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E-Newsletter • October 2026 |
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Editor's E-Note
October is Breast Cancer Awareness month, and this month we’re highlighting an interesting advance in treatment. Cancer margin assessment is a critical part of breast cancer surgery, but assessing margins during lumpectomy can be challenging. A recently FDA-approved tool that uses optical coherence tomography (OCT) is designed to make that task more accurate.
Intermountain Health in Salt Lake City is the first health system to adopt the intraoperative device, and the health system’s surgeons have high hopes for its effect on patient outcomes. A consensus guideline on ductal carcinoma in situ treated with lumpectomy and whole-breast radiation defines a 2 mm margin as adequate because it lowers the rate of local recurrence compared with narrower negative margins. Research shows OCT producing cross-sectional images to a depth of about 2 mm at approximately 10 times the resolution of ultrasound and specimen radiography and 100 times that of MRI. A study presented at the 26th Annual Meeting of the American Society of Breast Surgeons in May 2025 demonstrated a margin accuracy of 88.1% and a statistically significant reduction in residual cancer postsurgery, compared with the standard of care.
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Enjoy the newsletter.
— Dave Yeager, editor |
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| In This E-Newsletter
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Improvement at the Margins
By Beth Strohbusch
AI in the surgical suite enhances breast margin assessment.
Salt Lake City-headquartered Intermountain Health is the nation’s first health system to deploy an AI-centric breast cancer margin assessment solution following its FDA approval in March 2026. The microscopic tissue visualization system, called Claire, is being used for its earliest cases to help surgeons make more informed decisions while the patient is still in surgery.
“Microscopic cancer can be difficult to identify in the operating room. When you’re doing a lumpectomy, there's no way to know 100% that you have clear margins,” says Teresa Reading, MD, a breast surgeon at Intermountain Health LDS Hospital in Salt Lake City. “This device helps direct my attention to specific areas of concern, giving me more information to guide my decisions during these procedures.”
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Surgeons performing breast-conserving surgery have long faced a difficult challenge: remove too little tissue and risk leaving undetected cancer behind or remove too much and potentially affect cosmetic results. Reoperation rates within one year of surgery range from 15% to 21% and translate into 24% higher costs, according to a study published in 2024 in the Annals of Surgical Oncology. “The rates of reoperation after breast cancer surgery have remained high. Continuing efforts to reduce reoperation need more attention,” the study’s researchers concluded.
Reading says many ideas have been pursued to improve margin assessment over the years. “I really think this AI approach is on the right track and will be very helpful,” she says.
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AI May Help Identify Subtle Signs of Breast Cancer
A recent retrospective review found that AI tools may help radiologists identify more interval cancers. The findings raise the possibility that AI could provide an early warning signal, but the researchers note that prospective studies are needed.
AI Helps Radiologists Detect More Brain Aneurysms
A recent study of 3,856 CT angiography exams across a large, integrated health system found that AI helped increase brain aneurysm detection. Radiologists and an AI tool agreed in more than 96% of cases, but the AI tool found an additional 55 true-positive cases, a 39% increase.
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AI Model Identifies Patients at Risk of Treatment-Induced Lung Inflammation
Researchers have developed a new AI model that can use existing CT scans to identify lung cancer patients who are at risk of developing serious immunotherapy-related side effects before therapy is initiated. This development may help facilitate more personalized monitoring and prevention strategies.
Radiosurgery Shows Promise for Treatment-Resistant Depression
Incisionless radiosurgery was shown to significantly reduce symptoms of major depression and suicidal thoughts among patients with treatment-resistant psychiatric illness in a prospective observation study presented at the ASTRO annual meeting in September 2026. |
“My biggest hope is that this trains a generation of models that don’t just describe a finding but actually show where it is. A model shouldn’t only say, ‘There’s a nodule.’ It should put a marker on the exact voxel it’s talking about, so every statement comes with its evidence.”
— Pranav Rajpurkar, PhD, an associate professor of bioinformatics at the Blavatnik Institute at Harvard Medical School in Boston and senior author of a paper published June 18 in the New England Journal of Medicine that demonstrates the ability of an AI model to analyze CT scans and communicate results more effectively |
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COVER STORY
Sunset, Sunrise
Microsoft is sunsetting its PowerScribe 360 platform, and radiology departments are considering where they want to go from here.
FEATURE
Display Modes
Medical displays are essential equipment for radiologists, and changes in radiology are reflected in the latest offerings.
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