Classification of alzheimer’s disease from MRI using sulcal morphology

Abstract

Alzheimer’s disease (AD), an age-related progressive neurodegenerative disorder, is the most common cause of dementia. It is characterised by abnormal neuroanatomical changes in the brain, some of which can be difficult to distinguish from the alterations caused by normal aging. Sulcal morphology is affected by AD atrophy, indicates significant differences between cognitively normal (CN) and AD subjects, and proves to be a potential AD biomarker. 210 subjects (100 CN, 110 AD) were acquired from the ADNI database. 120 sulci were extracted per subject using BrainVISA sulcal identification pipeline. Mean curvature, surface area and volume were calculated for each sulcus, parameterized by a 3D mesh, and used as AD/CN classification features. 184 subjects were correctly classified (AD=98, CN=86), producing an accuracy of 88%, sensitivity of 89%, specificity of 86%, based on 33 features. Results indicate that sulcal morphology, when based on specific features, could be a valuable AD biomarker.