Optimizing Bayesian penalized likelihood algorithm for low count PET reconstruction to simulate low dose PET imaging
10.3760/cma.j.cn321828-20231016-00073
- VernacularTitle:优化贝叶斯惩罚似然法的低计数PET重建模拟低剂量PET显像
- Author:
Weiwei RUAN
1
;
Fang LIU
;
Hua SHU
;
Jia HU
;
Xiaoli LAN
Author Information
1. 华中科技大学同济医学院附属协和医院核医学科、分子影像湖北省重点实验室，武汉 430022
- Keywords:
Neoplasms;
Positron-emission tomography;
Magnetic resonance imaging;
Fluorodeoxyglucose F18;
Bayes theorem;
Algorithms;
Image processing, computer-assisted
- From:
Chinese Journal of Nuclear Medicine and Molecular Imaging
2023;43(12):718-723
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To study whether Bayesian penalized likelihood (BPL) and its optimized reconstruction algorithm can improve the reconstructed image quality of low count total-body PET.Methods:Eight patients (5 males, 3 females, age (67.2±6.3) years) who underwent hybrid 18F-FDG PET/MR total-body scans at Department of Nuclear Medicine in Union Hospital, Tongji Medical College, Huazhong University of Science and Technology were collected retrospectively from January to June in 2023. Total-body PET/MR images of them were included and list-mode data were reconstructed with four methods, namely 25% counts conventional reconstruction (group 1), 100% counts conventional reconstruction (group 2), 25% counts BPL reconstruction (group 3), and 25% counts optimized BPL reconstruction (group 4). At last, 32 total-body PET images were obtained. SUV max and SUV mean in different ROIs and tumor metabolic volume (MTV) were measured. Total lesion glycolysis (TLG) and parameters of image quality including the ratio of lesion to background (L/B) and image signal-to-noise ratio (SNR) were calculated. Then the differences in all the parameters among the four groups were analyzed by repeated measures analysis of variance and Friedman test. Quantitative differences between BPL reconstruction and optimized BPL with the 100% counts conventional reconstruction were compared respectively by using the Bland-Altman (BA) plot. Results:For the inter-group comparison, except for SUV mean in the muscle ( F=0.38, P=0.767), SUV max and SUV mean in other ROIs were statistically different ( F values: 8.15-36.08, χ2=18.15, all P<0.01), as well as MTV and L/B ( χ2 values: 10.65, 13.35, P values: 0.014, 0.004), but not for TLG ( χ2=4.95, P=0.175) or SNR ( F=2.64, P=0.076). For the pairwise comparison, the differences between group 2 and group 3 were the most significant (all P<0.05). Compared with group 2, there were no significant differences for SUV max and SUV mean of the cerebellar cortex and lesions in group 4 (all P>0.05), as well as MTV and L/B (both P>0.05). In addition, compared with group 1, SUV max of liver and muscle in group 2 were decreased (both P<0.05), while there were no significant differences in group 4 (all P>0.05). BA plots showed that the differences of SUV, MTV, and TLG between group 4 and group 2 were smaller obviously than those between group 3 and group 2. Conclusion:BPL reconstruction can improve low focus detection sensitivity induced by low counts, but it will cause significant changes for PET quantification, which can be solved by optimized BPL reconstruction.
