Cancer
Patients support AI as radiologist backup in screening mammography
The results of a large survey from a diverse patient population revealed cautious support for artificial intelligence (AI) implementation in screening mammography, according to a new study.
While the diagnostic accuracy of AI systems has drastically improved in recent years, there is still a lack of widespread adoption and acceptance of this technology for a variety of reasons, such as concerns with data privacy, algorithmic bias or even level of knowledge of AI.
One opinion that is frequently overlooked in the conversation surrounding the growth of AI in radiology is that of the patient.
“Patient perspectives are crucial because successful AI implementation in medical imaging depends on trust and acceptance from those we aim to serve,” said study author Basak Dogan, clinical professor of radiology and director of breast imaging research at the University of Texas Southwestern Medical Center in Dallas.
“If patients are hesitant or skeptical about AI’s role in their care, this could impact screening adherence and, consequently, overall health care outcomes.”
To gain a better understanding of patient opinions and concerns regarding the use of AI in screening mammography, Dr. Dogan and colleagues developed a 29-question survey to be offered to all patients who attended their institution for a breast cancer screening mammogram. The optional survey was available for a period of seven months in 2023.
All survey questions were closed-ended and assessed the participants’ knowledge and perceptions of AI. The survey obtained demographic information in addition to clinical information, which uncovered a respondent’s history with breast cancer, such as whether they had any abnormal mammograms in the past or if they or a close family member has ever had breast cancer.
Of the 518 patients who completed the survey, most indicated support for the use of AI alongside a radiologist’s review, with 71 per cent of respondents preferring AI to be used as a second reader. This was despite concerns about loss of personal interaction with the radiologist, data privacy, lack of transparency and bias. Less than 5 per cent were comfortable with AI alone interpreting their screening mammogram.
Because of its large and diverse patient population, the survey uncovered a variety of demographic factors that influence patient perceptions. Respondents with more than a college degree or a higher self-reported knowledge of AI were two times more likely to accept AI involvement in their screening mammogram.
Of note, Hispanic and non-Hispanic Black respondents reported significantly higher concerns about AI bias and data privacy, which most likely resulted in a lower acceptance of AI among these patient groups.
“These results suggest that demographic factors play a complex role in shaping patient trust and perceptions of AI in breast imaging,” Dr. Dogan added.
Familial and personal medical history also impacted patient attitudes toward AI.
Regardless of whether an abnormality was detected by AI or a radiologist, patients who had a close relative diagnosed with breast cancer were more likely to request additional reviews. However, these patients exhibited a high degree of trust in both AI and radiologist reviews when the mammogram came back as normal.
In contrast, patients with a history of an abnormal mammogram were more likely to pursue diagnostic follow-up if AI and radiologist reviews conflicted. This was especially the case if it was AI that flagged an abnormality.
“This highlights how personal medical history influences trust in AI and radiologists differently, emphasising the need for personalised AI integration strategies in mammographic screening,” Dr. Dogan said.
The researchers noted that it is important to continue engaging with patients to understand their evolving views of AI technology in health care, as the technology continues to advance.
“Our study shows that trust in AI is highly individualised, influenced by factors such as prior medical experiences, education and racial background,” Dr. Dogan said.
“Incorporating patient perspectives into AI implementation strategies ensures that these technologies improve and not hinder patient care, fostering trust and adherence to imaging reports and recommendations.”
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.”
The FDA has delayed approval of camizestrant while it reviews new analyses submitted by AstraZeneca after advisers voted against the breast cancer drug.
The US regulator had been considering whether to approve the oral treatment after a phase 3 switching study in a specific group of breast cancer patients.
Camizestrant is an oral SERD, or selective oestrogen receptor degrader. These drugs are designed to block and break down oestrogen receptors that can help some breast cancers grow.
AstraZeneca filed for approval based on the phase 3 Serena-6 trial, which tested a treatment-switching approach.
Patients in the study received an aromatase inhibitor and a CDK4/6 inhibitor. Aromatase inhibitors lower oestrogen levels, while CDK4/6 inhibitors are targeted cancer drugs that help slow cancer cell growth.
After detecting an ESR1 mutation, investigators switched the aromatase inhibitor to camizestrant.
An ESR1 mutation is a change in a gene linked to the oestrogen receptor. It can make some breast cancers less responsive to standard hormone treatments.
AstraZeneca said switching to camizestrant was linked to a 56 per cent increase in progression-free survival.
Progression-free survival measures how long a patient lives without their disease getting worse.
However, the FDA raised questions about the study design.
An FDA advisory committee later voted six to three that AstraZeneca had failed to show camizestrant provides a clinically meaningful benefit.
The vote was a setback for the company’s hopes of approval, although the FDA can go against advisory committee recommendations.
After the setback, AstraZeneca submitted additional analyses requested by the FDA.
