Impact of a deep progressive reconstruction algorithm on low-dose or fast-scan PET image quality and Deauville score in patients with lymphoma.

ABSTRACT:

Background

A 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 ¹⁸F-FDG by up to 2/3 in a real-world deployment with DPR. The aim of this study is to assess the impact of the use of DPR on Deauville score (DS) and clinical interpretation of PET/CT in patients with lymphoma.

Methods

A total of 87 lymphoma patients (age, 45.1 ± 14.9 years) who underwent ¹⁸F-FDG PET imaging for during or post-treatment follow-up from November 2020 to F

SUBMITTER: Qiao W 

PROVIDER: S-EPMC11961783 | biostudies-literature | 2025 Apr

REPOSITORIES: biostudies-literature