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Alzheimer's disease
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AI helps identifying onset of Alzheimer’s disease

Researchers from VU University Medical Centre in Amsterdam have developed an automated machine that can identify dementia in early stages. They have coupled machine learning methods with a special MRI technique — that measures perfusion, or tissue absorption rate, of blood throughout the brain — to detect early forms of dementia.

Their study was published online in the journal Radiology.

It contends that the brain undergoes functional changes before the physical changes associated with the disease happen. And, there’s definitive way to identify the onset of dementia or predict which cases of mild cognitive impairment (MCI) will progress to Alzheimer’s disease.

“With standard diagnostic MRI, we can see advanced Alzheimer’s disease, such as atrophy of the hippocampus,” principal investigator Dr. Meije Wink said.

“But at that point, the brain tissue is gone and there’s no way to restore it. It would be helpful to detect and diagnose the disease before it’s too late.”

The study used a type of MRI called the arterial spin labeling (ASL) imaging. They create images called perfusion maps. They reveal how much blood is delivered to various regions of the brain.

Identifying changes that appear early

The automated machine learning program is made to recognize these images and distinguish those with varying levels of cognitive impairment. And, it proved to be a success.

It was able to distinguish effectively among participants with Alzheimer’s disease, MCI and subjective cognitive decline (SCD).

Alzheimer's disease
Discrimination maps for classifying MCI subgroups, inside the masks that resulted in the highest accuracies. A: between patients with MCI that converted to AD (MCIc) and subjects with SCD; B: between MCIc and patients with MCI that remained stable (MCIs). Photo: Radiological Society of North America


“ASL MRI can identify brain changes that appear early in disease process, when there’s a window of opportunity for intervention,” Dr. Meije Wink said. “If the disease process from SCD to MCI to Alzheimer’s disease could be intercepted or slowed, this technique could play a role in screening.”


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