ArticleBiomedical engineering online2025
Calculation of recovery coefficients for partial volume effect correction in PET/CT imaging using a customized anthropomorphic body phantom.
Article in Biomedical engineering online, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
1 citing paper in PubMed.
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Authors and funding
5 authors.
Funding
Abstract
Positron Emission Tomography/Computed Tomography (PET/CT) combines metabolic and anatomical information improving the precision and accuracy of oncological diagnostics. The standardized uptake value (SUV) measures tumor metabolism, yet its accuracy is influenced by the partial volume effect (PVE), impacting small lesion detection. This study aims to refine PVE corrections for small lesions using an in-house customized, special anthropomorphic phantom. Scans of this phantom which contained spheres of different sizes were performed across four hospitals at different PET/CT systems from various manufacturers (Siemens and Philips analog PET/CT systems, GE analog and digital PET/CT systems). The phantom contained six custom-designed cylinders with embedded spheres simulating sub-centimeter (0.3, 0.5, 0.9) and centimeter (1.3, 1.9, 2.8) lesions. Scans were performed separately for each sphere in the thorax, abdomen, and pelvis regions at all sites. Recovery Coefficients (RCs) were calculated to correct SUV values, demonstrating that RCs vary by sphere size and anatomical region but not change significantly among scanners. RCs are approaching unity for larger spheres, ensuring accurate SUV measurements. However, small spheres (< 0.5 cm) exhibited significant measurement challenges due to PVE. The anthropomorphic phantom proved effective in obtaining realistic SUV-corrected values, offering a promising tool for enhancing the accuracy and standardization of PET imaging in oncology. This study underscores the necessity for advanced imaging technologies and standardized RC application in clinical settings to improve the quantification of PET imaging, particularly in small lesion detection.
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