Metabolic tumour volume in Hodgkin lymphoma - a comparison between manual and AI-based analysis.

May SadikSally F BarringtonElin TrägårdhBabak SabouryAnne Lerberg NielsenAnnika Loft JakobsenJose Luis Loaiza GongoraJesus Lopez UrdanetaRajender KumarLars Edenbrandt

Published in: Clinical physiology and functional imaging (2023)

The results of this study indicate that RECOMIA and Siemens PARS AI tools could be used without any major manual adjustments in 69% (33/48) and 58% (28/48) of HL-patients, respectively. This demonstrates the feasibility of using AI tools to support physicians measuring tMTV for assessment of prognosis in clinical practice. This article is protected by copyright. All rights reserved.

Keyphrases

hodgkin lymphoma
artificial intelligence
end stage renal disease
clinical practice
ejection fraction
primary care
newly diagnosed
chronic kidney disease
peritoneal dialysis
prognostic factors
deep learning
patient reported outcomes