Longitudinal validity of PET‐based staging of regional amyloid deposition

Abstract

Positron emission tomography (PET)‐based staging of regional amyloid deposition has recently emerged as a promising tool for sensitive detection and stratification of pathology progression in Alzheimer's Disease (AD). Here we present an updated methodological framework for PET‐based amyloid staging using region–specific amyloid‐positivity thresholds and assess its longitudinal validity using serial PET acquisitions. We defined region‐specific thresholds of amyloid‐positivity based on Florbetapir‐PET data of 13 young healthy individuals (age ≤ 45y), applied these thresholds to Florbetapir‐PET data of 179 cognitively normal older individuals to estimate a regional amyloid staging model, and tested this model in a larger sample of patients with mild cognitive impairment (N = 403) and AD dementia (N = 85). 2‐year follow‐up Florbetapir‐PET scans from a subset of this sample (N = 436) were used to assess the longitudinal validity of the cross‐sectional model based on individual stage transitions and data‐driven longitudinal trajectory modeling. Results show a remarkable congruence between cross‐sectionally estimated and longitudinally modeled trajectories of amyloid accumulation, beginning in anterior temporal areas, followed by frontal and medial parietal areas, the remaining associative neocortex, and finally primary sensory‐motor areas and subcortical regions. Over 98% of individual amyloid deposition profiles and longitudinal stage transitions adhered to this staging scheme of regional pathology progression, which was further supported by corresponding changes in cerebrospinal fluid biomarkers. In conclusion, we provide a methodological refinement and longitudinal validation of PET‐based staging of regional amyloid accumulation, which may help improving early detection and in‐vivo stratification of pathologic disease progression in AD.

In-Vivo Staging of Regional Amyloid Progression In Healthy Middle Aged To Older People At Risk of Alzheimer’s Disease

“…Similar to our previous staging studies (10,11,17), the current PiB-PET ndings suggest that the estimated amyloid staging model provides a higher sensitivity for early amyloid detection compared to a more conventional binary classi cation of subjects into amyloid-negative or -positive categories. Only 37.5% of the stage I participants were categorized as amyloid-positive by a standard global amyloid threshold proposed for binarization of the 11 C-PiB-PET DVR data (8).…”

“…While this is also consistent with early neuropathological estimates of regional amyloid progression ( 9), other amyloid-PET studies have more consistently pointed to the anterior and posterior cingulate as the earliest amyloid accumulating regions in AD (8, 40,41). Regarding this discrepancy it was hypothesized that the early amyloid-PET signal increases in the temporal lobe may re ect some sort of "physiological" age-related amyloid deposition, whereas amyloid accumulation in anterior and posterior midline structures is more closely associated with progressive AD pathology (17,39).…”

“…Analysis of amyloid-PET scans of young healthy adults who are highly unlikely to exhibit cerebral amyloid deposition demonstrated a considerable variation in regional uptake values (16). This indicates regionally varying noise levels in amyloid-PET signal and argues for the use of region-speci c amyloid-positivity cut-offs in the staging model (17). It was previously reported that global cortical signals of 11 C-PiB-PET and 18 F-based amyloid-PET imaging data obtained from the same individuals were highly correlated (18).…”

Spatial Extent of Amyloid-β Levels and Associations with Alzheimer’s Disease Biomarkers

“…This approach is not always optimal to detect individuals with early Aβ levels, mainly if Aβ has accumulated regionally but is not yet globally widespread 32,47 . There is a growing body of literature documenting the earliest topographical distribution of Aβ-PET binding in individuals with and without cognitive impairment 15,18,49 . We took advantage of this literature to identify seven regions with early detectable Aβ-PET binding, and instead of classifying our participants on a "global" Aβ index, we dichotomized Aβ positivity/negativity within each of these regions and counted the number of regions with positive Aβ-PET binding.…”

The role of APOE in cognitive trajectories and motor decline in Parkinson’s disease

“…Group-based trajectory modeling has been used to summarize the variation pattern and to identify prognostic factors for chronic disease including dementia 6 , 7 , hypertension 8 , diabetes mellitus 9 , chronic kidney disease 10 , and juvenile idiopathic arthritis 11 . Group-based trajectory modeling involves data-driven analysis, rather than using arbitrarily selected thresholds 12 .…”