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Alzheimer's

Unlocking the Secrets of Heart Health through AI-Powered Mammograms

Mammograms, with the help of artificial intelligence (AI) models, may reveal much more than cancer, according to a new study. The findings highlight how these important cancer screening tools can also be used to assess the amount of calcium buildup in the arteries within breast tissue — an indicator of cardiovascular health.

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The American College of Cardiology’s Annual Scientific Session (ACC.25) recently showcased a groundbreaking study that sheds new light on the capabilities of mammograms. These essential cancer screening tools have long been used to detect breast cancer, but now, with the aid of artificial intelligence (AI) models, they can also serve as a window into heart health.

The U.S. Centers for Disease Control and Prevention recommends that middle-aged and older women receive regular mammograms, which are performed over 40 million times annually in the United States. However, radiologists typically do not quantify or report information on breast artery calcifications, which can be seen on these images. This study demonstrates how AI image analysis techniques can automatically analyze breast arterial calcification and provide a cardiovascular risk score.

“We see an opportunity for women to get screened for cancer and also receive a cardiovascular screen from their mammograms,” said Theo Dapamede, MD, PhD, the lead author of the study. The researchers used an AI model to segment calcified vessels in mammogram images and calculate the future risk of cardiovascular events based on data obtained from electronic health record data.

The findings are significant, as heart disease is the leading cause of death in the United States, yet it remains underdiagnosed in women and awareness about this condition lags. By utilizing AI-enabled mammogram screening tools, researchers can identify more women with early signs of cardiovascular disease, taking advantage of routine screenings that many women already receive.

A buildup of calcium in blood vessels is a sign of cardiovascular damage associated with early-stage heart disease or aging. Previous studies have shown that women with calcium buildup in the arteries face a 51% higher risk of heart disease and stroke.

To develop this screening tool, researchers trained a deep-learning AI model on a large dataset, which included images and health records from over 56,000 patients who had a mammogram at Emory Healthcare between 2013 and 2020. The model was then tested for its ability to characterize patients’ cardiovascular risk as low, moderate, or severe based on mammogram images.

The results showed that the AI model performed well in characterizing patients’ cardiovascular risk. After calculating the risk of dying from any cause or suffering an acute heart attack, stroke, or heart failure at two years and five years, the model demonstrated that the rate of these serious cardiovascular events increased with breast arterial calcification level in two of the three age categories assessed – women younger than age 60 and age 60-80, but not in those over age 80.

The researchers also found that women with the highest level of breast arterial calcification (above 40 mm2) had a significantly lower five-year rate of event-free survival compared to those with the lowest level (below 10 mm2). This translates to approximately 2.8 times the risk of death within five years in patients with severe breast arterial calcification compared to those with little to no breast arterial calcification.

The AI model was developed as a collaboration between Emory Healthcare and Mayo Clinic, but it is not currently available for use. If it passes external validation and gains approval from the U.S. Food and Drug Administration, researchers said the tool could be made commercially available for other healthcare systems to incorporate into routine mammogram processing and follow-up care.

The researchers also plan to explore how similar AI models could be used for assessing biomarkers for other conditions, such as peripheral artery disease and kidney disease, that might be extracted from mammograms.

Alzheimer's

Groundbreaking Study Suggests Link Between Semaglutide and Lower Dementia Risk in Type 2 Diabetes Patients

A blockbuster diabetes and weight-loss drug might be doing more than controlling blood sugar—it could also be protecting the brain. Researchers at Case Western Reserve University found that people with type 2 diabetes who took semaglutide (the active ingredient in Ozempic and Wegovy) had a significantly lower risk of developing dementia. The benefit was especially strong in women and older adults.

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A recent study by researchers at the Case Western Reserve School of Medicine has made an astonishing discovery that may revolutionize the way we approach dementia prevention. The research team found that semaglutide, a popular medication used to treat diabetes and aid in weight loss, could significantly lower the risk of dementia in people with type 2 diabetes (T2D).

Dementia is a devastating condition that affects millions worldwide, causing memory loss and cognitive decline. It occurs when brain cells are damaged, disrupting their connections and ultimately leading to this debilitating state. Encouragingly, studies indicate that approximately 45% of dementia cases could be prevented by addressing modifiable risk factors.

The study, published in the Journal of Alzheimer’s Disease, analyzed three years’ worth of electronic records from nearly 1.7 million T2D patients nationally. The researchers used a statistical approach that mimicked a randomized clinical trial to determine the effectiveness of semaglutide in preventing dementia.

Their findings suggest that patients prescribed semaglutide had a significantly lower risk of developing Alzheimer’s disease-related dementia compared to those taking other anti-diabetic medications, including GLP-1R-targeting medications. These results were even more pronounced in women and older adults.

Semaglutide, a glucagon-like peptide receptor (GLP-1R) molecule that decreases hunger and regulates blood sugar levels in T2D patients, has shown remarkable benefits beyond its primary use as a diabetes treatment. It also reduces the risk of cardiovascular diseases, further solidifying its potential in preventing dementia.

