Every year in the United States, a quarter of a million women are diagnosed with breast cancer. Of these, approximately 180,000 undergo surgery to remove the cancer and also keep as much of the healthy breast tissue as possible, according to medicalnewstoday.
The problem is that, even after the surgery has been performed, it’s difficult to know for sure whether the cancer has been completely removed. The standard post-op analysis, known as the gold-standard analysis, takes a day or more to present the results of an operation clearly. As a result, about 25% of women who undergo lumpectomies will require a second surgery to eliminate remaining cancer tissues.
First developed in the mid 20th-century, the gold-standard method involves slicing and staining tissue to highlight malignant cells, and subsequent lab analyses, before finally returning results to the surgeon for review. With obvious flaws visible in this system, new imaging technology, known as photoacoustic imaging, presents an interesting alternative.
Developed by researchers at the Washington School of Medicine in St. Louis and the California Institute of Technology, photoacoustic imaging works by using light-beams to scan tumor samples. As the light-beams are absorbed by the molecule, energy is released as sound, which can then be used to create an image.
To test their technology, researchers scanned slices of tumors removed from three breast cancer patients, in addition to staining those same samples according to standard procedures. Analysis confirmed that photoacoustic images matched up to stained samples across all key features.
Deborah Novack, (MD, PhD and associate professor of medicine, pathology and immunology) said that, “It’s the pattern of cells – their growth pattern, their size, their relationship to one another – that tells us if this is normal tissue or something malignant … overall, the photoacoustic images had a lot of the same features that we see with standard staining, which means we can use the same criteria to interpret the photoacoustic imaging.”
While promising, this technology requires further advancements in speed before being utilized during operations. Another of the researchers, Lihong Wang, PhD, said that the team expects “to be able to speed up the process. For this study, we had only a single channel for emitting light. If you have multiple channels, you can scan in parallel and that reduces the imaging time. Another way to speed it up is to fire the laser faster. Each laser pulse gives you one data point. Faster pulsing means faster data collection.”