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AI-powered mammograms: a new window into heart health

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Mammograms used in combination with AI may reveal much more than cancer,  but can also be used to assess the amount of calcium build up in the arteries within breast tissue – an indicator of cardiovascular health, a new study shows.

While breast artery calcifications can be seen on mammogram images, radiologists do not typically quantify or report this information to women or their clinicians.

This new study, which used an AI image analysis technique not previously used on mammograms, demonstrates how AI can help fill this gap by automatically analysing breast arterial calcification and translating the results into a cardiovascular risk score.

“We see an opportunity for women to get screened for cancer and also additionally get a cardiovascular screen from their mammograms,” said Theo Dapamede, postdoctoral fellow at Emory University in Atlanta and the study’s lead author.

 

“Our study showed that breast arterial calcification is a good predictor for cardiovascular disease, especially in patients younger than age 60. If we are able to screen and identify these patients early, we can refer them to a cardiologist for further risk assessment.”

Heart disease is the leading cause of death in the United States but remains underdiagnosed in women and there is also lagging awareness. Researchers said the use of AI-enabled mammogram screening tools could help identify more women with early signs of cardiovascular disease by taking better advantage of screening tests that many women routinely receive.

A build up 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 build up in the arteries face a 51 per cent higher risk of heart disease and stroke.

To develop the screening tool used for this study, researchers trained a deep-learning AI model to segment calcified vessels in mammogram images, which appear as bright pixels on X-rays, and calculate the future risk of cardiovascular events based on data obtained from the electronic health record data.

The segmentation approach is what separates this model from previous AI models developed for analysing breast artery calcifications. Researchers said the model is also strengthened by its use of a large dataset for training and testing, which included images and health records from over 56,000 patients who had a mammogram at Emory Healthcare between 2013 and 2020 and had at least five years of follow-up electronic health records data.

“Advances in deep learning and AI have made it much more feasible to extract and use more information from images to inform opportunistic screening,” Dapamede said.

Overall findings showed the new model performed well at characterizing patients’ cardiovascular risk as low, moderate or severe based on mammogram images.

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 showed 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 to 80, but not in those over age 80.

This makes the tool particularly well suited for providing early warning of heart disease risk in younger women, who can benefit more from early interventions, researchers said.

The results also showed that women with the highest level of breast arterial calcification (above 40 mm2) had a significantly lower five-year rate of event-free survival than those with the lowest level (below 10 mm2).

For example, 86.4 per cent of those with the highest breast arterial calcification survived for five years compared with 95.3 per cent of those with the lowest level of calcification. 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 and 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 health care 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.

Entrepreneur

TidalSense raises £14m to expand five-minute COPD test across NHS

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Cambridge health tech company TidalSense has secured £14.2m in funding led by Cross-Border Impact Ventures to expand its AI-powered lung disease test across the NHS and into Europe and the US.

The investment, which also includes returning backers BGF, Airstream Capital and Foresight Group, will fund the rollout of a handheld diagnostic device that can detect chronic obstructive pulmonary disease (COPD) in as little as five minutes.

It will also support the development of software to diagnose asthma using the same platform.

Donna Parr is managing partner at Cross-Border Impact Ventures.

She said: We look for technology that doesn’t just have a compelling story, but a body of clinical evidence behind it.

“TidalSense has both, with a CEO who has lived the problem she’s solving, and a product that’s already live within the NHS healthcare environment, saving time for patients who have waited years for an answer.

“It is also technology that can improve access to appropriate treatment for COPD sufferers on a global basis and especially for women who are often misdiagnosed.

“This is exactly the kind of impact we want to make with our investments.”

COPD, a progressive condition that restricts airflow and makes breathing increasingly difficult, is the third leading cause of death in England, according to the NHS.

It is responsible for about 30,000 deaths each year and costs the health service an estimated £1.9bn annually.

The company believes its technology could transform how respiratory disease is diagnosed by replacing the need for conventional spirometry in many settings.

Patients simply breathe normally into the handheld device for 75 seconds while artificial intelligence analyses the breath in real time.

A diagnosis is then displayed on screen, allowing clinicians to complete the entire process in around five minutes.

TidalSense says the technology allows clinicians to assess as many as six patients an hour, compared with roughly one an hour using spirometry, which has remained the standard diagnostic test for COPD despite changing little since it was first developed in the 19th century.

Spirometry requires patients to perform forceful breathing manoeuvres and typically needs specialist staff to administer.

TidalSense chief executive Ameera Patel said: “Our ambition is really bold and broad, and it is to have a really significant impact at a population level on chronic respiratory diseases like COPD and asthma.

“We want the test to be available to anyone the first time they present with symptoms, so there’s no bias in accessibility based on where you live, your socio-economic status or your ethnicity.”

Founded in 2013 by chief engineering officer Julian Carter, who holds a PhD in microelectronics and has more than 35 years’ experience developing medical devices, TidalSense has spent more than a decade building the technology.

Its AI models have been trained on more than 2.5 million recorded breaths to identify the distinctive patterns associated with COPD.

The device was introduced into the NHS last year and is now being used by public health providers in Suffolk, north-east Essex, Wales, Glasgow and community lung screening clinics across the south of England.

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CEM shows promise for screening high-risk breast cancer patients

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Contrast-enhanced mammography (CEM) has shown promise for women at higher risk of breast cancer, with follow-up screening showing greater specificity and accuracy.

Cancer detection rates remained consistent during repeat screening, while specificity improved compared with baseline examinations.

Specificity shows how accurately a test identifies people who do not have the disease, helping to reduce unnecessary follow-up procedures.

Researchers at Memorial Sloan Kettering Cancer Center analysed 6,911 contrast-enhanced mammography screens carried out among 2,756 women between 2015 and 2021.