The company said the analyses include data on circulating tumour DNA clearance linked to longer-term efficacy outcomes.
Circulating tumour DNA refers to fragments of genetic material from cancer cells that can be found in the blood.
AstraZeneca is expected to share the data next week at the American Society of Clinical Oncology annual meeting.
The FDA has now delayed its ruling while it reviews the additional information. AstraZeneca did not provide a new decision date.
Three-month delays are typical and, during the second Trump administration, have been common.
After budget cuts reduced its workforce, the FDA delayed rulings on assets including Bayer’s Lynkuet, Biohaven’s troriluzole and Sanofi’s tolebrutinib. The FDA reportedly blamed a “heavy workload and limited resources” for one delay.
The agency has continued to delay rulings this year, with Biogen, Savara and Travere Therapeutics among the companies to say the FDA has extended reviews of their drugs.
Like AstraZeneca, those three companies faced delays after submitting additional information that the agency needed time to review.
If the additional analyses address the regulator’s concerns, AstraZeneca could still secure approval for a drug it has estimated could generate peak sales of more than US$5bn.
Guggenheim Securities analysts recently described the Serena-6 study as “a limited commercial opportunity in our and [AstraZeneca’s] view”.
AstraZeneca is also running two adjuvant studies and a trial in a first-line setting as it seeks to position camizestrant across different stages of breast cancer care.
Adjuvant treatment is given after primary treatment, such as surgery, to reduce the risk of cancer returning. First-line treatment is the first therapy given for a disease.
Roche reported the failure of its rival oral SERD in first-line breast cancer in March, but AstraZeneca executives have argued that their trial designs and drug candidate are different.
Last week, Europe’s Committee for Medicinal Products for Human Use issued a positive opinion on camizestrant.
The drug is expected to be marketed as Etcamah in Europe.
An early PET scan after one cycle of chemotherapy may help predict how aggressive breast cancer responds to treatment, a study suggests.
Research led by The Institute of Cancer Research, London and King’s College London suggests that an early scan taken after one cycle of chemotherapy could help predict how well a patient’s cancer will respond to treatment.
The study focused on patients with triple-negative breast cancer (TNBC), an aggressive form of the disease in which cancer cells lack receptors for the hormones oestrogen and progesterone, as well as the HER2 protein.
Patients with TNBC are usually treated with chemotherapy prior to surgery. While many respond well, residual disease at surgery, typically around six months later, is associated with a significantly poorer prognosis. Identifying people sooner who are unlikely to respond remains a major clinical challenge.
The research explored whether using PET imaging shortly after treatment begins, rather than relying only on MRI scans later in the treatment process, could provide earlier insight into how a patient’s cancer is responding. Twenty-two patients were recruited, with fourteen undergoing FDG-PET scans before treatment and after the first cycle of chemotherapy.
The findings, published in Clinical Cancer Research, showed that changes seen on PET scans after just one cycle of chemotherapy were strongly associated with subsequent response, including whether there was no detectable cancer, known as a complete response, by the end of treatment. Importantly, early PET response showed stronger associations with treatment outcomes than standard mid-treatment MRI scans in this study.
Being able to identify patients who are not responding well at an early stage could allow clinicians to adjust treatment sooner or consider alternative approaches. These findings may also support future strategies to better tailor treatment intensity to individual patients.
The study also compared two types of PET tracers, FDG and FLT, to determine which was most suitable. While both met the study’s technical criteria, FDG-PET was selected for further evaluation due to its better image quality, greater consistency and wider use in clinical practice.
The research also explored how imaging changes after just one cycle of chemotherapy relate to the body’s immune response to treatment. Biopsies taken before and after the first cycle of chemotherapy showed that an increase in immune cells within the tumour was strongly associated with both early PET changes and improved treatment outcomes.
The researchers emphasise that these findings now need to be validated in larger studies. Future work will aim to confirm these results in broader patient groups and explore more accessible imaging approaches, such as ultrasound, alongside PET and MRI.
Sheeba Irshad, professor of cancer immunology at King’s College London and lead of the Breast Cancer Now KCL Research Unit, said:
“In patients who had PET scans both before treatment and after the first cycle, we found that this early scan could predict whether they were likely to achieve a complete response by the end of treatment. These findings highlight the potential of early imaging to guide treatment decisions, and now need to be validated in larger, modern clinical trials.”
Andrew Tutt, professor of breast oncology at The Institute of Cancer Research, London, said:
“Research that helps us determine early who is already benefitting from standard neoadjuvant chemotherapy and who might benefit from clinical trials to find better treatments is vital. This study shows that FDG-PET may have great value in this regard. We hope to be able to design studies that further investigate and validate these findings.”
The study was supported by funding from King’s College London and Guy’s and St Thomas’ NHS Foundation Trust, Breast Cancer Now, Cancer Research UK, and Guy’s and St Thomas’ Charity.
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