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.

Choline PET/CT features to predict survival outcome in high risk prostate cancer restaging: a preliminary machine-learning radiomics study / 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. - 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]

Choline PET/CT features to predict survival outcome in high risk prostate cancer restaging: a preliminary machine-learning radiomics study

Mapelli, Paola;Picchio, Maria;
2022-01-01

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.
2022
Choline; Positron emission tomography computed tomography; Prostatic neoplasms
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.11768/103688
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