AUTHOR=Frood Russell , Willaime Julien M. Y. , Miles Brad , Chambers Greg , Al-Chalabi H’ssein , Ali Tamir , Hougham Natasha , Brooks Naomi , Petrides George , Naylor Matthew , Ward Daniel , Sulkin Tom , Chaytor Richard , Strouhal Peter , Patel Chirag , Scarsbrook Andrew F. 

TITLE=Comparative effectiveness of standard vs. AI-assisted PET/CT reading workflow for pre-treatment lymphoma staging: a multi-institutional reader study evaluation

JOURNAL=Frontiers in Nuclear Medicine

VOLUME=Volume 3 - 2023

YEAR=2024

URL=https://www.frontiersin.org/journals/nuclear-medicine/articles/10.3389/fnume.2023.1327186

DOI=10.3389/fnume.2023.1327186

ISSN=2673-8880

ABSTRACT=The incidence of lymphoma is increasing worldwide, with FDG PET/CT used to stage high-grade lymphoma. The complexity of cases can vary at presentation with the more complex cases being more time consuming to report. Artificial intelligence (AI) has the potential to help improve the accuracy and speed of reporting. The aim of our multi-centre reader study was to assess the effect of AI assistance on reader speed and quality of reporting, as well as the influence of AI on reporting behavior. The study found that AI assistance significantly improved the speed of reporting whilst maintaining report quality, and that less experienced reporters were more at risk of being influenced