Can a Single Brain Scan Accurately Diagnose Alzheimer's?
A machine learning algorithm can determine whether an individual has Alzheimer's disease (AD) based on a single MRI scan with 98% accuracy, new research suggests. Many patients who present with Alzheimer's at memory clinics do also have other neurological conditions, but even within this group our system could pick out those patients who had Alzheimer's from those who did not. To develop the algorithm, Aboagye and colleagues divided the brain into 115 regions and allocated 660 different features, such as size, shape, and texture, to assess each region. They trained the algorithm to identify where changes to these features could accurately predict AD. Using data from the Alzheimer's Disease Neuroimaging Initiative (ADNI), the team tested their algorithm on brain scans from more than 400 patients with early and later stage AD, healthy controls, and patients with other neurologic conditions, including frontotemporal dementia and Parkinson's disease.
@bipasha In 98% of cases, the MRI-based machine learning tool alone could accurately predict whether an individual had AD, outperforming standard hippocampal volume and cerebrospinal fluid (CSF) amyloid-beta measurements. It could also distinguish between early- and late-stage AD in 79% of patients. The tool was "robust and repeatable across MRI scans, demonstrating its potential for applicability in clinical practice in the future," the researchers write.