Correlation of Global and Regional Amyloid Burden by 18 F-Florbetaben PET/CT With Cognitive Impairment Profile and Severity.

PURPOSE: To assess the correlation between profile and severity deterioration in the neuropsychological assessment and the most affected regions in amyloid PET semiquantification. The influence of vascular risk and other potential confounding factors was also evaluated. METHODS: A retrospective, observational, and multicenter study including all patients referred for amyloid PET in daily practice was conducted. Patients underwent neuropsychological assessment, and cognitive decline severity and domain(s) affected were recorded. The patients were grouped according to cognitive impairment (CI) profile and severity: (A) no CI, single-domain amnestic CI, multiple-domain amnestic CI, and nonamnestic CI; and (B) mild CI, moderate and severe dementia. An adapted Framingham Stroke Risk Profile was calculated for each individual. Depression and parkinsonism were also recorded. Standardized quantitative analysis software was used to obtain standardized uptake value ratio (SUVR) values from PET/CT images. The corresponding associations were assessed with the most appropriate statistical tests. RESULTS: One hundred twenty-nine patients were included (62 men, 67 women; 64.67 ± 7.47 years old). Significant differences in global and regional amyloid load were exclusively found in women between non-CI and moderate dementia ( P = 0.006, for total-cerebellum SUVR). Posterior and anterior cingulates and prefrontal cortex best represented CI severity ( P = 0.003, 0.006, and 0.006, respectively). No relationship between the CI profile and the regional amyloid load was shown. A significantly high positive correlation was found between age and vascular risk and between these variables and amyloid load in nearly all regions, especially in women with moderate dementia. CONCLUSION: Semiquantitative analysis of amyloid PET by SUVR values revealed a significant correlation between amyloid burden and CI severity, although only in women.

Increasing the confidence of 18F-Florbetaben PET interpretations: Machine learning quantitative approximation.

AIM: To assess the added value of semiquantitative parameters on the visual assessment and to study the patterns of 18F-Florbetaben brain deposition. MATERIALS AND METHODS: Retrospective analysis of multicenter study performed in patients with mild cognitive impairment or dementia of uncertain origin. 18F-Florbetaben PET scans were visually interpreted by two experienced observers, analyzing target regions in order to calculate the interobserver agreement. Semiquantification of all cortical regions with respect to three reference regions was performed to obtain standardized uptake value ratios (SUVRs). The ability of SUVRs to predict the visual evaluation, the possibility of preferential radiotracer deposition in some target regions and interhemisphere differences were analyzed. RESULTS: 135 patients were evaluated. In the visual assessment, 72 were classified as positive. Interobserver agreement was excellent. All SUVRs were significantly higher in positive PET scans than in negative ones. Prefrontal area and posterior cingulate were the cortical regions with the best correlations with the visual evaluation, followed by the composite region. Using ROC analysis, the SUVRs obtained in same target locations showed the best diagnostic performance. CONCLUSIONS: The derived information from target regions seems to help the visual classification, based on a preferential amyloid ß deposit, allowing machine learning. The amyloid ß deposit, although diffuse in all cortical regions, seems not to be uniform and symmetric.