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.”
Diagnosis
Lung cancer drug shows breast cancer potential
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.”
Insight
FDA approves Agilent test for ovarian cancer
Agilent has FDA approval for a test to identify ovarian cancer patients who may be eligible for immunotherapy.
Agilent’s PD-L1 IHC 22C3 pharmDx is the only FDA-approved companion diagnostic to help identify patients with epithelial ovarian, fallopian tube or primary peritoneal carcinoma whose tumours express PD-L1 and who may be eligible for treatment with KEYTRUDA, Merck’s anti-PD-1 therapy.
A companion diagnostic is a test used alongside a specific treatment to show whether a patient is suitable for that therapy. PD-L1 is a protein on some cancer cells that helps tumours evade the immune system.
These cancers affect the reproductive system and the lining of the abdominal cavity.
The test enables pathologists to assess PD-L1 expression at diagnosis to support treatment decisions in a disease where options remain limited for many.
This is the seventh FDA-approved companion diagnostic indication for PD-L1 IHC 22C3 pharmDx for use with KEYTRUDA.
Nina Green, vice president and general manager of Agilent’s clinical diagnostics division, said: “Delivering effective precision oncology requires close collaboration between diagnostics and therapeutics, and this FDA approval reflects Agilent’s long-standing industry partnership in companion diagnostics.
“We are proud to enable pathologists to identify patients with EOC who may benefit from immunotherapy.
“As the first immuno-oncology approval for this disease, this milestone underscores our commitment to advancing precision medicine and expanding access to innovative cancer treatments worldwide.”
PD-L1 expression with this test was evaluated in the KEYNOTE-B96 clinical trial supporting its use to identify patients who may benefit from KEYTRUDA.
In the US, ovarian cancer caused approximately 12,730 deaths in 2025 and the five-year survival rate was 51.6 per cent between 2015 and 2021.
In addition to these cancer types, the test is indicated in the US to help identify patients with non-small cell lung cancer, oesophageal squamous cell carcinoma, cervical cancer, head and neck squamous cell carcinoma, triple-negative breast cancer and gastric or gastro-oesophageal junction adenocarcinoma who may benefit from treatment with KEYTRUDA.
The test was developed by Agilent with Merck as a companion diagnostic for KEYTRUDA.
Cancer
Why this is your year to enter the Women’s Cancer Innovation award
Breakthroughs in cancer care don’t only come from large institutions or fully funded labs.
They also come from determined individuals, small teams, early-stage founders, clinicians with an idea, researchers testing a new approach, technologists building smarter tools and advocates redesigning how care is delivered.
If you’re building something that could change how we prevent, detect, treat, manage or live with cancer, the Women’s Cancer Innovation award sponsored by Endomag is for you.
This award is designed to spotlight organisations, technologies and individuals who are moving cancer innovation forward at any meaningful stage.
Innovation doesn’t have to fit one mold
When people hear “cancer innovation,” they often picture a new drug or medical device.
But meaningful progress happens across many areas, including digital health tools, diagnostics and early detection approaches, AI and data platforms, care delivery models, patient support solutions and more.
If your work addresses a real cancer challenge in a new or more effective way, it counts.
And you don’t need to be “finished.” Many companies delay applying for awards until everything feels polished and complete.
But the Femtech World Awards are as much about recognising momentum and potential as they are celebrating outcomes.
Judges and reviewers understand innovation journeys. They are often more interested in clarity of problem, strength of insight, and thoughtful design than in perfect execution.
Progress matters. Direction matters. Impact potential matters.
And finally, if you’re wondering “Is this good enough?” – apply.
Many strong applicants almost don’t apply. The most common hesitation isn’t lack of innovation – it’s self-doubt.
If you’re asking yourself whether your project is too early, your team too small, your work innovative enough, or whether it counts if you’re not a startup, those questions are normal.
They’re also often the very reason you should submit.
These awards exist because great work is sometimes overlooked, underfunded, or under-recognised.
The goal is to surface promising solutions and support the people building them.
Find out more about the Femtech World Awards and enter for free here.
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