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Updated: May 5, 2026

Construction of a Preclinical Multimodality Phantom Using Tissue-mimicking Materials for Quality Assurance in Tumor Size Measurement
Published on: July 29, 2013
Calculation of recovery coefficients for partial volume effect correction in PET/CT imaging using a customized
Gunes Yavuz1, Bilal Kovan2, Turkay Toklu3
1Institute of Biomedical Engineering, Boğaziçi University, Kandilli Campus, Feza Gürsey Bld., 34685, Çengelköy-Istanbul, Turkey. gunesyavuz75@gmail.com.
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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