Choline PET/CT features to predict survival outcome in high risk prostate cancer restaging: a preliminary machine-learning radiomics study
Articolo
Data di Pubblicazione:
2022
Citazione:
Choline PET/CT features to predict survival outcome in high risk prostate cancer restaging: a preliminary machine-learning radiomics study / Alongi, P., Laudicella, R., Stefano, A., Caobelli, F., Comelli, A., Vento, A., Sardina, D., Ganduscio, G., Toia, P., Ceci, F., Mapelli, P., Picchio, M., Midiri, M., Baldari, S., Lagalla, R., Russo, G.. - In: THE QUARTERLY JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING. - ISSN 1827-1936. - 66:4(2022), pp. 352-360. [10.23736/S1824-4785.20.03227-6]
Abstract:
Radiomic features are increasingly utilized to evaluate tumor heterogeneity in PET imaging but to date its role has not been investigated for Cho-PET in prostate cancer. The potential application of radiomics features analysis using a machine-learning radiomics algorithm was evaluated to select 18F-Cho PET/CT imaging features to predict disease progression in PCa.
Tipologia CRIS:
1.1 Articolo in rivista
Elenco autori:
Alongi, Pierpaolo; Laudicella, Riccardo; Stefano, Alessandro; Caobelli, Federico; Comelli, Albert; Vento, Antonio; Sardina, Davide; Ganduscio, Gloria; Toia, Patrizia; Ceci, Francesco; Mapelli, Paola; Picchio, Maria; Midiri, Massimo; Baldari, Sergio; Lagalla, Roberto; Russo, Giorgio
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