Background: Prognosis for Alzheimer’s disease is difficult, with rates of disease progression varying widely. Despite the extensive use of clinical dementia severity assessment scales to determine dementia diagnosis and to monitor progression, there is no consensus on which imaging factors may accurately predict future decline trajectories on these measures. Determination of baseline imaging patterns that are related to slower, or faster, decline rates could be used to identify those at highest risk of worse outcomes and inform care planning.
Method: Decline trajectories were estimated from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset which contains clinical, imaging, and biological assessment records for 1,736 patients followed-up over 8 years at 3, 6, or 12 month intervals. Clusters of similar decline trajectories were identified for patients with relevant baseline fluorodeoxyglucose positron emission tomography (FDG-PET) imaging data (N=530) using mini-mental state examination (MMSE), clinical dementia rating sum of boxes (CDR-SB), Alzheimer’s disease assessment scale (ADAS-13), and functional activities questionnaire (FAQ) assessment scores. Decline trajectories allocated to slow, intermediate, and fast clusters were further analysed to find significant associations with PET imaging features using statistical parametric mapping (SPM12).
Results: When compared to cognitively normal non-decliners, slow, intermediate and fast cluster groups showed similar topographic patterns of hypometabolism on FDG-PET for all four clinical assessments (p<0.05 family-wise error corrected). Slow progressors showed focal hippocampal hypometabolism, which extended into parietotemporal, inferior parietal and precuneal regions for intermediate progressors. Fast progressors showed more extensive hypometabolism in similar regions with additional superior frontal hypometabolism. Although locational deficits were similar on cognitive measures for decline groups, CDR-SB showed the greatest hypometabolism extent for slow progressors, followed by FAQ, then ADAS-13, with MMSE showing the least.
Conclusion: Our results suggest a single pattern of pathological progression of functional degeneration in Alzheimer’s disease, with slow, intermediate and fast progressors at different time points on the same decline trajectory. This progression begins with focal medial temporal regional abnormalities, extending to parietotemporal, inferior parietal and precuneus regions, before finally involving the superior frontal lobe. CDR-SB was the most sensitive in detecting slow progressor abnormality, with MMSE being the least sensitive.