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 / M. Ferro, O. de Cobelli, G. Musi, F. Del Giudice, G. Carrieri, G.M. Busetto, U.G. Falagario, A. Sciarra, M. Maggi, F. Crocetto, B. Barone, V.F. Caputo, M. Marchioni, G. Lucarelli, C. Imbimbo, F.A. Mistretta, S. Luzzago, M.D. Vartolomei, L. Cormio, R. Autorino, O.S. Tătaru. - In: THERAPEUTIC ADVANCES IN UROLOGY. - ISSN 1756-2872. - 14:(2022 Jul), pp. 17562872221109020.1-17562872221109020.37. [10.1177/17562872221109020]
Radiomics in prostate cancer: an up-to-date review
M. Ferro
;O. de CobelliSecondo
;G. Musi;F.A. Mistretta;S. Luzzago;
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.File | Dimensione | Formato | |
---|---|---|---|
10.1177_17562872221109020.pdf
accesso aperto
Tipologia:
Publisher's version/PDF
Dimensione
1.09 MB
Formato
Adobe PDF
|
1.09 MB | Adobe PDF | Visualizza/Apri |
Pubblicazioni consigliate
I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.