Computed tomography radiomic analysis of paraspinal muscles in the prognosis of advanced head and neck cancers
No parameter, including radiomic features, was able to statistically and independently demonstrate prognostic value for locally advanced head and neck cancers. However, a radiomic feature, the sum of Hounsfield unit value after discretization, when used in conjunction with Computed Tomography body composition parameters and clinico biological nutritional parameters could help predict survival.
Authors
- L. Cassagnes (ORCID: https://orcid.org/0000-0002-6863-5542)
- Maureen Bernadach (ORCID: https://orcid.org/0000-0002-7185-0809)
- N. Saroul (ORCID: https://orcid.org/0000-0003-3241-2010)
- J. Biau (ORCID: https://orcid.org/0000-0002-1570-4487)
- Bruno Pereira (ORCID: https://orcid.org/0000-0001-6102-4530)
- Benoît Magnin
- Rémi Thomas-Monier
- Alexane Lere-Chevaleyre
Institutions
- Centre National de la Recherche Scientifique (FR)
- Inserm (FR)
- Université Clermont Auvergne (FR)
- Institut National de Recherche pour l'Agriculture, l'Alimentation et l'Environnement (FR)
- University of Clermont Auvergne (FR)
- Sigma Clermont (FR)
- Centre Jean Perrin (FR)
- Centre Hospitalier Universitaire de Clermont-Ferrand (FR)
Publication Details
- Journal
- Clinical Nutrition ESPEN
- Published
- 2025-09-24
- DOI
- https://doi.org/10.1016/j.clnesp.2025.09.020
- Primary Topic
- Radiomics and Machine Learning in Medical Imaging
- Type
- article
- Field-Weighted Citation Impact
- 0.00