Background Radiomics or computer‐extracted texture features derived from MRI have been
shown to help quantitatively characterize prostate cancer (PCa). Radiomics have not been …

Background: To identify multiparametric magnetic resonance imaging (mp-MRI)-based
radiomics features as prognostic factors in patients with localized prostate cancer after …

Background: Prostate cancer (PCa) influences its surrounding habitat, which tends to
manifest as different phenotypic appearances on magnetic resonance imaging (MRI). This …

Background Multiparametric MRI (mp‐MRI) combined with machine‐aided approaches
have shown high accuracy and sensitivity in prostate cancer (PCa) diagnosis. However …

Purpose To evaluate the role of a 3T biparametric magnetic resonance imaging (bpMRI), T2‐
weighted imaging, and three separate diffusion‐weighted imaging acquisitions combined …

Purpose To investigate the efficiency of radiomics signature in discriminating between
benign and malignant prostate lesions with similar biparametric magnetic resonance …

Background Gleason score (GS) is a histologic prognostic factor and the basis of treatment
decision‐making for prostate cancer (PCa). Treatment regimens between lower‐grade …

OBJECTIVE To assess the role of multiparametric magnetic resonance imaging (mp‐MRI) of
the prostate in evaluating local recurrence of prostate cancer, using transperineal template …

Radiomics is an emerging field of image analysis with potential applications in patient risk
stratification. This study developed and evaluated machine learning models using …

OBJECTIVE. The purpose of this study is to retrospectively investigate whether pretreatment
multiparametric MRI findings can predict biochemical recurrence in patients who underwent …