MRI detects signs of premature aging in people with poor heart health
Tracking brain health using MRI and machine learning not only predicts how individuals will age in those who had poor cardiovascular health early in life, but also May offer ways to coordinate prevention and treatment of neurodegenerative diseases, says lead author Dr. Jonathan Schott of the Center for Dementia Research, University College London, UK
“We want this technology [of using MRI with machine learning] One day, it could be a useful tool for identifying people at risk of accelerated aging, providing early, targeted prevention strategies to improve brain health,” said Schott. said in a statement released by the university.
Brain age and cardiovascular health have long been associated, with older brain age relative to chronological age associated with lower scores on cognitive tests and increased risk of brain atrophy over time. increase. There is a risk of cognitive decline and other brain-related diseases,” the journal said in a statement.
Through a study that used MRI-based machine learning algorithms to assess the brain age of 456 Britons born in one week in 1946, Schott’s team was able to predict the effects of aging on brain age and cardiovascular health. I tried to explore possible relationships between the worsening of the condition.
Participants in this study were part of the UK Medical Research Council’s National Survey on Health and Development (also known as the 1946 UK Birth Cohort or Insight 46) and were followed for life. As part of the study, they underwent 24 health assessments, including a heart health assessment from his Framingham Heart Study Cardiovascular Risk Score.
All participants also had an MRI examination between May 2015 and January 2018, between the ages of 69 and 72 years.
The machine learning model created by Schott and colleagues was trained on 2,001 healthy adults between the ages of 18 and 90. The group used this model to compare Insight 46 MRI scan data with the chronological ages of study participants, to find “the brain-predicted age difference.”
Schott’s team found that study participants who had worse heart health in their 30s also had worse brain health in their late 60s and early 70s, suggesting that the brain predicts an increase in age. , were associated with increased cerebrovascular disease burden, decreased cognitive performance, and increased serum. Neurofilament photodensity (a biomarker of nerve damage).
The researchers also found that the model predicted the brain age of women to be five years younger than that of men. However, researchers found no association between higher brain age compared to chronological age based on childhood cognitive ability, educational level, or socioeconomic class.
The results of this study suggest that brain-predicted age differences based on MRI findings may be a useful way to assess brain health in individuals.
“These findings reflect multiple contributions to brain aging and support brain-predicted age differences as an integrated summary measure of brain health that may have prognostic utility.” ,” they concluded.
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