Electron Density and Biologically Effective Dose (BED) Radiomics-Based Machine Learning Models to Predict Late Radiation-Induced Subcutaneous Fibrosis

Purpose: to predict the occurrence of late subcutaneous radiation induced fibrosis (RIF) after partial breast irradiation (PBI) for breast carcinoma by using machine learning (ML) models and radiomic features from 3D Biologically Effective Dose (3D-BED) and Relative Electron Density (3D-RED). Method...

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Salvato in:
Dettagli Bibliografici
Pubblicato in:Front Oncol
Autori principali: Avanzo, Michele, Pirrone, Giovanni, Vinante, Lorenzo, Caroli, Angela, Stancanello, Joseph, Drigo, Annalisa, Massarut, Samuele, Mileto, Mario, Urbani, Martina, Trovo, Marco, el Naqa, Issam, De Paoli, Antonino, Sartor, Giovanna
Natura: Artigo
Lingua:Inglês
Pubblicazione: Frontiers Media S.A. 2020
Soggetti:
Oncology
Accesso online:https://ncbi.nlm.nih.gov/pmc/articles/PMC7186445/
https://ncbi.nlm.nih.gov/pubmed/32373520
https://ncbi.nlm.nih.govhttp://dx.doi.org/10.3389/fonc.2020.00490
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