ArticleEJNMMI physics2025
Impact of a deep progressive reconstruction algorithm on low-dose or fast-scan PET image quality and Deauville score in patients with lymphoma.
Article in EJNMMI physics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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2 citing papers in PubMed.
- Toward an optimized PET reconstruction protocol for spinal cord: superiority of OSEM with TOF and PSF.EJNMMI physics · 2026Article
- Innovations in clinical PET image reconstruction: advances in Bayesian penalized likelihood algorithm and deep learning.Annals of nuclear medicine · 2025Review
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Abstract
backgroundA deep progressive learning method for PET image reconstruction named deep progressive reconstruction (DPR) method was developed and presented in previous works. It has been shown in previous study that the DPR with one-third duration can maintain the image quality as OSEM with standard dose (3.7 MBq/kg). Subsequent studies have shown we can reduce the administered activity of
methodsA total of 87 lymphoma patients (age, 45.1 ± 14.9 years) who underwent
resultsThe patients with OSEM_6 min_1/3 and DPR_2 min_1/3 showed good image quality with 5(5,5) and 5(4,5) of Likert scoring, as well as the patients with OSEM_2 min_full and DPR_40 s_full. No significant difference was found between the OSEM_6 min_1/3 and DPR_2 min_1/3 groups in terms of liver SUVmax and MBP SUVmax (P = 0.452 and 0.430), as well as the patients with OSEM_2 min_full and DPR_40 s_full (P = 0.105 and 0.638). No significant difference was found between the OSEM_6 min_1/3 and DPR_2 min_1/3 groups in terms of lesion SUVmax (P = 0.080). There was a significant differences in lesion SUVmax between OSEM-2 min_full with DPR-40 s_full (P = 0.027). The DS results were consistent (100%) between OSEM-6 min_1/3 with DPR_2 min_1/3, and between OSEM-2 min_full with DPR-40 s_full, respectively.
conclusionsDPR reconstruction demonstrated feasibility in reducing PET injection dose or scanning time, while ensuring the preservation of image quality and DS for during or post-treatment follow-up patients with lymphoma.
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