Sample size requirement for achieving multisite harmonization using structural brain MRI features.

ABSTRACT: When data is pooled across multiple sites, the extracted features are confounded by site effects. Harmonization methods attempt to correct these site effects while preserving the biological variability within the features. However, little is known about the sample size requirement for effectively learning the harmonization parameters and their relationship with the increasing number of sites. In this study, we performed experiments to find the minimum sample size required to achieve multisite harmonization (using neuroHarmonize) using volumetric and surface features by leveraging the concept of learning curves. Our first two experiments show that site-effects are effectively removed in a univariate and multivariate manner; however, it is essential to regress the effect of covariates from t

SUBMITTER: Parekh P 

PROVIDER: S-EPMC7615107 | biostudies-literature | 2022 Dec

REPOSITORIES: biostudies-literature