Effect of deeply progressive reconstruction algorithm on image quality and SUV of 18F-FDG PET/CT in obese patients
10.3969/j.issn.1672-8270.2025.01.005
- VernacularTitle:深度渐进重建算法对肥胖患者18F-脱氧葡萄糖PET/CT图像质量和标准化摄取值的影响
- Author:
Zhou MAO
1
;
Qingle MENG
1
;
Rui YANG
1
;
Rushuai LI
1
;
Chi WEI
1
;
Rencong LIU
1
;
Feng WANG
1
;
Lei XU
1
;
Yan CAO
1
Author Information
1. 南京医科大学附属南京医院(南京市第一医院)核医学科 南京 210006
- Publication Type:Journal Article
- Keywords:
Positron computer tomography/Computed tomography (PET/CT);
18F-fluorodeoxyglucose (18F-FDG);
Ordered subset expectation maximization (OSEM);
Deep learning
- From:
China Medical Equipment
2025;22(1):24-29
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the enhancement effect of deep progressive reconstruction (DPR) algorithm on image quality and standardized uptake value (SUV) of 18F-fluorodeoxyglucose positron emission tomography/computed tomography (18F-FDG PET/CT) in obese patients. Methods:The images of a total of 27 obese patients,who underwent 18F-FDG PET/CT in Affiliated Nanjing Hospital of Nanjing Medical University from September 2023 to May 2024,were retrospectively enrolled. The images of all patients were collected by using uMI 780 PET/CT. Ordered subset expectation maximization (OSEM) iterative algorithm and DPR algorithm were adopted to reconstruct PET images,and measure counting rate of scattering coincidence of PET/CT images,counting rate of true coincidence,noise equivalent counting rate (NECR) and scattering fraction (SF). The quality indicators of PET images included signal-to-noise ratio (SNR),the maximum SUV (SUVmax) of lesions,the tumor-to-background ratio (TBR),the contrast-to-noise ratio (CNR) and the visual scores of 18F-FDG PET/CT images on livers were evaluated. The differences and consistency of various indicators between DPR and OSEM reconstruction algorithms were further analyzed. Results:The average 18F-FDG PET/CT injection activity of 27 patients was (0.12±0.01) mCi (1 mCi=37 MBq)/kg,and the counting rate of true coincidence,NECR and SF of PET images were respectively (153.73±25.09),(44.81±8.47) kcps and (36.77±1.91)％. The SNR of liver obtained by DPR algorithm was (15.83±3.60),which was significantly higher than that (9.06±1.87) of OSEM algorithm,with statistically significant (t=20.6,P<0.05),and there was significantly correlation in liver SNR between two algorithms (R2=0.91,P<0.05). In 27 uptake 18F-FDG PET/CT lesions,the SUVmax,TBR and CNR of lesions that were obtained from OSEM algorithm were respectively (5.86±1.49),(1.95±0.49) and (17.74±4.77),which were lower than corresponding those of DPR algorithm,and the differences were significant (t=9.03,8.79,15.49,P<0.05),respectively. There were significant correlations in SUVmax,TBR and CNR between the two algorithms (R2=0.71,0.70,0.76,P<0.05),respectively. The visual scores of PET images obtained from the DPR algorithm was 4 (3,5) scores,which was significantly higher than 3 (2,4) scores of OSEM algorithm,and the difference of that between two algorithms was significant (U=396,P<0.05). Conclusion:The scattering effect of 18F-FDG PET/CT imaging is stronger in obese patients,whose counting rate of equivalent effect of noise is lower. The DPR reconstruction algorithm can significantly improve the SNR and lesion contrast of PET images than the OSEM algorithm,which has significant gain effect on the SUVmax of lesions,and it can significantly improve the quality of 18F-FDG PET/PET images in obese patients.
