Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.

Radiomics in prostate cancer: an up-to-date review / Ferro, Matteo; de Cobelli, Ottavio; Musi, Gennaro; Del Giudice, Francesco; Carrieri, Giuseppe; Busetto, Gian Maria; Falagario, Ugo Giovanni; Sciarra, Alessandro; Maggi, Martina; Crocetto, Felice; Barone, Biagio; Caputo, Vincenzo Francesco; Marchioni, Michele; Lucarelli, Giuseppe; Imbimbo, Ciro; Mistretta, Francesco Alessandro; Luzzago, Stefano; Vartolomei, Mihai Dorin; Cormio, Luigi; Autorino, Riccardo; Tătaru, Octavian Sabin. - In: THERAPEUTIC ADVANCES IN UROLOGY. - ISSN 1756-2872. - 14:(2022). [10.1177/17562872221109020]

Radiomics in prostate cancer: an up-to-date review

Del Giudice, Francesco;Busetto, Gian Maria;Sciarra, Alessandro;Maggi, Martina;Lucarelli, Giuseppe;
2022

Abstract

Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male population. The diagnosis, the identification of aggressive disease, and the post-treatment follow-up needs a more comprehensive and holistic approach. Radiomics is the extraction and interpretation of images phenotypes in a quantitative manner. Radiomics may give an advantage through advancements in imaging modalities and through the potential power of artificial intelligence techniques by translating those features into clinical outcome prediction. This article gives an overview on the current evidence of methodology and reviews the available literature on radiomics in PCa patients, highlighting its potential for personalized treatment and future applications.
2022
MRI; PET-CT; artificial intelligence; prostate cancer; radiomics
01 Pubblicazione su rivista::01g Articolo di rassegna (Review)
Radiomics in prostate cancer: an up-to-date review / Ferro, Matteo; de Cobelli, Ottavio; Musi, Gennaro; Del Giudice, Francesco; Carrieri, Giuseppe; Busetto, Gian Maria; Falagario, Ugo Giovanni; Sciarra, Alessandro; Maggi, Martina; Crocetto, Felice; Barone, Biagio; Caputo, Vincenzo Francesco; Marchioni, Michele; Lucarelli, Giuseppe; Imbimbo, Ciro; Mistretta, Francesco Alessandro; Luzzago, Stefano; Vartolomei, Mihai Dorin; Cormio, Luigi; Autorino, Riccardo; Tătaru, Octavian Sabin. - In: THERAPEUTIC ADVANCES IN UROLOGY. - ISSN 1756-2872. - 14:(2022). [10.1177/17562872221109020]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1654242
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