Sulci characterization to predict progression from mild cognitive impairment to Alzheimer's disease

摘要

Patients who develop Alzheimer's disease (AD) have passed through a prodromal stage called mild cognitiveimpairment (MCI) but, not every MCI patient will develop AD. Structural magnetic resonance imaging (MRI)has the potential to capture the differences between the groups of MCI: patients who converted to dementia dueto AD (MCIc) and those who remained stable (MCInc). Sulci and folding structures are affected due to theneurodegenerarive nature of AD. A characterization method for these structures is proposed by performing amulti-spherical mapping and a curvelet decomposition at different levels of the brain. 829 MCI subjects fromthe ADNI initiative were studied at 24, 36 and 60 months of conversion. A random forest classification modelwas used to validate the methodology achieving an AUC = 0:77 with high-dimensional feature vectors andAUC = 0:70 when 5% of the features are selected. This suggests discriminating differences in sulci and gyridepth between non-converters and converters to AD.