Comparison of myocardial perfusion estimates from dynamic contrast-enhanced magnetic resonance imaging with four quantitative analysis methods.

Dynamic contrast-enhanced MRI has been used to quantify myocardial perfusion in recent years. Published results have varied widely, possibly depending on the method used to analyze the dynamic perfusion data. Here, four quantitative analysis methods (two-compartment modeling, Fermi function modeling, model-independent analysis, and Patlak plot analysis) were implemented and compared for quantifying myocardial perfusion. Dynamic contrast-enhanced MRI data were acquired in 20 human subjects at rest with low-dose (0.019 +/- 0.005 mmol/kg) bolus injections of gadolinium. Fourteen of these subjects were also imaged at adenosine stress (0.021 +/- 0.005 mmol/kg). Aggregate rest perfusion estimates were not significantly different between all four analysis methods. At stress, perfusion estimates were not significantly different between two-compartment modeling, model-independent analysis, and Patlak plot analysis. Stress estimates from the Fermi model were significantly higher (approximately 20%) than the other three methods. Myocardial perfusion reserve values were not significantly different between all four methods. Model-independent analysis resulted in the lowest model curve-fit errors. When more than just the first pass of data was analyzed, perfusion estimates from two-compartment modeling and model-independent analysis did not change significantly, unlike results from Fermi function modeling.