Development of a Monte Carlo-based scatter correction method for total-body PET using the uEXPLORER PET/CT scanner.

Autor:	Bayerlein R; Departments of Radiology and Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Spencer BA; Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Leung EK; UIH America, Houston, TX, United States of America., Omidvari N; Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Abdelhafez YG; Departments of Radiology and Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Wang Q; Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Nardo L; Departments of Radiology and Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Cherry SR; Departments of Radiology and Biomedical Engineering, University of California-Davis, Davis, CA, United States of America.; Biomedical Engineering, University of California-Davis, Davis, CA, United States of America., Badawi RD; Departments of Radiology and Biomedical Engineering, University of California-Davis, Davis, CA, United States of America.; Biomedical Engineering, University of California-Davis, Davis, CA, United States of America.
Jazyk:	angličtina
Zdroj:	Physics in medicine and biology [Phys Med Biol] 2024 Feb 16; Vol. 69 (4). Date of Electronic Publication: 2024 Feb 16.
DOI:	10.1088/1361-6560/ad2230
Abstrakt:	Objective. This study presents and evaluates a robust Monte Carlo-based scatter correction (SC) method for long axial field of view (FOV) and total-body positron emission tomography (PET) using the uEXPLORER total-body PET/CT scanner. Approach. Our algorithm utilizes the Monte Carlo (MC) tool SimSET to compute SC factors in between individual image reconstruction iterations within our in-house list-mode and time-of-flight-based image reconstruction framework. We also introduced a unique scatter scaling technique at the detector block-level for optimal estimation of the scatter contribution in each line of response. First image evaluations were derived from phantom data spanning the entire axial FOV along with image data from a human subject with a large body mass index. Data was evaluated based on qualitative inspections, and contrast recovery, background variability, residual scatter removal from cold regions, biases and axial uniformity were quantified and compared to non-scatter-corrected images. Main results. All reconstructed images demonstrated qualitative and quantitative improvements compared to non-scatter-corrected images: contrast recovery coefficients improved by up to 17.2% and background variability was reduced by up to 34.3%, and the residual lung error was between 1.26% and 2.08%. Low biases throughout the axial FOV indicate high quantitative accuracy and axial uniformity of the corrections. Up to 99% of residual activity in cold areas in the human subject was removed, and the reliability of the method was demonstrated in challenging body regions like in the proximity of a highly attenuating knee prosthesis. Significance. The MC SC method employed was demonstrated to be accurate and robust in TB-PET. The results of this study can serve as a benchmark for optimizing the quantitative performance of future SC techniques. (© 2024 Institute of Physics and Engineering in Medicine.)
Databáze:	MEDLINE
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