无线电技术
医学
前列腺癌
恶性肿瘤
模式
疾病
人口
癌症
医学物理学
内科学
放射科
社会科学
环境卫生
社会学
作者
Matteo Ferro,O. De Cobelli,Gennaro Musi,Francesco Del Giudice,Giuseppe Carrieri,Gian Maria Busetto,Ugo Giovanni Falagario,Alessandro Sciarra,Martina Maggi,Felice Crocetto,Biagio Barone,Vincenzo Caputo,M. Marchioni,Giuseppe Lucarelli,Ciro Imbimbo,F.A. Mistretta,Stefano Luzzago,Mihai Dorin Vartolomei,Luigi Cormio,Riccardo Autorino,Octavian Sabin Tătaru
标识
DOI:10.1177/17562872221109020
摘要
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.
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