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Published on: January 24, 2025
A Factor-Image Framework to Quantification of Brain Receptor Dynamic PET Studies.
Z Jane Wang1, Zsolt Szabo, Peng Lei
1Member, IEEE, The Department of Electrical and Computer Engineering, University of British Columbia, Vancouver, BC, Canada (e-mail: zjanew@ece.ubc.ca ).
This study introduces a new voxel-based framework for positron emission tomography (PET) imaging, improving quantification of receptor binding and neurotransmitter release in the brain. The method reliably estimates kinetic parameters and input functions, even without arterial blood sampling.
Area of Science:
- Neuroimaging
- Radiochemistry
- Biophysics
Background:
- Positron emission tomography (PET) enables in vivo measurement of brain receptor distribution and neurotransmitter release.
- Quantification in PET studies is challenged by voxel-level tissue heterogeneity due to limited scanner spatial resolution.
- Tracer kinetic modeling often necessitates invasive arterial blood sampling for input function determination.
Purpose of the Study:
- To develop a likelihood-based framework in the voxel domain for quantitative PET imaging.
- To enable accurate estimation of radioligand kinetic parameters and the input function, with or without blood sampling.
- To address challenges posed by tissue heterogeneity and improve the reliability of PET data analysis.
Main Methods:
- A novel likelihood-based framework is proposed for quantitative imaging in the voxel domain.
- Radioligand kinetic parameters and the input function are co-estimated.
- Parameter initialization uses a subspace-based algorithm, followed by iterative likelihood-based refinement.
Main Results:
- Simulations demonstrate reliable estimation of factor time-activity curves (TACs) and parametric images.
- The proposed approach shows good agreement with the Logan plot method.
- Analysis of real brain PET data confirms robust performance in determining TACs and factor images.
Conclusions:
- The developed voxel-based framework offers a reliable method for quantitative PET imaging.
- It effectively estimates kinetic parameters and input functions, reducing reliance on arterial blood sampling.
- This advancement holds promise for improved understanding of receptor binding and neurotransmitter dynamics in the brain.
