Deep progressive reconstruction algorithm applicated in reconstructing whole-body 18 F-FDG PET images
10.13929/j.issn.1003-3289.2025.01.030
- VernacularTitle:深度渐进重建算法用于重建全身18F-FDG PET图像
- Author:
Yan TIAN
1
;
Qigang LONG
1
;
Zhenchun XU
1
;
Wenqian ZHANG
1
;
Liang CAI
1
Author Information
1. 重庆医科大学附属第二医院核医学科,重庆 400010
- Publication Type:Journal Article
- Keywords:
positron-emission tomography;
artificial intelligence;
image quality
- From:
Chinese Journal of Medical Imaging Technology
2025;41(1):142-147
- CountryChina
- Language:Chinese
-
Abstract:
Objective To observe the value of deep progressive reconstruction(DPR)algorithm for reconstructing whole-body 18 F-FDG PET images.Methods Totally 67 patients who underwent whole-body 18 F-FDG PET/CT were retrospectively enrolled.PET data of 30 s,60 s,90 s and 120 s per bed in equipment list were reconstructed using ordered subset expectation maximization(OSEM)and DPR algorithms,respectively.Finally 7 groups of reconstructed images were obtained,including OSEM_30,OSEM_60 and OSEM_120,also DPR_30,DPR_60,DPR_90 and DPR_120 groups.The subjective scores,also objective evaluation indexes,i.e.the maximum and mean standard uptake values(SUV)of lesions and livers,namely SUVmax and SUVmean,were compared,and target-to-background ratio(TBR),signal-to-noise ratio(SNR),contrast-to-noise ratio(CNR)and coefficient of liver variation(CVliver)were calculated.Taken results based in OSEM_120 group as references,Bland-Altman plot was drawn to explore the consistency of SUV of lesions and livers obtained based on DPR_30,DPR_60 and DPR_90 groups with those in OSEM_120 group.Results Under the same acquisition time,subjective scores,SUVmax and SUVmean of lesions,TBR,SNR,CNR and CVliver in DPR_30,DPR_60 and DPR_120 groups were superior to those in corresponding OSEM_30,OSEM_60 and OSEM_120 groups(all P＜0.001).Compared with OSEM_120 group,subjective scores and SNR decreased but TBR and CVliver increased in DPR_30 group,while subjective and objective evaluation results in DPR_60 group and DPR_90 group increased(all P＜0.05)or being not significantly different from those in OSEM_120 group(all P＞0.05).No significant difference of liver SUV mean was found among 7 groups(P=0.955).SUVmax and SUVmean of lesions and livers obtained based on DPR_30,DPR_60 and DPR_90 groups were in good agreement with those oibtained based on OSEM_120 group.Conclusion Using DPR algorithm to reconstruct whole-body 18 F-FDG PET image could shorten acquisition time under the premise of ensuring image quality.
