We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: “(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)” have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts.

Ghezzo, S., Bezzi, C., Presotto, L., Mapelli, P., Bettinardi, V., Savi, A., et al. (2022). State of the art of radiomic analysis in the clinical management of prostate cancer: A systematic review. CRITICAL REVIEWS IN ONCOLOGY HEMATOLOGY, 169(January 2022) [10.1016/j.critrevonc.2021.103544].

State of the art of radiomic analysis in the clinical management of prostate cancer: A systematic review

Presotto L.;Mapelli P.;Preza E.;Scifo P.;
2022

Abstract

We present the current clinical applications of radiomics in the context of prostate cancer (PCa) management. Several online databases for original articles using a combination of the following keywords: “(radiomic or radiomics) AND (prostate cancer or prostate tumour or prostate tumor or prostate neoplasia)” have been searched. The selected papers have been pooled as focus on (i) PCa detection, (ii) assessing the clinical significance of PCa, (iii) biochemical recurrence prediction, (iv) radiation-therapy outcome prediction and treatment efficacy monitoring, (v) metastases detection, (vi) metastases prediction, (vii) prediction of extra-prostatic extension. Seventy-six studies were included for qualitative analyses. Classifiers powered with radiomic features were able to discriminate between healthy tissue and PCa and between low- and high-risk PCa. However, before radiomics can be proposed for clinical use its methods have to be standardized, and these first encouraging results need to be robustly replicated in large and independent cohorts.
Articolo in rivista - Review Essay
Clinical management; CT; MRI; PET; Prostate cancer; Radiomics;
English
Ghezzo, S., Bezzi, C., Presotto, L., Mapelli, P., Bettinardi, V., Savi, A., et al. (2022). State of the art of radiomic analysis in the clinical management of prostate cancer: A systematic review. CRITICAL REVIEWS IN ONCOLOGY HEMATOLOGY, 169(January 2022) [10.1016/j.critrevonc.2021.103544].
Ghezzo, S; Bezzi, C; Presotto, L; Mapelli, P; Bettinardi, V; Savi, A; Neri, I; Preza, E; Samanes Gajate, A; De Cobelli, F; Scifo, P; Picchio, M
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/381177
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