Optimal experiment design for PET quantification of receptor concentration

Area of Science:

• Nuclear medicine
• Pharmacology
• Biophysics

Background:

• Mathematical models for positron emission tomography (PET) data analysis require parameter estimation.
• Estimating parameters for receptor quantitation is challenging due to complex interdependencies.
• Myocardial beta-adrenergic receptors are crucial targets for cardiovascular drug development.

Purpose of the Study:

• To optimize experimental design for precise estimation of myocardial beta-adrenergic receptor concentration.
• To improve the accuracy of receptor quantitation using PET and a novel ligand.

Main Methods:

• Utilized unlabeled and (18)F-labeled S(-)-fluorocarazolol as a ligand for receptor binding.
• Employed the D-optimal criterion to optimize ligand injection times and dosages for a three-injection study.
• Analyzed PET data to estimate model parameters and receptor concentration.

Main Results:

• Optimization revealed that the optimal three-injection design effectively reduces to a two-injection experiment.
• The optimized two-injection design yielded receptor concentration estimates nearly five times more precise than an empirical three-injection design.
• Ligand dosage in the third injection of the optimized design approached zero.

Conclusions:

• The D-optimal criterion is effective in optimizing PET experimental designs for receptor quantitation.
• A two-injection protocol is superior to a three-injection protocol for estimating myocardial beta-adrenergic receptor concentration.
• Optimized experimental designs can significantly enhance the precision of PET-based receptor imaging studies.