The researchers identified the lowest optimal limit values for detecting amyloid (A) accumulation determined by positron emission tomography (PET). These thresholds provide sufficient performance to determine the progression of cognitive decline in individuals with low to moderate A loads. The results of this study were published in Neurology.
The failure of existing therapies for mild cognitive impairment and Alzheimer’s disease (AD) requires earlier intervention to slow or prevent the progression of the disease. The aim of this study was to redefine the Aâ PET threshold based on the lowest threshold that predicts future cognitive decline and Aâ accumulation.
The researchers in this study enrolled clinically normal participants in the Harvard Aging Brain Study (HABS), the Australian Imaging, Biomarkers and Lifestyle (AIBL) study of aging and the Alzheimer’s Disease Neuroimaging Initiative (ADNI). The enrolled participants came from across the AD continuum.
The PACC5 version of the preclinical Alzheimer’s Cognitive Composite (PACC) was used to assess Aâ-related cognitive decline. Sequential Aâ limit values were examined to determine the lowest limit associated with future changes in perception via PACC and Aâ-PET.
The study researchers observed similar optimal breakpoints associated with cognitive decline between HABS at a C-Pittsburgh Compound B (PIB) volume distribution ratio (DVR) of 1.14 (centiloid) [CL]= 17.5), AIBL with a PIB-standardized intake ratio (SUVR) of 1.24 (CL = 15.0) and ADNI with an F-florbetapir (FBP) SUVR of 1.1 (CL = 18.5).
The optimal cutoff across the samples fell between 0.04 and 0.05 SUVR / DVR below the respective cutoff of the Gaussian mixture model. The optimal thresholds associated with Aβ accumulation were the same as the cognitively derived thresholds for HABS and AIBL, with minor differences observed only for ADNI (FBP SUVR 1.09; CL = 16.7).
Regarding constraints, the researchers in this study found that separately modeling possible limit values limited their “ability to estimate the uncertainty in the limit value”.
They concluded that “threshold convergence increases the possibility of simultaneous early changes in Aâ and cognition,” adding that the identified “optimized thresholds may help inform future research and clinical studies aimed at early Aâ” .
Disclosure: Several authors of the study have stated that they are part of the pharmaceutical industry. For a full list of the authors’ information, see the original reference.
Farrell ME, Jiang S., Schultz AP, et al. Define the lowest amyloid PET threshold to predict future cognitive decline and amyloid accumulation. Neurology. Published online on November 16, 2020. doi: 10.1212 / WNL.0000000000011214