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.”