A Machine learning model trained on dual-energy CT radiomics significantly improves immunotherapy response prediction for patients with stage IV melanoma

BACKGROUND: To assess the additive value of dual-energy CT (DECT) over single-energy CT (SECT) to radiomics-based response prediction in patients with metastatic melanoma preceding immunotherapy. MATERIAL AND METHODS: A total of 140 consecutive patients with melanoma (58 female, 63±16 years) for who...

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Detalles Bibliográficos
Autores principales: Brendlin, Andreas Stefan, Peisen, Felix, Almansour, Haidara, Afat, Saif, Eigentler, Thomas, Amaral, Teresa, Faby, Sebastian, Calvarons, Adria Font, Nikolaou, Konstantin, Othman, Ahmed E
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2021
Materias:
Immunotherapy Biomarkers
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8603266/
https://www.ncbi.nlm.nih.gov/pubmed/34795006
http://dx.doi.org/10.1136/jitc-2021-003261

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8603266/
https://www.ncbi.nlm.nih.gov/pubmed/34795006
http://dx.doi.org/10.1136/jitc-2021-003261

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