Keywords: Preclinical Image Analysis, Alzheimer's Disease, Asymptomatic Stage; Cognitive Decline; Progression Prediction;
Motivation: Predicting the conversion from cognitive normal to mild cognitive impairment (MCI) at the asymptomatic stage is challenging.
Goal(s): To investigate whether longitudinal alteration in brain structure can provide valuable information for normal-to-MCI conversion prediction.
Approach: We conducted a 7-year longitudinal study on 222 community-dwelling elderly and built a two-stage intelligent prediction model to establish the mapping relationship from the baseline to 7-year changes, using brain T1 MRI scans and comprehensive neuropsychological tests.
Results: The model, with forecasted 7-year changed features, achieved promising conversion predictions (accuracy=73.8%). Cortical thickness changes, particularly in the visual and default mode cortices, played a significant role in prediction.
Impact: Long-term (7-year) brain cortical changes could be predicted and further used to help disease progression prediction for community elderly. Leveraging pre-built predictive model, physicians can evaluate the progression risk at the preclinical phase, well before the onset of Alzheimer's disease.
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