Cancer
AI identifies women at high risk of breast cancer
AI technology can identify 42 per cent of breast cancers that develop between routine mammograms by flagging women at highest risk, researchers have found.
The study analysed 134,217 screening mammograms using a deep learning model known as Mirai, which estimates breast cancer risk from imaging data, tumour features and breast density.
Researchers from the University of Cambridge and Addenbrooke’s Hospital tested the tool on UK screening data collected between 2014 and 2016.
They identified 524 “interval cancers” — cases diagnosed between regular screening appointments.
The algorithm’s risk scores predicted 42.4 per cent of these interval cancers among women ranked in the highest 20 per cent for risk, equating to an additional detection rate of 1.7 cancers per 1,000 women screened.
Interval cancers tend to be more advanced when diagnosed, often larger or more aggressive than cancers found during routine screenings.
Co-author Fiona J. Gilbert is professor of radiology at the University of Cambridge and honorary consultant radiologist at Addenbrooke’s Hospital.
Gilbert said: “Interval cancers generally have a worse prognosis compared with screen-detected cancers because they tend to be either larger or more aggressive.
“That’s why it’s important to minimise the number of interval cancers that you have in any screening programme.”
The tool was most accurate for cancers developing within a year of screening, performing less well for those emerging after 12 to 36 months.
It was also less effective for women with extremely dense breast tissue — tissue with more glands and fibrous material than fat — which can make tumours harder to detect.
However, Mirai still outperformed conventional risk assessment tools.
Lead researcher Joshua W. D. Rothwell, an M.B.B.S./Ph.D. student at the University of Cambridge, said the findings could help identify women who need closer monitoring or additional imaging.
Rothwell said: “Our results suggest that further workup of mammograms within the top 20 per cent of scores could yield 42.4 per cent of interval cancers, meaning that Mirai could be used to identify women for supplemental imaging or a shortened screening interval.
In the UK, around 2.2 million women undergo breast screening each year through the triennial programme, which invites women for mammograms every three years.
The technology could refine this process by identifying those who would benefit from extra imaging such as MRI or contrast-enhanced mammography — an X-ray technique that uses dye to highlight areas of concern.
Gilbert said: “If we called back 20 per cent of women for supplemental imaging, we’d have to find the capacity to offer contrast-enhanced mammography or MRI to 440,000 women.
“Personalised breast cancer screening depends on accurately assessing an individual’s risk of developing breast cancer within a specific timeframe.
“We can use supplemental imaging and adjust screening frequency based on a woman’s breast density and likelihood of developing breast cancer within a short timeframe.”
Next steps include comparing commercially available predictive tools, conducting cost-effectiveness studies and running trials to identify which women would benefit most from additional imaging.
“Identifying women at increased risk of developing breast cancer is a complex, multifactorial problem,” Dr Gilbert said.
“The goal is to accurately identify the women most likely to have an interval cancer while minimising the amount of additional imaging required.”
A new ovarian cancer drug has been approved for NHS use in England, offering hundreds of women with hard-to-treat disease a life-prolonging treatment.
Elahere is the first new drug for chemotherapy-resistant ovarian cancer to be approved by the NHS for more than 20 years.
Ovarian cancer is the 18th most common type of cancer globally, affecting more than 300,000 women a year.
More than three-quarters of patients are diagnosed at an advanced stage, making the disease harder to treat.
Prof Ruth Plummer, national clinical lead for cancer drugs at NHS England, said: “This represents the most significant breakthrough in NHS treatment for these hard-to-treat ovarian cancers in over two decades – and we’re delighted it will now offer hundreds of women much-needed hope of precious extra time with their loved ones.”
Standard treatment for ovarian cancer usually involves surgery and chemotherapy, but about 80 per cent of patients with advanced disease relapse and most eventually develop resistance to chemotherapy.
According to the National Institute for Health and Care Excellence, patients with folate receptor-alpha-positive platinum-resistant epithelial cancers have until now had limited options when their tumours stop responding to standard chemotherapy.
