Regional PET may detect early beta-amyloid deposits, areas vulnerable to accumulation
SAN DIEGO — Identifying regions vulnerable to beta-amyloid deposits in younger populations may help predict future accumulation, according to study results presented at the Alzheimer’s Association International Conference.
“Amyloid is known to deposit in the brain as early as 20 years from symptom onset in Alzheimer’s disease dementia,” Emma G. Thibault, BA, from Massachusetts General Hospital and Harvard Medical School, said during her presentation.
Because previous efforts to identify early accumulating regions of amyloid have been based on older adults, Thibault and colleagues sought to identify vulnerable areas in younger adults using positron emission tomography.
Their study included 235 clinically healthy adults, aged 33 to 74 years, from the Framingham Heart Study who underwent one time-point of dynamic Pittsburgh Compound B (PIB) PET scans. Researchers quantified PIB in Desikan regions using distribution volume ratio (DVR) and ran linear and quadratic models (age + age2) to link age with region of interest PIB DVR. They further selected regions of interest with significantly increasing DVRs for the generation of candidate early vulnerable area (EVA) aggregates and generated multiple aggregate EVA DVRs (EVA2-EVA11) by sequential addition of regions in rank order of descending age2 estimate. EVA positivity was determined from both full-sample Gaussian mixture models (GMM) and less-than-45 sample mean+2SD thresholds.
In addition, Thibault and colleagues tested EVA aggregates using an independent cohort of 250 older adults, aged 50 to 92 years, from the Harvard Aging Brain Study (HABS), who were imaged under the same protocol. Researchers then determined sensitivity and specificity of each aggregate at baseline to predict progression to global PIB positivity 3 years later.
According to results, of 35 Desikan regions evaluated, 11 were identified as quadratic age relationships and were used to generate EVA aggregates. Independent validation in baseline global PIB-individuals from HABS revealed that EVA9 and EVA10 were strong predictors of future accumulation. Thresholds based on Gaussian mixture models provided excellent specificity (SP = 1) but weak sensitivity (SE = 0.41) to predict progression to global PIB positivity 3 years later. Conversely, mean+2SD thresholds yielded improved sensitivity but decreased specificity (SE = 0.88, SP = 0.88).
“Modified methods in younger populations may help improve detection based on more focal amyloid,” Thibault said during the presentation. “Taking an extent approach allows spatial flexibility in identifying early amyloid.”