English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Plus annual

Presents the access of premium content as premium feature

Premium Content

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools annual

Global: Zendy Free Plan

Global: Zendy Tools monthly

Global: Zendy Plus monthly

The diagnostic landscape of prostate cancer has evolved rapidly, from prostate-specific antigen (PSA) testing to exciting new technologies that allow visualization of the disease, moving away from random sampling to targeted biopsies. Multiparametric magnetic resonance imaging (mpMRI) is a new modality that combines T2-weighted (T2W), diffusion-weighted (DW) and dynamic contrast-enhanced (DCE) sequences, each designed to reveal specific microstructural features typically associated with malignancy such as increased vascularity and cellularity.

Can texture features computed from the joint intensity distribution of different MRI sequences accurately predict prostate cancer grade?