Probabilistic estimation for across-batch compatibility enhancement for amyloid PET.

Introduction: It is necessary to accurately account for systematic differences due to variability in scanners, radiotracers, and acquisition protocols in multisite studies combining amyloid imaging data.

Methods: We propose Probabilistic Estimation for Across-batch Compatibility Enhancement (PEACE), a fully Bayesian multimodal extension of the widely used ComBat harmonization model, and we apply it to harmonize regional amyloid positron emission tomography data from two scanners.

Results: Simulations show that PEACE recovers true harmonized values better than ComBat, even for unimodal data. PEACE harmonization of multiscanner regional amyloid imaging data yields results that agree better with longitudinal data compared to ComBat, without removing the known biological effects of age or apolipoprotein E genotype.

Discussion: PEACE outperforms ComBat in both unimodal and bimodal contexts, is applicable to multisite amyloid imaging data, and holds promise for the harmonization of other neuroimaging data over ComBat.

Highlights: We introduce PEACE, a fully Bayesian multimodal extension of ComBat harmonization.Simulations show that PEACE recovers true harmonized values better than ComBat.PEACE accurately harmonizes multiscanner regional amyloid imaging data.