Now NICE has approved mirvetuximab soravtansine, also known as Elahere, for patients with epithelial ovarian, peritoneal or fallopian tube cancer that has become resistant to platinum-based chemotherapy and whose tumours contain the FRα protein that the drug targets.
FRα is a protein found on the surface of some cancer cells.
NHS England said up to 400 women a year in England could benefit, in what it described as a major milestone for treatment.
Mirvetuximab soravtansine is given through a drip once every three weeks.
A global clinical trial involving eight NHS hospitals found that the treatment delayed cancer progression and prolonged survival by an average of four months, compared with chemotherapy alone, with more manageable side-effects.
Cancer progression means the disease is growing, spreading or worsening.
In 37 per cent of patients, tumours shrank by at least 30 per cent, compared with 16 per cent of those given chemotherapy.
The drug, made by AbbVie, combines a “homing” antibody, which seeks out the FRα protein on the surface of cancer cells, with a cancer-killing molecule that destroys the cell from within.
Experts said the decision was a seminal moment and could significantly improve the quality of life of affected patients.
Rachel Downing, head of policy and external affairs at Target Ovarian Cancer, said: “This is a hugely important moment for women with platinum-resistant ovarian cancer and their families, who have faced limited effective treatment options for far too long. Today’s announcement offers real hope of improved quality of life.”
Victoria Clare, chief executive of the charity Ovacome, said: “Today marks a landmark moment. Being told that platinum-based chemotherapy is no longer working can bring anxiety and uncertainty, particularly when the disease is at an advanced stage, where time and options are limited.
“This recommendation is the first in over 20 years to offer the ovarian cancer community an additional choice at a critical stage, with the potential to make a real difference to patients and their families.”
Helen Knight, director of medicines evaluation at NICE, said: “We heard clearly from patients and clinicians about the very limited options available at this stage of the disease and the substantial burden that chemotherapy places on women’s lives.
“We are pleased that, following a robust process and a new commercial arrangement with AbbVie, we are now able to recommend this treatment for NHS use.”
AI may help speed breast cancer diagnosis for high-risk women after abnormal mammograms, a study suggests.
Women with abnormal mammograms often wait weeks to learn whether they have breast cancer.
Researchers at UC San Francisco and UC Berkeley said an AI-guided workflow could help reduce that wait by quickly identifying those most likely to have the disease. Some women could move from imaging to evaluation, and sometimes biopsy, in a single day.
Dr Maggie Chung, first author of the study, said: “This is a really an exciting time.
“This moves us closer to personalised care, where we can tailor a plan so that each patient gets the right intervention at the right time.”
The study used an open-source AI model called Mirai.
The model was trained on hundreds of thousands of mammograms linked to patients’ cancer outcomes.
A mammogram is an X-ray scan of the breast used to look for signs of cancer. A biopsy involves taking a small tissue sample to test for disease.
The AI tool is designed to detect subtle patterns in screening mammograms and predict a woman’s cancer risk.
Researchers at UC San Francisco and UC Berkeley applied the model to more than 4,100 screening mammograms at Zuckerberg San Francisco General Hospital and Trauma Center.
Mirai identified 525 women, about 12.7 per cent of screened patients, as high risk.
Those patients could receive an interpretation of their mammograms immediately after the scan and have additional diagnostic imaging for suspicious areas on the same day.
Some women who needed biopsies were also able to have them on the same day.
The researchers said Mirai reduced the wait time for diagnostic evaluation from several weeks to about an hour.
For women who were ultimately diagnosed with breast cancer, it reduced the average wait for biopsy from more than two months to fewer than 10 days.
The researchers stressed that Mirai does not replace radiologists or make diagnoses on its own.
Instead, it acts as a triage tool to help physicians identify the patients who can benefit most from accelerated care.
