ComBatLS: A location- and scale-preserving method for multi-site image harmonization

COEX 

Recent work has leveraged massive datasets and advanced image harmonization algorithms to construct normative models of imaging-derived phenotypes (IDPs)[1,2]. These brain chart models, which can produce centile or z-scores to benchmark individuals' morphology within a population, are often fit on magnetic resonance imaging data collected across hundreds of scanners. One popular method for harmonizing these data is ComBat, which preserves the effects of specified covariates on the IDPs' means. However, evidence suggests that biological factors, such as sex, also impact an IDP's variance across a population[3]. These scale effects, which directly impact centile and z-score distributions, are not preserved by current harmonization methods. Thus, harmonization may induce error in centile and z-scores, particularly when factors that impact scale are distributed unequally across sites.

Here, we propose a new method in the ComBat family of harmonization tools, ComBatLS, that preserves biological variance in IDPs' location and scale. We tested ComBatLS's ability to preserve variation in scale and its impacts on centile and z-scores by harmonizing across sex-imbalanced artificial "sites" in data from the UK Biobank.