Development and validation of a multiparametric MRI-based radiomics signature for distinguishing between indolent and aggressive prostate cancer.

ABSTRACT:

Objective

To develop and validate a non-invasive MRI-based radiomics signature for distinguishing between indolent and aggressive prostate cancer (PCa) prior to therapy.

Methods

In all, 139 qualified and pathology-confirmed PCa patients were divided into a training set (n = 93) and a validation set (n = 46). A total of 1576 radiomics features were extracted from the T₂WI (n = 788) and diffusion-weighted imaging (n = 788) for each patient. The Select K Best and the least absolute shrinkage and selection operator regression algorithm were used to construct a radiomics signature in the training set. The predictive performance of the radiomics signature was assessed in the training set and then validated in the validation set by rece

SUBMITTER: Zhang L 

PROVIDER: S-EPMC8978240 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature