Cancer
AI-human task-sharing could cut mammography screening costs by up to 30 per cent

The most effective way to harness the power of AI when screening for breast cancer may be through collaboration with human radiologists — not by wholesale replacing them, says new research.
The study finds that a “delegation” strategy, where AI helps triage low-risk mammograms and flags higher-risk cases for closer inspection by human radiologists, could reduce screening costs by as much as 30 per cent without compromising patient safety.
The findings could help shape how hospitals and clinics integrate AI into their diagnostic workflows amid a growing demand for early breast cancer detection and a shortage of radiologists, said Mehmet Eren Ahsen, a professor of business administration and Deloitte Scholar at University of Illinois Urbana-Champaign.
“We often hear the question: Can AI replace this or that profession?” Ahsen said. “In this case, our research shows that the answer is ‘Not exactly, but it can certainly help.’ We found that the real value of AI comes not from replacing humans, but from helping them via strategic task-sharing.”
The study, which was published by the journal Nature Communications, was co-written by Mehmet U. S. Ayvaci and Radha Mookerjee of the University of Texas at Dallas; and Gustavo Stolovitzky of the NYU Grossman School of Medicine and NYU Langone Health.
The researchers developed a decision model to compare three decision-making strategies in breast cancer screening: an expert-alone strategy — the current clinical norm in which radiologists read every mammogram; an automation strategy, in which AI assessed all mammograms without human oversight; and a delegation strategy, in which AI performed an initial screening and referred ambiguous or high-risk cases to radiologists.
The model accounted for a wide range of costs, including implementation, radiologist time, follow-up procedures and potential litigation. It evaluated outcomes using real-world data from a global AI crowdsourcing challenge for mammography, which was sponsored as part of the White House Office of Science and Technology Policy’s Cancer Moonshot initiative of 2016 to 17.
The researchers found that the delegation model outperformed both the full automation and the expert-alone approaches, yielding up to 30.1 per cent in cost savings, according to the paper.
While the idea of fully automating radiological tasks may seem appealing from an efficiency standpoint, the study cautions that current AI systems still fall short of replacing human judgment in complex or borderline cases.
“AI is excellent at identifying low-risk mammograms that are relatively straightforward and easy to interpret,” said Ahsen, also the health innovation professor at the Carle Illinois College of Medicine.
“But for high-risk or ambiguous cases, radiologists still outperform AI. The delegation strategy leverages this strength: AI streamlines the workload, and humans focus on the toughest cases.”
With nearly 40 million mammograms performed annually in the U.S. alone, breast cancer screening is a critical public health tool. Yet the process is time-intensive and costly, in both labor and follow-up procedures triggered by false positives. And when cancers are missed, the resulting false negatives can lead to significant harm for patients and health care providers, Ahsen said.
“One of the issues in mammography is, because of the sheer number of screenings performed, that it generates so many false positives and false negatives,” Ahsen said. “If you have a 10% false positive rate out of 40 million mammograms per year, that’s four million women who are being recalled to the hospital for more appointments, screenings and tests, and potentially biopsies.”
That whole process only increases stress and anxiety for the patient, Ahsen said.
“It’s a nightmare scenario,” he said. “Follow-up appointments often take weeks, leaving patients with a black cloud hanging over their heads. It’s a very stressful time for them.”
With AI and the delegation model, it’s possible that health care providers could streamline the process.
“You get screened, AI sees something it doesn’t like and immediately flags you for follow-up, all while you’re still at the hospital,” Ahsen said. “It has the potential to be that much more efficient of a workflow.”
The research also raises broader questions about how AI should be implemented and regulated in medicine.
“The delegation strategy works best when breast cancer prevalence is either low or moderate,” Ahsen said.
“In high-prevalence populations, a greater reliance on human experts may still be warranted. But an AI-heavy strategy also might work well in situations where there aren’t a lot of radiologists – in developing countries, for example.”
Another potential landmine involves legal liability. If AI systems are held to stricter liability standards than human clinicians, then “health care organisations may shy away from automation strategies involving AI, even when they are cost-effective,” Ahsen said.
The findings are potentially applicable to other areas of medicine such as pathology and dermatology, where diagnostic accuracy is critical, but AI is potentially able to improve workflow efficiency.
With the infinite work capacity of AI, “we can use it 24/7, and it doesn’t need to take a coffee break,” Ahsen said.
“AI is only going to continue to make inroads into health care, and our framework can guide hospitals, insurers, policymakers and health care practitioners in making evidence-based decisions about AI integration.
“We’re not just interrogating what AI can do – we’re asking if it should do it, and when, how and under what conditions it should be deployed as a tool to help humans.”
Cancer
Federal gov should fund drug to treat breast cancer and endometriosis, Aus committee says

Australia’s drug advisory committee has recommended wider funding of triptorelin for women with breast cancer or endometriosis.
The recommendation comes after AstraZeneca announced plans to remove Zoladex from the market, risking leaving more than 7,500 women with breast cancer without an alternative treatment.
Both medicines block the release of oestrogen and testosterone and can be used as part of treatment, or for fertility preservation, in some forms of cancer.
The Pharmaceutical Benefits Advisory Committee met urgently in July and recommended making triptorelin unrestricted under the Pharmaceutical Benefits Scheme (PBS), which would mean it was funded for all uses.
The drug has been listed on the PBS for prostate cancer since 2006.
Triptorelin and Zoladex can also be used to treat endometriosis and to block puberty for either precocious puberty or gender-affirming care.
Vicki Durston, director of policy and advocacy at Breast Cancer Network Australia, described the recommendation as “a significant step forward” and said access to the medicine could mean the difference between life and death for some patients.
She said some women had already chosen to have their ovaries removed because of uncertainty over Zoladex supplies.
Marilla Druitt, Victorian state chair of the Royal Australian and New Zealand College of Obstetricians and Gynaecologists, said it remained unclear whether triptorelin would work exactly the same way as Zoladex, but the recommendation was likely to be positive for patients with endometriosis and pelvic pain.
She said: “I’m glad we’ve got an alternative.”
“That’s fantastic, and it remains to be seen whether or not it will be as good, but pain is so complex, pain is a really hard thing to study because it’s got so many contributors.”
Druitt said further research would be needed after the medicine was introduced.
If accepted by the federal government, the recommendation would also allow PBS funding of triptorelin for puberty suppression in precocious puberty and gender-affirming care.
This would make gender-affirming care federally funded through the PBS for the first time and would remove a financial barrier for transgender children in Queensland and the Northern Territory.
Stuart Aitken, medical director of Gender Health Australia, said the recommendation had sparked “absolute joy” among his patients.
He said: “It takes away a huge barrier to accessing evidence-based care.”
“It means that the ban has a very limited effect.”
Cancer
AI tool can predict breast cancer progression

An AI tool has identified microscopic breast cancer patterns that could help medical professionals better forecast disease progression.
The tool, called CenSegNet, was developed to analyse hundreds of thousands of cells in tumour samples and detect abnormalities in structures known as centrosomes.
Centrosomes are small structures inside cells that ensure DNA is divided equally during cell replication. Researchers say abnormalities in these structures have been considered a hallmark of cancer for more than a century.
In cancerous tissue, centrosomes can replicate excessively, driving the progression of the disease.
Scientists at the University of Southampton used the system to study tissue from 127 breast cancer patients being treated at University Hospital Southampton.
More than 330,000 centrosomes were analysed, revealing two distinct abnormalities that had previously been considered part of the same process.
One involved cells developing too many centrosomes, while the other involved centrosomes becoming abnormally enlarged.
Researchers found the two defects behaved independently and could occur in different areas of the same tumour.
Dr Salah Elias, of the University of Southampton’s school of biological sciences and institute for life sciences, said: “For more than a century, centrosome abnormalities have been recognised as a hallmark of cancer, but studying them in patient tissues has been extremely challenging.
“CenSegNet allows us to analyse these defects at single-cell resolution across entire tumours and uncover patterns that were previously impossible to see.
“Rather than viewing centrosome abnormalities as a single phenomenon, our study shows that they have distinct biological states with different spatial distributions and clinical associations.”
The platform also helped uncover a link between different centrosome abnormalities and features of cancer.
Tumours with high levels of enlarged centrosomes were more aggressive, while patients whose cells had lower levels had a better chance of survival.
Dr Elias said: “Specific combinations of defects may influence how a tumour grows, invades surrounding tissues and responds to treatment.
This opens the door to developing new biomarkers and, ultimately, more personalised treatment strategies.”
Researchers hope AI could eventually be used to track disease by analysing the behaviour of cell structures.
The team also plans to combine CenSegNet with more data to explore whether it could help guide treatment decisions.
Diagnosis
Glaucoma drugs could one day be used to treat breast cancer – study

Glaucoma drugs could potentially be repurposed to treat aggressive breast cancer after researchers identified markers linked to response.
Scientists found that several cancers, including breast cancer, melanoma and a type of blood cancer, rely on the same molecule to become aggressive and spread.
Drugs that block the molecule are already used to treat glaucoma and may therefore have potential as cancer treatments.
Researchers also identified markers that could help indicate which patients may respond well to the drugs.
Experts said the findings could help establish which patients may benefit from existing treatments.
Repurposing medicines already shown to be safe could also allow treatments to reach patients faster.
Lead author Victoria Sanz Moreno, professor of cancer cell and metastasis biology at The Institute of Cancer Research in London, said: “Some cancers are particularly aggressive, and once they spread they become very hard to treat.
“Catching these aggressive cancers and preventing their ability to move around the body is really crucial to our mission to keep more people living well with cancer.
“Our research has identified a shared weakness of aggressive cancer cells that could be targeted across many cancer types, wherever they originate in the body.
“We confirmed our findings in aggressive cancers such as breast cancer, melanoma, and a type of blood cancer called acute myeloid leukaemia, but we believe this molecular fingerprint of cancer cells likely to die after treatment applies to many more cancer types.
“It’s reassuring to know that a treatment already exists – a drug currently being used safely in some patients could be adapted to treat these cancers.”
Researchers set out to find markers that could identify which cancers would respond well to drugs blocking ROCK, also known as Rho kinase.
Aggressive cancer cells rely on ROCK as they spread around the body and cause advanced disease that is harder to treat.
The molecule keeps the scaffolding inside cells tense, causing them to contract and become round and generating enough force for cancer cells to squeeze through tissue.
The team, working in the Breast Cancer Now Toby Robins Research Centre at The Institute of Cancer Research, examined data from a drug-sensitivity database to identify which cancer cells responded to ROCK inhibitors.
Breast cancer cells that responded to ROCK inhibitors had a particular gene called E-Cadherin that was not working properly.
In melanoma, responsive cells tended to have a more rounded shape and high activity in a signalling pathway called NFKB.
Acute myeloid leukaemia cells that responded well to ROCK inhibitors had a specific subset of genetic alterations.
Researchers then tested the findings in laboratory tumour samples and mouse studies.
They hope tumour biopsies showing these markers could eventually help identify patients who may respond well to ROCK inhibitors.
Dr Simon Vincent, chief scientific officer at Breast Cancer Now, said: “With around 11,500 women tragically dying from breast cancer every year in the UK, research like this is vital to finding more effective treatment options.
“This study helps to lay the foundation for understanding who among those with certain cancers, including breast cancer, might benefit most from existing drugs. Finding new uses for existing treatments, which we know people can safely take, is easier and faster than developing new cancer drugs from scratch.
“It’s encouraging that these drugs may be especially effective in targeting cancer cells that are more likely to spread and resist treatment.
“While this research is still at an early stage and clinical trials are needed, it’s an important step towards more personalised breast cancer treatments in the future.”
First author Jaume Barcelo, formerly a postdoctoral research fellow at The Institute of Cancer Research in London and now based at Barts Cancer Institute at Queen Mary University of London, said: “Our study has identified a specific pattern of features that is consistent across many cancer types, and that can be used to match the right patients to this treatment.
“The next stage for this research will be to test how these drugs that inhibit ROCK work in combination with other treatments, to maximise the benefit for patients.
“As ROCK inhibitors are already approved to treat glaucoma, I hope that our findings can be used to progress the drugs into clinical trials to treat cancer in the near future.”
The research was funded by The Institute of Cancer Research, Breast Cancer Now, Barts Cancer Charity, Cancer Research UK, Worldwide Cancer Research and UK Research and Innovation.
Susanna Daniels, chief executive officer of Melanoma Focus, said: “Despite major advances in melanoma treatment over the past decade, too many people still die from the disease each year, and not every patient responds to the treatments currently available.
“Every new discovery improves our understanding of how melanoma grows and survives, bringing us closer to treatments that are more effective, more targeted and have the potential to improve survival.
“While these findings are still at an early stage and will need to be tested in clinical trials, they offer an encouraging direction for future melanoma research and the development of more personalised treatments.”
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