Technology to Reduce Breast Biopsies
Hester Hill Schnipper, LICSW, OSW-C Program Manager, Oncology Social Work
OCTOBER 18, 2017
Machine learning identifies breast lesions likely to become cancerA machine learning tool can help identify which high-risk breast lesions are likely to become cancerous, according to a new study appearing online in the journal Radiology. Researchers said the technology has the potential to reduce unnecessary surgeries.
High-risk breast lesions are biopsy-diagnosed lesions that carry an increased risk of developing into cancer. Because of that risk, surgical removal is often the preferred treatment option. However, many high-risk lesions do not pose an immediate threat to the patient's life and can be safely monitored with follow-up imaging, sparing patients the costs and complications associated with surgery.
"There are different types of high-risk lesions," said study author and radiologist Manisha Bahl, M.D., M.P.H., from Massachusetts General Hospital (MGH) and Harvard Medical School, both in Boston. "Most institutions recommend surgical excision for high-risk lesions such as atypical ductal hyperplasia, for which the risk of upgrade to cancer is about 20 percent. For other types of high-risk lesions, the risk of upgrade varies quite a bit in the literature, and patient management, including the decision about whether to remove or survey the lesion, varies across practices."