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A microvascular compartment model validated using 11C-methylglucose liver PET in pigs
Ole L Munk1,2, Susanne Keiding1,3, Charles Baker4
1Department of Nuclear Medicine & PET Center, Aarhus University Hospital, 8000 Aarhus, Denmark.
Physics in Medicine and Biology
|October 19, 2017
Summary
A new microvascular compartment model (MCM) offers a more realistic analysis of dynamic PET data than the standard compartment model (CM). The MCM accurately captures tracer dynamics, including capillary gradients and backflux, yielding superior physiological parameter estimates.
Area of Science:
- Nuclear Medicine
- Physiology
- Pharmacokinetics
Background:
- The standard compartment model (CM) is a common tool for analyzing dynamic Positron Emission Tomography (PET) data.
- CM analyzes tracer transport between well-mixed compartments using rate constants derived from time-activity curves.
- Limitations exist in CM's ability to capture complex physiological processes in dynamic PET analysis.
Purpose of the Study:
- To develop and validate a more realistic microvascular compartment model (MCM) for dynamic PET data analysis.
- The MCM aims to incorporate capillary tracer concentration gradients, cellular backflux, and multiple re-uptakes.
- To compare the performance of the MCM against the standard CM using pig liver PET data.
Main Methods:
- Developed a novel microvascular compartment model (MCM) with physiologically meaningful parameters, avoiding numerical solutions.
- Acquired 3-minute dynamic PET data from pig livers (N=5) after injecting 11C-methylglucose.
- Measured blood tracer concentrations in the aorta, portal vein, and liver vein via manual sampling during PET scans.
Main Results:
- The MCM demonstrated superior performance compared to the CM in fitting dynamic PET data (Akaike values: MCM 46±4 vs. CM 82±8).
- MCM extracted physiologically relevant parameters, such as blood perfusion, with high accuracy, closely matching independent measurements (difference: -0.01±0.05 ml/ml/min).
- MCM accurately predicted liver vein tracer concentrations, a capability lacking in CM due to its inability to model tracer backflux.
Conclusions:
- The microvascular compartment model (MCM) significantly outperforms the standard compartment model (CM) for dynamic PET data analysis.
- Dynamic PET data contain information not extractable by the standard CM, highlighting the need for more sophisticated models.
- Models incorporating detailed physiological processes, such as concentration gradients and backflux, are crucial for accurate analysis of tracer exchange in capillary beds.
