Integrating biparametric MRI radiomics with clinical variables improves pre-treatment prediction of prostate cancer recurrence

IntroductionRadiomics can quantify intratumoral heterogeneity on MRI, providing complementary information beyond clinical predictors. This study aimed to evaluate whether integrating radiomic features from pre-operative biparametric MRI (bpMRI) with standard clinical variables improves pre-treatment...

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Bibliografische gegevens

Hoofdauteurs:	Selma Bozorgpana, Indri Desiati, Mohammed R. S. Sunoqrot, Petter Davik, Guro F. Giskeødegård, Gabriel Addio Nketiah, Mattijs Elschot, May-Britt Tessem, Tone F. Bathen
Formaat:	Artigo
Taal:	Inglês
Gepubliceerd in:	Frontiers Media S.A. 2026-07-01
Reeks:	Frontiers in Oncology
Onderwerpen:	biochemical recurrence biparametric MRI machine learning prostate neoplasms radiomics risk prediction
Online toegang:	https://www.frontiersin.org/articles/10.3389/fonc.2026.1812805/full
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