Modeling of carbon-11-acetate kinetics by simultaneously fitting data from multiple ROIs coupled by common parameters

Area of Science:

• Nuclear medicine
• Medical imaging
• Physiology

Background:

• Positron emission tomography (PET) enables noninvasive quantification of metabolic processes.
• Metabolic rate parameters are derived from time-activity curves in regions of interest (ROIs) using kinetic modeling.
• Coupling datasets with shared parameters, like time delays, can refine kinetic modeling.

Purpose of the Study:

• To evaluate a coupled region method for kinetic modeling in PET imaging.
• To assess the impact of parameter coupling on the precision of metabolic rate estimates, specifically k2.
• To compare the coupled region method with standard single-region fitting for myocardial oxygen consumption analysis.

Main Methods:

• Applied a coupled region method to data from eight ROIs on myocardial PET images.
• Coupled datasets using shared parameters for blood metabolite concentrations.
• Compared estimates of the rate constant k2 using the coupled method versus standard single-region fitting.
• Validated k2 estimates against measured myocardial oxygen consumption.

Main Results:

• The coupled region method reduced the variance in k2 estimates by an average of 37% when common parameters were unconstrained.
• Constraining common metabolite parameters further reduced the average variance in k2 estimates by 30%.
• Minimal changes were observed in the mean values of k2 between methods.

Conclusions:

• The coupled region technique significantly enhances the precision of myocardial oxygen consumption estimates from 11C-acetate PET images.
• Improved precision facilitates the detection of small regional or temporal physiological changes.
• This method is applicable when kinetic model parameters are known to be consistent across multiple ROIs.