Data driven diagnostic classification in Alzheimer's disease based on different reference regions for normalization...

Positron emission tomography (PET) neuroimaging with the Pittsburgh Compound_B (PiB) is widely used to assess amyloid plaque burden. Standard quantification approaches normalize PiB-PET by mean cerebellar gray matter uptake. Previous studies suggested similar pons and white-matter uptake in Alzheimer's disease (AD) and healthy controls (HC), but lack exhaustive comparison of normalization across the three regions, with data-driven diagnostic classification. We aimed to compare the impact of distinct reference regions in normalization, measured by data-driven statistical analysis, and correlation with cerebrospinal fluid (CSF) amyloid β (Aβ) species concentrations. 243 individuals with clinical diagnosis of AD, HC, mild cognitive impairment (MCI) and other dementias, from the Biomarkers for Alzheimer's/Parkinson's Disease (BIOMARKAPD) initiative were included. PiB-PET images and CSF concentrations of Aβ₃₈, Aβ₄₀ and Aβ₄₂ were submitted to classification using support vector machines. Voxel-wise group differences and correlations between normalized PiB-PET images and CSF Aβ concentrations were calculated. Normalization by cerebellar gray matter and pons yielded identical classification accuracy of AD (accuracy-96%, sensitivity-96%, specificity-95%), and significantly higher than Aβ concentrations (best accuracy 91%). Normalization by the white-matter showed decreased extent of statistically significant multivoxel patterns and was the only method not outperforming CSF biomarkers, suggesting statistical inferiority. Aβ₃₈ and Aβ₄₀ correlated negatively with PiB-PET images normalized by the white-matter, corroborating previous observations of correlations with non-AD-specific subcortical changes in white-matter. In general, when using the pons as reference region, higher voxel-wise group differences and stronger correlation with Aβ₄₂, the Aβ₄₂/Aβ₄₀ or Aβ₄₂/Aβ₃₈ ratios were found compared to normalization based on cerebellar gray matter.