Artificial Intelligence can help predict who will develop dementia, a new study finds

 

Photo by Lukas Budimaier

If you could find out years ahead that you were likely to develop Alzheimer’s, would you want to know?

Researchers from McGill University argue that patients and their families could better plan and manage care given this extra time. So the team has developed new artificial intelligence software that uses positron emission tomography (PET) scans to predict whether at-risk patients will develop Alzheimer’s within two years.

They retrospectively studied 273 individuals with mild cognitive impairment who participated in the Alzheimer’s Disease Neuroimaging Initiative, a global research study that collects imaging, genetics, cognitive, cerebrospinal fluid and blood data to help define the progression of Alzheimer’s disease.

Patients with mild cognitive impairment have noticeable problems with memory and thinking tasks that are not severe enough to interfere with daily life. Scientists know these patients have abnormal amounts of tau and beta-amyloid proteins in specific brain regions involved in memory, and this protein accumulation occurs years before the patients have dementia symptoms.

However, not everyone with mild cognitive impairment will go on to develop dementia, and the McGill researchers aimed to predict which ones will.

First, the team trained their artificial intelligence software to identify patients who would develop Alzheimer’s, by identifying key features in the amyloid PET scans of the ADNI participants. Next, they assessed the performance of the trained AI using an independent set of ADNI amyloid PET scans. It predicted Alzheimer’s progression with an accuracy of 84 percent before symptom onset, as reported in a recent paper in Neurobiology of Aging.

The researchers hope their new AI tool will help improve patient care, as well as accelerate research to find a treatment for Alzheimer’s disease by identifying which patients to select for clinical trials.

“By using this tool, clinical trials could focus only on individuals with a higher likelihood of progressing to dementia within the time frame of the study. This will greatly reduce the cost and time necessary to conduct these studies,” said Serge Gauthier, MD, a senior author and professor of neurology and neurosurgery and of psychiatry at McGill, in a recent news release.

The new AI tool is now available to scientists and students, but the McGill researchers need to conduct further testing before it will be approved and available to clinicians.

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

Alzheimer’s researchers call on citizen scientists to play an online game

Image by geralt
Image by geralt

Many people, like me, have helplessly watched a loved one suffer and die from dementia. Now there is something you can do to help accelerate Alzheimer’s research — play a game.

The game, called Stall Catchers, is part of the EyesOnALZ project that uses citizen scientists to analyze Alzheimer’s research data. The game was developed by the Human Computation Institute, in collaboration with scientists from Cornell University, MIT and the University of California, Berkeley. The research team is trying to understand the association between reduced blood flow in the brain and Alzheimer’s disease.

The game features movies of real blood vessels in live mouse brains. Players must search for clogged vessels where blood flow is blocked, or stalled. Each movie is seen by many citizen scientists and then checked by a research scientist in order to quickly and accurately identify the stalls.

Past research has shown that Alzheimer’s is associated with the accumulation of beta amyloid proteins that clump together into sticky, neurotoxic aggregates called amyloid plaques. These proteins are normally cleared by the blood stream, but the formation of amyloid plaques slows down this clearance process.

Recent animal studies, performed by the Schaffer-Nishimura Lab at Cornell, suggest that improving blood flow in the brain may help reduce the devastating effects of amyloid accumulation. The researchers discovered that up to two percent of capillaries in the brains of Alzhiemer’s-affected mice were clogged — 10 times more than usual — and this caused up to a 30 percent decrease in overall blood flow in the brain.

“Advanced optical techniques have allowed us to peer into the brain of mice affected by Alzheimer’s disease,” said Chris Schaffer, PhD, the principal investigator in the Schaffer-Nishimura Lab, in a recent news release. “For the first time, we were able to identify the mechanism that is responsible for the significant blood flow reduction in Alzheimer’s, and were even able to reverse some of the cognitive symptoms typical to the disease.”

Now the main challenge for the Cornell researchers is the time-consuming process of manually analyzing all the brain movies to identify the stalled vessels. They need to study up to a thousand vessels for each animal. That’s why they collaborated with the experienced citizen teams at UC Berkeley and MIT to create the Stall Catchers game to get help from the public.

“Today, we have a handful of lab experts putting their eyes on the research data,” said Pietro Michelucci, PhD, the EyesOnALZ principal investigator, in a news story. “If we can enlist thousands of people to do that same analysis by playing an online game, then we have created a huge force multiplier in our fight against this dreadful disease.”

This is a reposting of my Scope blog story, courtesy of Stanford School of Medicine.

 

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