Performance of Machine Learning and Texture Analysis for Predicting Response to Neoadjuvant Chemoradiotherapy in Locally Advanced Rectal Cancer with 3T MRI

Background: To evaluate the diagnostic performance of a Machine Learning (ML) algorithm based on Texture Analysis (TA) parameters in the prediction of Pathological Complete Response (pCR) to Neoadjuvant Chemoradiotherapy (nChRT) in Locally Advanced Rectal Cancer (LARC) patients. Methods: LARC patien...

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Detalles Bibliográficos
Autores principales: Bellini, Davide, Carbone, Iacopo, Rengo, Marco, Vicini, Simone, Panvini, Nicola, Caruso, Damiano, Iannicelli, Elsa, Tombolini, Vincenzo, Laghi, Andrea
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416446/
https://www.ncbi.nlm.nih.gov/pubmed/36006071
http://dx.doi.org/10.3390/tomography8040173

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9416446/
https://www.ncbi.nlm.nih.gov/pubmed/36006071
http://dx.doi.org/10.3390/tomography8040173

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