The team analysed more than 114,000 archival mammograms before launching the programme, to ensure the model would capture enough high-risk patients without overloading the clinic with too many expedited evaluations.
The researchers said they hope AI will support a more personalised approach to breast cancer screening tailored to each patient’s breast cancer risk.
Chung said: “Right now, many women follow the same screening schedule but their individual risk can be very different.
“AI risk assessment gives us the chance to identify the women most likely to benefit from expedited care and get them what they need.”
Adam Yala, senior author of the study and a data scientist at UC Berkeley, said: “This is a powerful example of how AI can be a collaborative partner for physicians.
“It shows how we can improve care when we bring clinicians and data scientists together to design these systems.”
A genomic test may help some women with breast cancer avoid chemotherapy, with near-identical outcomes in an international trial.
The findings suggest patients with a low test score could be treated with hormone therapy alone without increasing the risk of their cancer returning.
Researchers said the results could support more personalised treatment decisions and spare some women the side-effects of chemotherapy.
Prof Rob Stein, the trial’s chief investigator and a professor of breast oncology at UCL, said: “Optima addresses a longstanding challenge in breast cancer care: identifying who truly benefits from chemotherapy and who does not.
“Our findings show that many patients can safely avoid chemotherapy without compromising their outcomes.
“These results mark an important and significant step toward more personalised treatment.
“The trial has successfully used tumour biology to guide decisions rather than relying solely on traditional clinical features.”
Breast cancer treatment usually involves surgery to remove tumours. Chemotherapy is then often recommended if doctors believe there is a risk the disease will return.
Chemotherapy can cause side-effects including hair loss, rashes, nausea, insomnia and fatigue. Some women may also face longer-term consequences such as infertility, cognitive impairment or early menopause.
The Optima trial followed more than 4,000 patients with newly diagnosed breast cancer in the UK, Norway, Sweden, Australia, New Zealand and Thailand.
The trial was led by University College London.
One woman who took part in the trial told the Guardian that being able to skip chemotherapy felt “like Christmas”. Nine years after being diagnosed, taking the test and skipping chemotherapy, she is healthy and enjoying a full and active life.
The trial tested whether a genomic test could identify which patients need chemotherapy and which could safely avoid it.
The Prosigna test, made by diagnostics company Veracyte, analyses the activity of 50 genes in tumour tissue. It identifies the molecular subtype of the cancer and gives a score estimating the risk of breast cancer returning in the next 10 years.
The randomised trial involved 4,429 patients aged 40 or over with hormone-positive breast cancer. Hormone-positive breast cancer grows in response to hormones such as oestrogen or progesterone. It is the most common form of breast cancer, accounting for up to 80 per cent of cases globally.
Participants were assigned to one of two groups. In the standard treatment group, patients received chemotherapy followed by hormone therapy.
In the second group, patients had their tumours analysed using the genomic test. Those with a high score received chemotherapy and hormone therapy. Those with a low score received hormone therapy alone.
Radiotherapy and other treatments were given as usual in both groups.
In the second group, outcomes were very similar whether chemotherapy was given or not. Five years after treatment, 95 per cent of patients who had chemotherapy and hormone therapy were alive and free from breast cancer recurrence, while 94 per cent of those who skipped chemotherapy were also alive and recurrence-free.
The findings suggest chemotherapy offered little or no additional benefit for patients with low test scores.
Some men also took part in the study, but researchers said there were too few to draw firm conclusions for this group.
The trial received funding from the National Institute for Health and Care Research, Veracyte and cancer charities.
Prof Iain MacPherson, a co-chief investigator and professor of breast oncology at the University of Glasgow, said: “Optima provides robust, practice-changing evidence that we can safely reduce the use of chemotherapy for many patients with hormone-sensitive breast cancer.
“These findings represent a major step forward in delivering more personalised, precise care, ensuring that treatment decisions are driven by what will genuinely improve outcomes for patients, while avoiding unnecessary toxicity.
“The potential impact for both patients and health services is substantial.”
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