Is it possible to diagnose cognitive impairment before it progresses to Alzheimer's?

Is it possible to diagnose cognitive impairment before it progresses to Alzheimer's? ...

Alzheimer''s disease is the main cause of dementia worldwide. Despite the fact that there is no cure, early detection is crucial for achieving effective treatments, which act before their progress is irreversible.

It''s the process that precedes the disease, but not everyone who suffers it ends up developing Alzheimer''s. A research conducted by the University of California at Catalunya, has successfully found a distinction between people who suffer from the disease and those who willprogress to it. The new approach, which uses specific artificial intelligence techniques to compare magnetic resonance images, is more effective than the other methods currently in use.

Fine-tuning the diagnosis

Alzheimer''s disease affects more than 50 million people worldwide, and the ageing of the population means there may be many more fatalities in the coming decades. Although it usually develops without any symptoms over many years, it is generally preceded by something known as mild cognitive impairment, which is considerably less severe than that experienced in someone of their age. "These patients may progress and worsen or remain in the same condition as time passes," said Mona Ashtari-Majlan, an UOC researcher at the AIWELL research group,

Using artificial intelligence and deep learning to discern these cases correctly might help to improve the quality of clinical trials used to test interventions, which increasingly seek to address the initial phases of the disease.

"We first compared MRIs from Alzheimer''s patients and healthy people to see different points," Ashtari-Majlan said. After training the system, they fine-tuned the proposed architecture with resonance images from people who had already developed a stable or progressive cognitive impairment with substantially less differences. In total, almost 700 images from publicly available datasets were used.

According to Ashtari-Majlan, the process "overcomes the complexity of learning caused by the subtle structural changes between the two types of mild cognitive impairment, which are significantly less likely than those between a normal brain and a brain affected by the disease. Furthermore, the proposed method might address the small sample size issue, where the number of MRIs for mild cognitive impairment cases is reduced than for Alzheimer''s."

The new method allows the two forms of mild cognitive impairment to be distinguished and classified with an accuracy rate of 85%. "Our evaluation criteria show that our proposed method outperforms existing ones," she said, implying, even if they are combined with biomarkers such as age and cognitive tests. "We can share our experience with anyone who wants to reproduce the findings and their methods with others. We believe this technique will assist professionals in expanding the research."

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