Abstract

Background
Alzheimer’s disease (AD) is highly related to brain amyloid and tau deposition. PET images evaluate these patterns of amyloid and tau proteinopathy noninvasively. Tau PET is less familiar than amyloid PET to clinicians and researchers, it may occur inter- and intra-observer variability to determine abnormalities in visual rating. We purposed to find optimal thresholds of tau PET, compared with visual assessment, and suggest the most appropriate standard of tau PET assessment using the assist of automated quantitative analysis of PET.

Method
101 participants were enrolled in tau (18F-flortaucipir), amyloid (18F-flutemetamol) PET, and a three-dimension T1-weighted MR image study. Each regional SUVR was calculated using SCALE PET version 1.2 (Neurophet Inc., Seoul, Republic of Korea.). Each regions-of-interest (ROI)-mean SUVR of reference region (whole cerebellum (CW) and cerebellar gray matter (CG)) and quantitative Tau PET positivity was compared with visual rating results of a nuclear medicine physician. We compared accuracy of tau PET positivity driven from 1) total Braak ROI, 2) a priori ROI, and 3) whole cerebral cortical mean SUVR above 1.65 (CW, CG) or 1.30 (CG).

Result
The highest accuracy was observed 0.832 with above 1.65 mean SUVR in a priori ROI using CG reference region. False negative (FN), where participants classified as negative with mean SUVR when visually positive (FN), was 26.7%. These FN participants were mostly identified as borderline patients who were categorized to Braak III/IV (3) or V/VI (24) in visual rating. All the participants classified as tau positive in the quantitative method were amyloid positive while 54.1% were in the tau negative group. Also, the patient group composed of AD and mild cognitive impairment (MCI) participants was 96.3% in positive, behalf 55.4% in negative group. Both visual rating and quantitative classification showed a significant difference between negative and positive groups (p <0.001).

Conclusion
Visual assessment may provide more sensitive outcome than quantitative estimation, i.e., mean SUVR. Our quantitative methods of tau PET showed high accuracy with visual assessment in the regions of early Braak stage, i.e., Braak I/II/III/IV. In the future, there needed to develop more sensitive cutoff values or quantitative methods for tauopathy deposition observation.