dementia
dementia. abstract silhouette of human head with simbol of mental illness

While there is currently no cure for Alzheimer’s disease (AD) and few drugs have had clinical efficacy in slowing progression, early detection is still a high priority to help manage the disease appropriately. Now, a new study by investigators at the Mallinckrodt Institute of Radiology within the Washington University School of Medicine in St. Louis (WUSM), has shown that MRI brain scans perform better than common clinical tests at predicting which people will go on to develop Alzheimer’s disease—a disease affecting 5.5 million Americans. Findings from this new study were presented recently at the annual meeting of the Radiological Society of North America (RSNA) through a presentation entitled “Tract-Based Spatial Statistics in Persons who Will Develop Alzheimer’s Dementia: A Study from the Alzheimer’s Disease Neuroimaging Initiative (ADNI).”

“Alzheimer’s disease is the most common cause of dementia in the world and is expected to increase globally, and especially in the U.S., as the population gets older,” explained lead study investigator Cyrus Raji, M.D., Ph.D., assistant professor of radiology at the Mallinckrodt Institute of Radiology at WUSM. “As we develop new drug therapies and study them in trials, we need to identify individuals who will benefit from these drugs earlier in the course of the disease.”

Common predictive models like standardized questionnaires used to measure cognition and tests for the APOE4 gene, a gene variant associated with a higher risk of AD, have limitations and—with accuracy rates of about 70–71%—fail to identify many people who go on to develop the disease. However, in recent years, researchers have turned to MRI exams of the brain using diffusion tensor imaging (DTI), a promising option for analysis of dementia risk. These exams assess the condition of the brain’s white matter.

“With DTI you look at the movement of water molecules along white matter tracts, the telephone cables of the brain,” Raji remarked. “When these tracts are not well connected, cognitive problems can result.”

DTI provides different metrics of white matter integrity, including fractional anisotropy (FA), a measure of how well water molecules move along white matter tracts. A higher FA value indicates that water is moving in a more orderly fashion along the tracts, while a lower value means that the tracts are likely damaged.

In the current study, the researchers set out to quantify differences in DTI in people who decline from normal cognition or mild cognitive impairment to Alzheimer’s dementia compared to controls who do not develop dementia. They performed brain DTI exams on 61 people drawn from the Alzheimer’s Disease Neuroimaging Initiative, a major, multisite study focusing on the progression of the disease.

Roughly half of the patients went on to develop Alzheimer’s disease, and DTI identified quantifiable differences in the brains of those patients. People who developed the disease had lower FA compared with those who didn’t, suggesting white matter damage. They also had statistically significant reductions in certain frontal white matter tracts.

“DTI performed very well compared to other clinical measures,” Dr. Raji noted. “Using FA values and other associated global metrics of white matter integrity, we were able to achieve 89% accuracy in predicting who would go on to develop Alzheimer’s disease. The Mini-Mental State Examination and APOE4 gene testing have accuracy rates of about 70–71%.”

The research team were excited by their findings but understand that more work is needed before the approach is ready for routine clinical use. The results point to a future role for DTI in the diagnostic workup of people at risk for AD. Many people already receive MRI as part of their care, so DTI could add significant value to the exam without substantially increasing the costs.

“Research shows that Alzheimer’s disease risk can be reduced by addressing modifiable risk factors like obesity and diabetes,” Raji concluded. “With early detection, we can enact lifestyle interventions and enlist volunteers into drug trials earlier.”

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