What’s the cut-point?: a systematic investigation of tau PET thresholding methods

Abstract

Background Tau positron emission tomography (PET) is increasing in popularity for biomarker characterization of Alzheimer’s disease (AD), and recent frameworks rely on tau PET cut-points to stage individuals along the AD continuum. Given the lack of standardization in tau PET thresholding methods, this study sought to systematically canvass and characterize existing studies that have derived tau PET cut-points and then directly assess different methods of tau PET thresholding in terms of their concurrent validity. Methods First, a literature search was conducted in PubMed to identify studies of AD and related clinical phenotypes that used the Flortaucipir (AV-1451) tau PET tracer to derive a binary cut-point for tau positivity. Of 540 articles screened and 47 full-texts reviewed, 23 cohort studies met inclusion criteria with a total of 6536 participants. Second, we derived and compared tau PET cut-points in a 2 × 2 × 2 design that systematically varied region (temporal meta-ROI and entorhinal cortex), analytic method (receiver operating characteristics and 2 standard deviations above comparison group), and criterion/comparison variable (amyloid-beta negative cognitively unimpaired or cognitively unimpaired only) using a sample of 453 older adults from the Alzheimer’s Disease Neuroimaging Initiative. Results For the systematic review, notable variability in sample characteristics, preprocessing methods, region of interest, and analytic approach were observed, which were accompanied by discrepancy in proposed tau PET cut points. The empirical follow-up indicated the cut-point derived based on 2 standard deviations above a either comparison group in either ROI best differentiated tau positive and negative groups on cerebrospinal fluid phosphorylated tau, Mini-Mental State Examination score, and delayed memory performance. Conclusions Given the impact of discrepant thresholds on tau positivity rates, biomarker staging, and eligibility for future clinical treatment trials, recommendations are offered to select cut-point derivations based on the unique goals and priorities of different studies.

Associations between different tau-PET patterns and longitudinal atrophy in the Alzheimer’s disease continuum: biological and methodological perspectives from disease heterogeneity

“…Tau-PET patterns on the discrete scale may be influenced by the relatively lenient cutpoints used in our study. Given the large range of tau-PET cutpoints reported in the literature, future studies should focus on continuous characterization where possible or apply standardized thresholds [ 58 ]. Although we tracked the longitudinal atrophy changes relative to baseline tau pathology, we could not assess longitudinal tau-PET changes due to the limited samples of longitudinal tau-PET in the ADNI.…”

Role of Enlarged Perivascular Space in the Temporal Lobe in Cerebral Amyloidosis

“…Participant‐specific volume of interest (VOI) images with the subcortical and cortical regions were obtained by processing magnetic resonance (MR) images using FreeSurfer 5.3 (Massachusetts General Hospital, Harvard Medical School; http://surfer.nmr.mgh.harvard.edu), 27 which was coregistered to individual MR images within the FreeSurfer surface. A/T/N status was determined by applying a validated method as reported previously (see Supplementary Method 4 for details) 28–32 …”

“…A/T/N status was determined by applying a validated method as reported previously (see Supplementary Method 4 for details). [28][29][30][31][32]…”

Should artificial intelligence be used in conjunction with Neuroimaging in the diagnosis of Alzheimer’s disease?

“…A study found cognitively unimpaired individuals positive for tau and amyloid were at high risk for cognitive decline in the short term, with tau burden in the MTL and neocortex region displaying a substantial additional risk (Ossenkoppele et al, 2022). Despite its utility, limitations of tau imaging include reports of in vivo off-target binding (Smith et al, 2022), variability of thresholds for tau positivity rates between studies (Weigand et al, 2022), and similarly as with amyloid, a positive tau marker alone is not sufficient for an AD diagnosis.…”