Although there is no cure for Alzheimer’s disease, being able to make an early diagnosis can nevertheless significantly help patients, by enabling them to access professional help and support, treatment to manage the symptoms and, also enabling them to plan for the future. Being able to accurately identify patients at an early stage of the disease also allows research teams to better identify brain changes early in the disease. Although most people with Alzheimer’s develop the disease after the age of 65, the disease is more and more frequently diagnosed in younger people, in whom early interventions will considerably slow down its progression.
A single brain scan is enough
Doctors currently use a range of tests to diagnose Alzheimer’s disease, including memory and cognitive tests and brain scans. The scans are used to assess the presence of protein deposits in the brain and shrinkage of the hippocampus, the area of the brain linked to memory. All of these tests can take several weeks.
The new approach requires only one magnetic resonance imaging (MRI) brain scan performed on a standard 1.5 Tesla machine, commonly found in most hospitals. The researchers developed an algorithm based on
660 different characteristics for 115 brain regions.
Among this data are the size, shape and texture of each region. The algorithm can identify abnormalities in these characteristics, which makes it possible to accurately predict the existence of Alzheimer’s disease. Tested on brain scans of more than 400 patients with early and late-stage Alzheimer’s disease, healthy controls, and patients with other neurological conditions, including frontotemporal dementia and Parkinson’s disease, the approach demonstrates its ability to detect and its accuracy. The new system can also spot changes in areas of the brain not previously associated with Alzheimer’s disease, including the cerebellum (the part of the brain that coordinates and regulates physical activity) and the diencephalon. ventral (related to the senses, sight and hearing) – which opens new avenues of research on the etiology of Alzheimer’s disease.
Then tested from data from more than 80 patients undergoing diagnostic testing for Alzheimer’s disease at Imperial College Healthcare, the diagnosis confirms its effectiveness:
- in 98% of cases, the automatic learning system based on MRI data makes it possible to predict, on its own and with precision, whether or not the patient has Alzheimer’s disease;
- moreover, the system makes it possible to distinguish between the early and advanced stages of Alzheimer’s disease with a fairly high precision, in 79% of patients.
Lead author Prof Eric Aboagye, from Imperial’s Department of Surgery and Cancer, comments on these findings: “Currently, no other simple and widely available method can predict Alzheimer’s disease with this level of accuracy. It is therefore an important step forward. Many patients who present with Alzheimer’s disease to memory clinics also have other neurological disorders, but even within this group, our system can distinguish ‘Alzheimer’ patients from other patients.
Finally, this system also makes it possible to shorten the wait for a diagnosis, a painful experience for patients and their families.