Breast-conserving surgery, or lumpectomy, is a treatment for early-stage breast cancer. It’s important for surgeons to remove enough tissue around the tumor to ensure that no cancer cells are left, but still conserve the surrounding healthy tissue as much as possible. Traditionally, this requires a slow process of staining and examining tissue under a microscope.

Researchers at NIST have developed a faster imaging method using hyperspectral dark-field microscopy. This technique uses different wavelengths of light to distinguish between cancerous and healthy cells without staining. It can be used on fresh tissue samples during surgery, providing immediate feedback to the surgeon. This reduces the need for follow-up surgeries by ensuring that all cancerous tissue is removed in the first operation.

This new method, combined with machine learning, accurately identifies cancer cells and could greatly improve breast cancer treatment and patient care. 

As breast cancer remains a leading cause of cancer-related deaths in women, innovations like these are crucial in improving treatment and overall patient care.

Learn more about the method.