AI Imaging Technology Aims to Reduce Repeat Breast Cancer Surgeries

Breast cancer remains one of the most significant health challenges for women worldwide. It is responsible for 
approximately one in six cancer deaths among women and affects millions each year, including an estimated four 
million in the United States alone [1]. Early detection through routine screening plays a crucial role in improving 
survival rates. However, tumors can still be missed during screening, particularly in patients with dense breast tissue.
Medical imaging technologies such as X-rays, ultrasound, and computed tomography (CT) scans are commonly used 
to screen patients and evaluate tumor size, shape, and location. While these tools are effective for diagnosis, ensuring 
that the entire tumor is removed during surgery remains a challenge. Many patients who undergo breast-conserving 
surgery must wait several days to learn whether cancerous tissue remains, potentially requiring an additional 
operation. This leads to significant stress and anxiety for the patient, while also adding potential additional burden 
on the healthcare system.

Recent advances in artificial intelligence (AI) may help address this issue. Perimeter Medical Imaging has received 
pre-market approval from the U.S. Food and Drug Administration (FDA) for Claire, the first AI-enabled optical 
coherence tomography (OCT) imaging system designed for breast cancer surgery. The system aims to help surgeons 
identify tumor margins more accurately during procedures, potentially reducing the need for repeat surgeries.
Claire uses optical coherence tomography, an imaging technique that operates similarly to ultrasound but uses light 
waves instead of sound waves, to produce high-resolution images. The system analyzes light reflected from tissue 
depths of up to 2 millimeters, generating detailed images of tissue specimens in real time [2]. Compared to standard 
imaging modalities such as X-ray or ultrasound, Claire can provide approximately ten times greater resolution [3].

The AI component of the system was trained using Perimeter’s proprietary database of more than two million breast 
tissue images, allowing the device to recognize patterns associated with cancerous tissue [4]. With a reported margin 
assessment accuracy of 88.1%, Claire is designed to assist surgeons in identifying residual tumor tissue during the 
operation [3]. This system will guide the surgical team to ensure that all the cancerous cells are removed on the first 
attempt.
Another advantage of the system is its compatibility with existing surgical dyes and tracers, allowing it to integrate 
with current surgical workflows and future imaging techniques as they evolve.
Currently, patients may wait up to ten days after surgery to determine whether additional tissue must be removed. 
By providing real-time imaging and AI-assisted analysis during surgery, Claire has the potential to help surgeons 
confirm that the entire tumor has been removed on the first attempt, improving patient outcomes and reducing the 
need for repeat procedures.

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References
[1] M. Arnold et al., “Current and future burden of breast cancer: Global Statistics for 2020 and 2040,” The Breast, 
vol. 66, pp. 15–23, Dec. 2022. doi:10.1016/j.breast.2022.08.010 
[2] “OCT imaging for Intraoperative Margin Visualization,” Perimeter Medical, https://perimetermed.com/howoct-works/ (accessed Mar. 12, 2026). 
[3] “Perimeter Medical Imaging Ai’s ‘Claire’ becomes first FDA-approved AI-Enabled Imaging Device for Breast 
Cancer Surgery,” AdvaMed®, https://www.advamed.org/industry-updates/news/perimeter-medical-imaging-aisclaire-becomes-first-fda-approved-ai-enabled-imaging-device-for-breast-cancer-surgery/ (accessed Mar. 12, 2026). 
[4] “How perimeter OCT fits into surgical workflow,” Perimeter Medical, 
https://perimetermed.com/products/perimeter-claire/ (accessed Mar. 12, 2026). 

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