Influence of spatial resolution on the accuracy of quantitative myocardial perfusion in first pass stress perfusion...

High-resolution myocardial perfusion analysis allows for preserving spatial information with excellent sensitivity for subendocardial ischemia detection. However, it suffers from low signal-to-noise ratio. Commonly, spatial averaging is used to increase signal-to-noise ratio. This bears the risk of losing information about the extent, localization and transmurality of ischemia. This study investigates spatial-averaging effects on perfusion-estimates accuracy.

Perfusion data were obtained from patients and healthy volunteers. Spatial averaging was performed on voxel-based data in transmural and angular direction to reduce resolution to 50, 20, and 10% of its original value. Fit quality assessment method is used to measure the fraction of modeled information and remaining unmodeled information in the residuals.

Fraction of modeled information decreased in patients as resolution reduced. This decrease was more evident for Fermi and exponential in transmural direction. Fermi and exponential showed significant difference at 50% resolution (Fermi P < 0.001, exponential P =0.0014). No significant differences were observed for autoregressive-moving-average model (P = 0.081). At full resolution, autoregressive-moving-average model has the lowest fraction of residual information (0.3). Differences were observed comparing ischemic regions perfusion-estimates coefficient of variation at transmural and angular direction.

Angular averaging preserves more information compared to transmural averaging. Reducing resolution level below 50% at transmural and 20% at angular direction results in losing information about transmural perfusion differences. Maximum voxel size of 2 × 2 mm(2) is necessary to avoid loss of physiological information due to spatial averaging.