A Framework of Analysis to Facilitate the Harmonization of Multicenter Radiomic Features in Prostate Cancer

ABSTRACT: Pooling radiomic features coming from different centers in a statistical framework is challenging due to the variability in scanner models, acquisition protocols, and reconstruction settings. To remove technical variability, commonly called batch effects, different statistical harmonization strategies have been widely used in genomics but less considered in radiomics. The aim of this work was to develop a framework of analysis to facilitate the harmonization of multicenter radiomic features extracted from prostate T2-weighted magnetic resonance imaging (MRI) and to improve the power of radiomics for prostate cancer (PCa) management in order to develop robust non-invasive biomarkers translating into clinical practice. To remove technical variability and correct for batch effects, we investi

SUBMITTER: Castaldo R 

PROVIDER: S-EPMC9821561 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature