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‘New hope’ for millions whose dense breast tissue masks cancer on mammograms
A new software promises to detect breast cancer in women with dense breasts
A tool that uses AI to detect breast cancer could “offer new hope” for millions of women whose dense breast tissue masks cancer on mammograms.
The software, developed by the health tech company DeepLook Medical, is the first AI tool to tackle breast cancer in women with dense tissue.
The technology is based on a shape recognition algorithm that aims to improve early detection, assist clinicians in creating treatment plans and accelerate workflow.
Nearly half of women over the age of 40 are found to have dense breast tissue which makes them more likely to get breast cancer.
However, because both dense breast tissue and cancer show up as white in a mammogram, as many as 50 per cent of cancers in these women are missed on mammograms.
“More than 40 per cent of women have dense breasts, myself included,” says DeepLook Medical CEO, Marissa Fayer.
“However, this disproportionately affects Black, Asian and Jewish populations which means these women have a higher chance of getting cancer just because of their genetics. There’s no reason not to have a technology that could be used with existing tools to help these women.”
What is unique about the software, DeepLook Medical claims, is that it is able to “see through” dense breast tissue.
“It is a precise tool that helps radiologists navigate dense breast tissue and gives patients the confidence that even if they have dense breast tissue, we can see through it,” says Fayer.
“This is a technology that works for everyone. It’s not just for white women – it can be used everywhere. The exciting part about it is that it is integrated straight into the workflow of radiologists; it’s right there on their monitor.”
The tool is currently available in the US, with certifications in other global regions pending and planned.
Fayer says: “There’s nobody in the world who hasn’t been touched by cancer. Our hope is that if it happens to you, you can find it early.”
AI for all
Reading mammograms with the help of AI technologies has been shown to detect more cancers than the routine double reading by two different radiologists. However, in order for this to benefit all patients, the datasets used for creating these technologies should be curated with diversity and inclusion in mind.
STANDING Together, an international initiative that tackles bias in AI health datasets, found that many datasets in different disease areas, including breast cancer, were from high-income settings and did not report individuals’ attributes.
“Making sure you have the correct data set coming in and ensuring the technologies you are developing can be used on diverse sets are some of the biggest challenges in AI,” says Fayer.
“It’s a big push, but it’s something that we need to keep talking about and something that developers need to stand up for.”
Not ensuring diverse datasets, Fayer warns, could lead to disparities similar to the ones seen in clinical research.
“Historically, women have been underrepresented in clinical trials, which led to poor health outcomes and huge data gaps. That’s why we need to keep talking about diversity, especially when it comes to AI. There’s no reason to stop talking about it.”
Ovarian cancer cells quickly activate survival responses after PARP inhibitor treatment, and a lung cancer drug could help block this, research suggests.
PARP inhibitors are a common treatment for ovarian cancer, particularly in tumours with faulty DNA repair. They stop cancer cells fixing DNA damage, which leads to cell death, but many tumours later stop responding.
Researchers identified a way cancer cells may survive PARP inhibitor treatment from the outset, pointing to a potential way to block that response. A Mayo Clinic team found ovarian cancer cells rapidly switch on a pro-survival programme after exposure to PARP inhibitors. A key driver is FRA1, a transcription factor (a protein that turns genes on and off) that helps cancer cells adapt and avoid death.
The team then tested whether brigatinib, a drug approved for certain lung cancers, could block this response and boost the effect of PARP inhibitors. Brigatinib was chosen because it inhibits multiple signalling pathways involved in cancer cell survival.
In laboratory studies, combining brigatinib with a PARP inhibitor was more effective than either treatment alone. Notably, the effect was seen in cancer cells but not normal cells, suggesting a more targeted approach.
Brigatinib also appeared to act in an unexpected way. Rather than working through the usual DNA repair routes, it shut down two signalling molecules, FAK and EPHA2, that aggressive ovarian cancer cells rely on. FAK and EPHA2 are proteins that relay survival signals inside cells. Blocking both at once weakened the cells’ ability to adapt and resist treatment, making them more vulnerable to PARP inhibitors.
Tumours with higher levels of FAK and EPHA2 responded better to the drug combination. Other data link high levels of these molecules to more aggressive disease, pointing to potential benefit in harder-to-treat cases.
Arun Kanakkanthara, an oncology investigator at Mayo Clinic and a senior author of the study, said: “This work shows that drug resistance does not always emerge slowly over time; cancer cells can activate survival programmes very early after treatment begins.”
John Weroha, a medical oncologist at Mayo Clinic and a senior author of the study, said: “From a clinical perspective, resistance remains one of the biggest challenges in treating ovarian cancer. By combining mechanistic insights from Dr Kanakkanthara’s laboratory with my clinical experience, this preclinical work supports the strategy of targeting resistance early, before it has a chance to take hold. This strategy could improve patient outcomes.”
Nighttime temperatures during pregnancy may be linked to a higher chance of an autism diagnosis in children, a recent study suggests.
The research tracked nearly 295,000 mother-child pairs in Southern California from 2001 to 2014 and linked warmer overnight temperatures with higher risk in early and late pregnancy.
Children of mothers exposed to higher than typical nighttime temperatures during weeks one to 10 of pregnancy had a 15 per cent higher risk of an autism diagnosis.
Exposure during weeks 30 to 37 was linked to a 13 per cent higher risk.
Lead author David Luglio, a post-doctoral fellow at Tulane University, said: “A key takeaway is that we identified specific windows when a mother and her developing child can be most affected by exposures to higher nighttime temperatures.
“This is critical and hopefully can help mothers prepare accordingly.”
The study is described as the first to examine how temperature may affect fetal neurodevelopment, the process by which a baby’s brain and nervous system form during pregnancy.
Extreme temperatures linked to increased risk were classified as above the 90th percentile, meaning 3.6°F hotter than average, and the 99th percentile, 5.6°F above average.
The association held even after researchers accounted for factors such as neighbourhood conditions, vegetation and fine-particle air pollution.
The study could not account for other factors such as access to air conditioning. Researchers did not find the same association with daytime temperatures, potentially because people spend more time away from home during the day.
“Heat waves are becoming more frequent, and people may only think of the dangers of daytime heat exposure,” said Mostafijur Rahman, assistant professor of environmental health sciences at Tulane University.
“These results indicate a strong association between high nighttime temperatures during pregnancy and autism risk in children and show that we need to think about exposure to heat around the clock.”
The study did not examine how higher temperatures at night might affect prenatal development, though Luglio said it is possible that warmer nights disrupt sleep for pregnant mothers.
Previous research has suggested insufficient sleep during pregnancy may be linked to a higher risk of neurocognitive delays in children.
“Extreme heat exposure during pregnancy has been linked to a range of adverse health outcomes, including prenatal neurodevelopment delays and complications with an embryo’s development of a central nervous system,” Luglio said.
“The goal of our study was to specifically explore the link between prenatal heat exposure and autism diagnoses for the first time.”
Kindbody has launched a fertility platform integrating AI with clinical care and patient support for employers and health plans.
The platform will enter a pilot with select Kindbody employer clients in 2026, covering over three million lives, ahead of wider availability in 2027.
Building on the company’s clinical model, the platform aims to improve outcomes and cost efficiency across family-building journeys. It connects Kindbody-owned clinics, partner clinics and an integrated clinical app.
The app offers virtual care across conception, pregnancy and reproductive health, extending through the menopause transition.
Launch features include updates in medication management, third-party reproduction, adoption, pregnancy, men’s health and global programme design.
David Stern, chief executive of Kindbody, said: “With our next-generation fertility platform, Kindbody is redefining what comprehensive, intelligent and affordable family-building care looks like for employers, health plans and patients.
“By unifying best-in-class clinical care, AI-driven intelligence and whole-person support, we are making it easier and more cost-effective for more people to build the families they envision.”
Kindbody has expanded access via its national network of IVF centres, including IVIRMA, Inception Fertility and Ivy Fertility.
A new Fertility Medication Portal is designed to streamline authorisations so medicines can be dispensed on time, giving patients visibility from prescription to coverage, pharmacy fulfilment and delivery tracking.
Through KindMan, men’s health education, digital resources and integrated clinical care are expanding, including hormone management programmes.
Services cover andropause (age-related testosterone decline), erectile dysfunction, low testosterone and other male reproductive conditions.
Specialist fertility care includes semen analysis, diagnostic testing, male hormone panels, genetic testing, surgical sperm extraction and sperm cryopreservation.
Launching in the second quarter, a pregnancy support app will act as a digital companion for expecting and new parents, with resources, interactive tools and clinical assessments to identify social drivers of health and mental health needs during pregnancy and beyond.
Kindbody’s physician-led menopause programme provides consultations with board-certified obstetricians and gynaecologists to diagnose, treat and manage menopausal symptoms, including hormone replacement therapy where appropriate, with support from nutritionists, mental health therapists and pelvic floor specialists.
AI and analytics will be embedded across the care journey. An AI care navigator will guide employees from benefit activation through intake, triage and scheduling.
Tools will track benefits and treatment plans, showing coverage and expected out-of-pocket costs at each step.
AI-supported scribing will assist clinicians with documentation, and a predictor tool will estimate a patient’s likelihood of having a baby across different treatment paths.
In 2027, Kindbody plans a savings model for eligible large employers that it says will guarantee lower total fertility spend while improving clinical efficiency and patient experience.
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