Purpose A balance between preserving urinary continence as well as sexual potency and
achieving negative surgical margins is of clinical relevance while implementary difficulty …

Background To construct a model based on magnetic resonance imaging (MRI) features
and histological and clinical variables for the prediction of pathology-detected extracapsular …

Simple Summary In approximately 50% of prostate cancer patients undergoing surgical
treatment, cancer has extended beyond the prostate boundary (ie, extraprostatic extension) …

Background Radiomics approaches based on multiparametric MRI (mp‐MRI) have shown
high accuracy in prostate cancer (PCa) management. However, there is a need to apply …

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 …

Purpose To investigate the value of multiparametric magnetic resonance imaging (mpMRI)
for extracapsular extension (ECE) in prostate cancer (PCa). Materials and Methods In all …

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

Objective: To evaluate the diagnostic accuracy of multiparametric MRI (mpMRI) for detecting
extracapsular extension (ECE) in patients with prostate cancer (PCa). Methods and …

Background: To develop a radiomics model based on multiparametric MRI (mpMRI) for
preoperative prediction of extraprostatic extension (EPE) in patients with prostate cancer …

Purpose To investigate and validate the potential role of a radiomics signature in predicting
the side-specific probability of extracapsular extension (ECE) of prostate cancer (PCa) …