Contrast-enhanced mammography, or CEM, combines standard mammography with an injected contrast agent that highlights areas of increased blood flow. Cancerous tumours often develop a greater blood supply.

The team compared 1,575 baseline screens with 3,336 incidence screens.

The researchers classified a screen as baseline if the woman had no previous CEM or had not undergone breast MRI in the previous three years.

Incidence screens were follow-up examinations carried out after previous screening.

After adjusting for the number of screens each woman received, the researchers found no statistically significant difference in cancer detection rates between the groups.

However, specificity reached 91.5 per cent during incidence screening, compared with 83.4 per cent for baseline screening.

Overall accuracy was also higher for incidence screening, at 91.4 per cent compared with 83.5 per cent.

“The ability of contrast-enhanced mammography to help detect cancer during prevalence screening in women at increased risk for breast cancer is maintained in subsequent incidence screens, with better specificity and accuracy,” the research team wrote.

Baseline screening detected 19 cancers per 1,000 examinations, compared with 11.6 per 1,000 incidence screens.

Sensitivity, which measures how well a test identifies people who have a disease, was 87.1 per cent for baseline screening and 86.1 per cent for incidence screening.

Contrast enhancement alone helped detect 18 of the 30 cancers found during baseline screening and 36 of the 62 found during incidence screening.

The researchers also identified 14 interval cancers across the examinations, with no evidence of a difference between the two groups.

An interval cancer is diagnosed after a screening result appears normal but before the next scheduled examination.

The retrospective study used previously collected clinical records rather than following participants in a newly designed trial.

The researchers described CEM as a reasonable screening tool for women with dense breasts.

Dense breasts contain more fibrous and glandular tissue, which can make cancer more difficult to detect with standard mammography.

CEM has previously shown greater sensitivity than ultrasound, digital mammography and digital breast tomosynthesis, according to the article.

Digital breast tomosynthesis takes several low-dose X-ray images from different angles to create a three-dimensional view of breast tissue.

The technique also takes less time and generally costs less than breast MRI, with previous research suggesting its performance is not inferior to MRI.

CEM is currently used for some screening purposes outside its approved indications.

The researchers said it could also help address health inequalities affecting women who face barriers to accessing MRI.

“In addition, women have reported a preference for CEM over MRI,” they wrote.

The researchers said a future article would provide full details about the interval cancers identified in the study.

An accompanying editorial said the technique could become a practical part of breast cancer screening for selected groups, although challenges remain around wider adoption.

“Whether this potential ultimately translates into widespread implementation will depend on future studies evaluating not only diagnostic performance, but also patient outcomes, health care utilisation, and real-world feasibility across diverse practice settings,” wrote Dr Vivianne Aguilera Freitas of the University of Toronto.

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Insight

Experimental treatment significantly slows progression of fatal brain disease in women, study finds

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Davunetide may significantly slow the progression of a fatal brain disease in women, according to a new analysis of clinical trial data.

The findings indicate that women and men with progressive supranuclear palsy (PSP) may respond differently to the experimental treatment.

Progressive supranuclear palsy, or PSP, is a rare and fatal neurodegenerative disease.

Researchers at Tel Aviv University led the analysis and said the results reinforce the need for sex-specific approaches to neurodegenerative diseases.

Neurodegenerative diseases are conditions in which nerve cells in the brain or nervous system gradually lose function and die.

The team reanalysed data from a 52-week international clinical trial involving more than 300 people with PSP.

The disease is caused by the abnormal accumulation of tau protein in the brain. Tau is a protein found in nerve cells that builds up abnormally in people with PSP.

There is currently no effective drug treatment for the disease.

The work was led by professor Illana Gozes of the Sagol School of Neuroscience and the Gray Faculty of Medical and Health Sciences at Tel Aviv University.

The research team included current and former students Dr Guy Shapira, Jason Blatt and Liri Guz, together with professor Noam Shomron.

The original clinical trial found that Davunetide was safe but ineffective.

However, the researchers separated female and male participants and re-examined the data using updated assessment measures recommended by the FDA.

Women treated with Davunetide experienced a significant slowing of disease progression, while no similar effect was observed in men.

The treatment helped preserve essential movement and functional abilities, including balance, fine motor skills and everyday tasks such as using cutlery, buttoning clothes and washing the face and hands.

Fine motor skills are the small, precise movements needed for tasks involving the fingers and hands.

Treated women also showed significant improvements in language ability, working memory and overall cognitive function.

Cognitive function covers mental abilities such as memory, attention, language and problem-solving.

The analysis also identified profound molecular differences between women and men.

The relationship between levels of pathological tau in cerebrospinal fluid and clinical symptoms was completely reversed between the sexes.

Cerebrospinal fluid is the clear liquid surrounding the brain and spinal cord. A biomarker is a measurable sign that can indicate disease activity.

For example, language abilities declined significantly as tau pathology increased in women, but not in men.

The researchers said this suggests the disease mechanisms may work differently in women and men, potentially explaining their different responses to treatment.

According to professor Gozes, overlooking biological differences between the sexes may hide a genuine treatment effect.

“Our data show that analysing women and men separately is not merely a statistical exercise, but an essential tool for developing more effective treatments for neurodegenerative brain diseases,” she said.

The researchers believe the findings provide a strong scientific basis for future clinical trials and treatment protocols designed from the outset to account for patients’ sex.

These trials could evaluate Davunetide as a targeted treatment for women with PSP.

They said the approach may also pave the way for more precise treatments for tau-related diseases, including Alzheimer’s disease and other neurodegenerative brain disorders.

The study was supported by ExoNavis Therapeutics, which is developing Davunetide for brain diseases under licence from Ramot, Tel Aviv University’s technology transfer company.

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