The Impact of Point Spread Function Modeling on Scan Duration in PET Imaging

Abstract

Purpose- In this study, we investigated the impact of PSF reconstruction 
acquisition time would compromise the accuracy of quantitative measures using PSF algorithm.
Methods- Both phantom and patient images were evaluated. A complete set of experiments were performed using an image quality phantom containing 6 inserts with 4:1 lesion to background ratio. Whole-body FDG PET/CT scan of 17 patients with different primary cancers were used in this study. All hantom
images reconstructed with 3 iterations, 24 subsets for 180, 150, 120, 90, and 60 s acquisition time per bed position. Post-smoothing filters with FWHM of 5 and 4 mm applied to HD and HD+PSF images respectively. Clinical PET images reconstructed with 3 iterations and 18 subsets. Quantitative analysis performed by CV%, SNR, RC, and SUVmax.
Results- By incorporating PSF algorithm, CV decreased 11.1% and 17.01% 0.92% for both phantom and clinical images. In addition, better edge detection achieved specially for smaller focal points. It was shown by reconstructing images with PSF algorithm, acquisition time can be reduced 33.3% with no significant changes of image quality and quantitative accuracy (P-value<0.05).
Conclusion- It can be concluded that using PSF algorithm improves the image quality, lesion detection, and quantitative accuracy. Besides, by incorporating this algorithm, the acquisition time can be reduced with no loss of image quality and quantitative accuracy where it is possible to have higher patient throughout with the same image quality.