PET NEMA IQ Phantom dataset: image reconstruction settings for quantitative PET imaging

Area of Science:

• Nuclear Medicine
• Medical Imaging Physics

Background:

• Accurate quantification in Positron Emission Tomography (PET) is essential for clinical diagnosis and research.
• Reconstruction parameters can influence the accuracy of quantitative metrics derived from PET images.

Purpose of the Study:

• To investigate the impact of various reconstruction parameters on PET image quantification.
• To evaluate the performance of different Volume of Interest (VOI) methods and derived quantitative indices.

Main Methods:

• Phantom measurements were performed using a Biograph 6 TruePoint TrueV PET/CT scanner with varying Spheres to Background Ratios (SBR).
• PET data were reconstructed with and without resolution recovery, using different iteration x subsets and Gaussian post-smoothing filter (FWHM) values.
• Recovery Coefficients (RC), Standardized Uptake Values (SUV), Metabolic Tumor Volume (MTV), Volume Recovery Coefficient (VRC), and Total Lesion Glycolysis (TLG) were calculated using multiple VOI methods.

Main Results:

• Recovery Coefficients (RCmax, RC50%, RCpeak) varied significantly with sphere size, SBR, and reconstruction parameters.
• The choice of reconstruction algorithm, iteration/subset numbers, and Gaussian post-smoothing FWHM influenced quantitative metrics.
• Different VOI methods yielded distinct quantitative values, highlighting the sensitivity to reconstruction settings.

Conclusions:

• Reconstruction parameter selection critically affects PET image quantification and derived metrics.
• Standardization of reconstruction protocols is necessary for reliable and reproducible quantitative PET imaging.
• The findings provide valuable data for optimizing quantitative metrics in PET studies.