Using technology to improve breast cancer screening

To highlight Breast Cancer Awareness month, we’ll use this week’s Domain Knowledge to explore technologies being adopted in the breast health space. We’ll look at the use of artificial intelligence (AI) in conjunction with ultrasound, CT, and MRI to support radiologists in both the screening and detection of breast cancer.

The first study of its kind, MRI Screening Cost-Effective for Women With Dense Breasts, finds MRI breast cancer screening every 4 years to offer the greatest benefit for women with very dense breasts.

Using machine learning as a triaging tool for ultrasound studies is being investigated as a way to broaden access, make ultrasound a more effective tool in breast cancer screening and possibly become an alternative to mammography. Details of the work being done are outlined in AI tool increases radiologists’ accuracy at spotting breast cancer on ultrasound scans by 37%.

Using AI with CT helps predict breast cancer metastasis looks at the use of a deep learning algorithm to predict axillary lymph node metastasis. This information plays a role in patient prognosis and treatment decisions.

Busy radiologists could find the work highlighted in AI triages breast screening MRIs without missing a single cancer to be valuable and helpful. Those involved in the study believe they have shown it is possible to safely use artificial intelligence to dismiss breast screening MRIs without missing any malignant disease.

That’s a wrap for this week’s review of news and happenings in the healthcare AI space. In closing, I’ll leave you with an invitation to follow our interview with Dr. Amy Patel.

Each week during the month of October I'll post more of our discussion on the Breast Health Series: Advocating for Equity in Breast Care. During the series, we touch on challenges, potential solutions, and the growing use of technologies to improve breast care and screening.

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