Tau-PET abnormality change along with Alzheimer’s disease: a topological perspective

Abstract Background: Tau PET imaging is an important biomarker for studying the progression of Alzheimer’s disease. The most commonly utilized quantification index in tau-PET is the standardized uptake value ratio (SUVR). Topological information derived from different brain regions has also been linked to tau pathology. However, previous studies on PET-based brain functional connectivity were mostly conducted at the group level. Methods: We propose to explore the change of tau deposition from a topological perspective across different neurocognitive levels of dementia both at the individual and group levels. We have developed a method for building subject-level tau networks to investigate the correlations between brain regions. We included 18F-flortaucipir scans of participants diagnosed with cognitive normal (CN), early mild cognitive impairment (EMCI), late mild cognitive impairment (LMCI), and Alzheimer’s disease from the ADNI database. Each scan was used to build a covariance network using SUVR at regions of interest (ROIs). Topological segregation and integration information was extracted and linked to disease progression. We then extracted seven functional clusters from each subject's covariance network and analyzed the connectivity strength for each: medial temporal lobe (MTL), cognitive control, executive control, default mode (DMN), visual (VIS), somatomotor, and language. Clusters with significant change over disease progression were identified. Two converted individuals with insignificant SUVR change were then investigated from a topological perspective. Results: Overall, topological data analysis outperformed conventional composite SUVR from signature brain regions. Connectivity strength with functional clusters can provide more accurate staging than SUVR (P<0.01), and the longitudinal change is associated better with future disease development at the subject level. MTL, DMN and VIS were identified as hubs vulnerable to early disease conversion before mild cognitive impairment. The main findings from ADNI were replicated in an independent cohort HABS. Conclusions: The proposed method can potentially monitor Alzheimer’s disease progression at the subject level, in contrast to group-based approaches, which has great potential in monitoring disease progression and response to treatment.