MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance.

ABSTRACT: Nearly half of patients with prostate cancer (PCa) harbour low- or intermediate-risk disease considered suitable for active surveillance (AS). However, up to 44% of patients discontinue AS within the first five years, highlighting the unmet clinical need for robust baseline risk-stratification tools that enable timely and accurate prediction of tumour progression. In this proof-of-concept study, we sought to investigate the added value of MRI-derived radiomic features to standard-of-care clinical parameters for improving baseline prediction of PCa progression in AS patients. Tumour T₂-weighted imaging (T2WI) and apparent diffusion coefficient radiomic features were extracted, with rigorous calibration and pre-processing methods applied to select the most robust features for pred

SUBMITTER: Sushentsev N 

PROVIDER: S-EPMC8217549 | biostudies-literature | 2021 Jun

REPOSITORIES: biostudies-literature