There’s no doubt that getting a diagnosis quickly at an early stage can help Alzheimer’s patients. It allows them to access help and support, get treatment to manage their symptoms, and plan for the future.
Being able to accurately identify patients at an early stage of the disease will also help researchers understand the brain changes that trigger the disease and prepare the ground for trials of new treatments.
New research by Imperial College London has come up with a single MRI brain scan that could be enough to diagnose Alzheimer’s.
The research looks at structural features within the brain, including regions not previously linked to the disease. The advantage of the new technique is its simplicity and the fact that it can identify the disease at an early stage when it can be very difficult to diagnose.
At the present time a raft of tests is done to diagnose Alzheimer’s, which include memory and cognitive tests and brain scans which can take several weeks. Imperial College London’s approach requires just one of these – a standard magnetic resonance imaging (MRI) brain scan taken on a standard machine found in most hospitals.
The researchers divided the brain into 115 regions and 660 different features, such as size, shape and texture, to assess each region.
They then trained an algorithm to identify changes which could accurately predict the existence of the disease. The team tested their approach on brain scans from over 400 patients with early and later stage Alzheimer’s, healthy controls, and patients with other neurological conditions.
They also tested it with data from over 80 patients undergoing diagnostic tests for Alzheimer’s at the Imperial College Healthcare NHS Trust. They found in 98% of cases, the MRI-based machine learning system alone could accurately predict whether the patient had Alzheimer’s disease or not.
It was also able to distinguish between early and late-stage Alzheimer’s with fairly high accuracy, in 79% of patients.
Professor Eric Aboagye, from Imperial’s Department of Surgery and Cancer, who led the research, said: “Currently no other simple and widely available methods can predict Alzheimer’s disease with this level of accuracy, so our research is an important step forward.
“Waiting for a diagnosis can be horrible for patients and families. If we could cut down the amount of time they have to wait, make diagnosis a simpler process and reduce uncertainty that would help a great deal.
“Our new approach could also identify early-stage patients for clinical trials of new drug treatments or lifestyle changes, which is currently very hard to do.”