Application of geometric shape‐based CT field‐of‐view extension algorithms in an all‐digital positron emission tomography/computed tomography system

• Published in: Medical physics (Lancaster) Vol. 51; no. 2; pp. 1034 - 1046
• Main Authors: Hu, Tianjiao, Li, Bingxuan, Yang, Jigang, Zhang, Bo, Fang, Lei, Liu, Yuqing, Xiao, Peng, Xie, Qingguo
• Format: Journal Article
• Language: English
• Published: United States 01.02.2024
• Subjects: all‐digital PET/CT system; artifact correction; attenuation correction; extended FOV; truncated projections; truncated projections; all-digital PET/CT system; attenuation correction; extended FOV; artifact correction
• ISSN: 0094-2405; 2473-4209; 2473-4209
• DOI: 10.1002/mp.16888

Background Computed tomography (CT)‐based positron emission tomography (PET) attenuation correction (AC) is a commonly used method in PET AC. However, the CT truncation caused by the subject's limbs outside the CT field‐of‐view (FOV) leads to errors in PET AC. Purpose In order to enhance the quantitative accuracy of PET imaging in the all‐digital DigitMI 930 PET/CT system, we assessed the impact of FOV truncation on its image quality and investigated the effectiveness of geometric shape‐based FOV extension algorithms in this system. Methods We implemented two geometric shape‐based FOV extension algorithms. By setting the data from different numbers of detector channels on either side of the sinogram to zero, we simulated various levels of truncation. Specific regions of interest (ROI) were selected, and the mean values of these ROIs were calculated to visually compare the differences between truncated CT, CT extended using the FOV extension algorithms, and the original CT. Furthermore, we conducted statistical analyses on the mean and standard deviation of residual maps between truncated/extended CT and the original CT at different levels of truncation. Subsequently, similar data processing was applied to PET images corrected using original CT and those corrected using simulated truncated and extended CT images. This allowed us to evaluate the influence of FOV truncation on the images produced by the DigitMI 930 PET/CT system and assess the effectiveness of the FOV extension algorithms. Results Truncation caused bright artifacts at the CT FOV edge and a slight increase in pixel values within the FOV. When using truncated CT data for PET AC, the PET activity outside the CT FOV decreased, while the extension algorithm effectively reduced these effects. Patient data showed that the activity within the CT FOV decreased by 60% in the truncated image compared to the base image, but this number could be reduced to at least 17.3% after extension. Conclusion The two geometric shape‐based algorithms effectively eliminate CT truncation artifacts and restore the true distribution of CT shape and PET emission data outside the FOV in the all‐digital DigitMI 930 PET/CT system. These two algorithms can be used as basic solutions for CT FOV extension in all‐digital PET/CT systems.