that local hemodynamics in the coronary vasculature appears to have a direct impact on CA bolus dispersion. Inclusion of atherosclerotic plaques resulted in a complex alteration of this effect, with both degree of area reduction and stenosis morphology affecting the amount of dispersion. This strong influence of vascular transport effects impairs the accuracy of MRI‐based MBF quantification techniques and, potentially, other bolus‐based perfusion measurement techniques like computed tomography perfusion imaging.

Influence of contrast agent dispersion on bolus‐based MRI myocardial perfusion measurements: A computational fluid dynamics study

“…The vascular geometries are discretized using the software package cfMesh (Creative Fields, London, United Kingdom), yielding mesh sizes of 13 830 835 (96% hexahedral type, duration mesh creation: 1.5 hours) on the LCT grid and 6 975 193 (95%, 20 minutes) on the RCT grid. The chosen resolution is based on the mesh convergence analyses in Refs .…”

“…The parameters to generate tissue concentration time curves Conc Myo from Figure with MMID4 can be set within the software JSim and are chosen as in a number of other studies . At rest, an MBF of 1 mL/min/g is assumed.…”

“…Vascular stenosis introduces further complexity. 25 These earlier studies suggest systematic MBF underestimation due to various influencing factors such as blood flow velocity, length, curvature, and branching of the analyzed vascular segment(s), as well as stenosis shape and degree. Furthermore, these studies indicate a decreasing influence of smaller vessels on dispersion, suggesting that the CA bolus dispersion effects do not occur in vessels beyond a certain limiting vessel generation.…”

“…The parameters to generate tissue concentration time curves Conc Myo from Figure 2 with MMID4 can be set within the software JSim 55 and are chosen as in a number of other studies. 6,9,10,[22][23][24][25]30,56 At rest, an MBF of 1 mL/min/g is assumed. At stress, MBF is assumed to increase to 2.7 and 2.3 mL/min/g in the LV and RV, respectively.…”

“…Interestingly, CFD simulations demonstrate that these effects occur even in nonstenotic (i.e., normal) vessels. Vascular stenosis introduces further complexity …”