Generalized ComBat harmonization methods for radiomic features with multi-modal distributions and multiple batch effects.

ABSTRACT: Radiomic features have a wide range of clinical applications, but variability due to image acquisition factors can affect their performance. The harmonization tool ComBat is a promising solution but is limited by inability to harmonize multimodal distributions, unknown imaging parameters, and multiple imaging parameters. In this study, we propose two methods for addressing these limitations. We propose a sequential method that allows for harmonization of radiomic features by multiple imaging parameters (Nested ComBat). We also employ a Gaussian Mixture Model (GMM)-based method (GMM ComBat) where scans are split into groupings based on the shape of the distribution used for harmonization as a batch effect and subsequent harmonization by a known imaging parameter. These two methods were eval

SUBMITTER: Horng H 

PROVIDER: S-EPMC8927332 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature