Neuropathologically validated MRI to tau PET synthesis via Covariate-modulated attention networks

Abstract Tau PET is a powerful tool to assess tau pathology in vivo; however, in comparison to MRI, its development is more recent, is rarely available at scale, and substantially more difficult to acquire. Here, we present Covariate-Modulated Attention UNet (CoMA-UNet) to synthesize subject-specific 3D tau PET from T1 MRI while incorporating in the synthesis procedure readily available covariates. Across six external validation datasets, CoMA-UNet reproduced regional patterns of tau PET uptake showing strong agreement with true PET that was generalizable across tracers. Next, we submitted the synthetic tau PET to a series of downstream clinically relevant tasks. First, MMSE associations between the synthetic tau PET were statistically indistinguishable from true PET. Second, the synthetic tau PET achieved out-of-sample diagnostic classification of dementia with an AUROC=0.99. Third, out-of-sample synthetic tau PET tracked longitudinal progression with subject-level slopes closely matching true PET. Fourth, in two independent autopsy cohorts, voxel wise synthetic tau PET images closely followed neuropathologically defined Braak-stages. These findings demonstrate that the novel CoMA-UNet MRI-based synthesis augmented with covariate information can approximate tau PET with sufficient accuracy for downstream scientific and clinical applications. Competing Interest Statement The authors have declared no competing interest. Footnotes ↵† Data used in preparation of this article were obtained from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database (adni.loni.usc.edu). As such, the investigators within the ADNI contributed to the design and implementation of ADNI and/or provided data but did not participate in analysis or writing of this report. A complete listing of ADNI investigators can be found at: http://adni.loni.usc.edu/wp-content/uploads/how_to_apply/ADNI_Acknowledgement_List.pdf