Artificial intelligence contouring in radiotherapy for organs-at-risk and lymph node areas.

Date publication

novembre 2024

Journal

Radiation oncology (London, England)

Auteurs

Membres identifiés du Cancéropôle Est :
Dr RETIF Paul , Dr FAIVRE Jean-Christophe , Dr MARTZ Nicolas

Tous les auteurs :
Meyer C, Huger S, Bruand M, Leroy T, Palisson J, Rétif P, Sarrade T, Barateau A, Renard S, Jolnerovski M, Demogeot N, Marcel J, Martz N, Stefani A, Sellami S, Jacques J, Agnoux E, Gehin W, Trampetti I, Margulies A, Golfier C, Khattabi Y, Olivier C, Alizée R, Py JF, Faivre JC

Lien Pubmed

https://www.ncbi.nlm.nih.gov/pubmed/39574153

Résumé

The delineation of organs-at-risk and lymph node areas is a crucial step in radiotherapy, but it is time-consuming and associated with substantial user-dependent variability in contouring. Artificial intelligence (AI) appears to be the solution to facilitate and standardize this work. The objective of this study is to compare eight available AI software programs in terms of technical aspects and accuracy for contouring organs-at-risk and lymph node areas with current international contouring recommendations.

Mots clés

Humans, Organs at Risk, radiation effects, Artificial Intelligence, Female, Male, Lymph Nodes, radiation effects, Radiotherapy Planning, Computer-Assisted, methods, Adult, Child, Tomography, X-Ray Computed, methods, Magnetic Resonance Imaging, methods, Software

Référence

Radiat Oncol. 2024 11 21;19(1):168