Prostate cancer (PCa) is the most common worldwide diagnosed malignancy in male
population. The diagnosis, the identification of aggressive disease, and the post-treatment …

Advances in our understanding of the role of magnetic resonance imaging (MRI) for the
detection of prostate cancer have enabled its integration into clinical routines in the past two …

Radiomics and genomics represent two of the most promising fields of cancer research,
designed to improve the risk stratification and disease management of patients with prostate …

Prostate cancer (PCa) is one of the most frequently diagnosed malignancies of men in the
world. Due to a variety of treatment options in different risk groups, proper diagnostic and …

Objectives To build a machine learning (ML) model to detect extraprostatic extension (EPE)
of prostate cancer (PCa), based on radiomics features extracted from prostate MRI index …

Multiparametric magnetic resonance imaging (mpMRI) is an indispensable tool in the
clinical workflow for the diagnosis and treatment planning of various diseases. Machine …

Multiparametric prostate magnetic resonance imaging (mpMRI) is widely used as a triage
test for men at a risk of prostate cancer. However, the traditional role of mpMRI was confined …

Background Preoperative prediction of extracapsular extension (ECE) of prostate cancer
(PCa) is important to guide clinical decision‐making and improve patient prognosis …

Objectives Extraprostatic extension (EPE) of prostate cancer (PCa) is predicted using clinical
nomograms. Incorporating MRI could represent a leap forward, although poor sensitivity and …

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 …