The study’s lead researcher, biomedical informatics professor Rong Xu, stated, “There is no cure or effective treatment for dementia, so this new study provides real-world evidence for its potential impact on preventing or slowing dementia development among at-high risk populations.”

While the findings are promising, it’s essential to note that further research through randomized clinical trials will be necessary to confirm the causal relationship between semaglutide and dementia prevention. Nevertheless, this groundbreaking study offers a glimmer of hope in the quest to combat dementia and improve the lives of millions worldwide.

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Alzheimer's

The Common Blood Test That Could Predict Alzheimer’s Progression

A simple blood test could reveal which early Alzheimer’s patients are most at risk for rapid decline. Researchers found that people with high insulin resistance—measured by the TyG index—were four times more likely to experience faster cognitive deterioration. The study highlights a major opportunity: a common lab value already available in hospitals could help guide personalized treatment strategies. This discovery also uncovers a unique vulnerability in Alzheimer’s disease to metabolic stress, offering new possibilities for intervention while the disease is still in its early stages.

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The common blood test known as the triglyceride-glucose (TyG) index has long been used to detect insulin resistance. New research presented at the European Academy of Neurology Congress 2025 suggests that this simple test could also be used to predict how fast Alzheimer’s disease progresses in individuals with mild cognitive impairment.

A team of neurologists from the University of Brescia reviewed records for 315 non-diabetic patients with cognitive deficits, including 200 with biologically confirmed Alzheimer’s disease. All subjects underwent an assessment of insulin resistance using the TyG index and a clinical follow-up of 3 years. The results showed that when patients were divided according to their TyG index levels, those in the highest third of the Mild Cognitive Impairment subgroup deteriorated far more quickly than their lower-TyG peers.

The researchers found that high TyG was associated with blood-brain barrier disruption and cardiovascular risk factors, yet it showed no interaction with the APOE ε4 genotype. This suggests that metabolic and genetic risks may act through distinct pathways.

Identifying high-TyG patients could refine enrolment for anti-amyloid or anti-tau trials and prompt earlier lifestyle or pharmacological measures to improve insulin sensitivity.

“If targeting metabolism can delay progression, we will have a readily modifiable target that works alongside emerging disease-modifying drugs,” concluded Dr. Bianca Gumina.

The study aimed to fill the gap in understanding how quickly Alzheimer’s progresses by focusing on its impact during the prodromal mild cognitive impairment (MCI) stage.

This research has significant implications for individuals with mild cognitive impairment and their families, as it could provide a simple and cost-effective way to predict the pace of cognitive decline.

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Alzheimer's

Epilepsy Strikes with Surprising Frequency in Frontotemporal Dementia Patients

According to a recent study, in patients with frontotemporal dementia (FTD), epileptic seizures are significantly more common than previously known. The discovery deepens understanding of the symptoms of this memory disorder and emphasises the importance of taking epileptic seizures into account in the treatment and monitoring of patients.

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Epileptic seizures are more common in patients with frontotemporal dementia (FTD) than previously known, according to a recent study. This discovery sheds new light on the symptoms of this memory disorder and emphasizes the importance of considering epileptic seizures in treatment and monitoring patients.

The research project, led by Neurocenter Finland, analyzed data from 12,490 medical records at the University Hospitals of Kuopio and Oulu between 2010-2021. The study identified 245 patients with FTD and found that epilepsy was significantly more common among them than those with Alzheimer’s disease or healthy controls.

“Our results show that epilepsy is considerably more common among those with FTD than those with Alzheimer’s disease or in healthy controls,” says Doctoral Researcher Annemari Kilpeläinen, the first author of the research article and a medical specialist in neurology. “It is noteworthy that epilepsy occurred in some patients with FTD already ten years before their dementia diagnosis, and it was more common in all the examined stages of the disease than previous international studies have reported.”

The prevalence of epilepsy increased over time in patients with FTD, reaching approximately 11% five years after the diagnosis. In addition to diagnosing epilepsy, medications used for epilepsy were more common among patients with FTD, further strengthening the reliability of the results.

Diagnosing epilepsy in patients with FTD can be challenging due to the resemblance between the symptoms of the disease and epileptic seizures. However, untreated epilepsy can significantly worsen patients’ condition. Identifying epilepsy is essential because its treatment can improve patients’ functional capacity and quality of life.

“Knowledge about the association between epilepsy and FTD raises new research questions: do these diseases share some pathophysiological mechanisms and could some FTD symptoms be caused by alterations in the specific electrical systems of the brain?” asks Associate Professor Eino Solje, the principal investigator of the project.

The recently published study is part of an extensive project that combines real-life patient data with different kinds of unique registers. The project involves a strong cooperation between the University of Oulu and the University of Eastern Finland as well as different fields of science, including between researchers in medicine and law.

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