Quantifying cardiac PET: MFR may be more consistent than MBF

There are a few different quantitative techniques used to measure myocardial blood flow (MBF) and myocardial flow reserve (MFR), both of which have been shown to provide useful information in managing cardiovascular disease. However, MFR measurements appear to be less affected by variables of quantitation when using different arterial input functions and extraction models, according to a comparison study published today in the Journal of Nuclear Medicine.

Venkatesh Murthy, MD, PhD, from the University of Michigan in Ann Arbor, and colleagues oversaw the Rb-82 rest-stress cardiac PET of 2,783 consecutive patients from 2006 to 2010 and conducted a statistical analysis for the input function and extraction model used to measure stress MBF and MFR. Five such extraction models included the Cohen K, bias and Pearson correlations. Input function was assessed via factor analysis, region of interest around the mitral valve or a combination of the two.

The researchers found stress MBF and MFR to be consistent when the input function was the same, even across different extraction models, but as soon as the input function changed, the correlations weakened significantly when quantifying MBF. Ultimately these inconsistencies had an impact on the assessed link between stress MBF and cardiac death. 

“Variability in the technique used to determine the input function and the extraction model for Rb-82 can lead to large differences in estimates for stress MBF and, to a lesser extent, MFR,” wrote Murthy et al. “The greater variability in stress MBF measures results in substantial variation in the relationship between stress MBF and annual cardiac mortality, depending on the technique used. In contrast, MFR is considerably more consistent, with similar relationships between MFR and cardiac mortality, regardless of technique used.”

The researchers concluded that improved standardization of these methods is essential to improving quantitative cardiac PET. Without standardization, the value of these measurements across clinical trials could be called into question.