Doctors may soon have another weapon in the battle against cancer.
A new imaging software could help detect breast cancer by scanning microscopic images of breast tissue for over 6,000 characteristics of cancer. The software helped predict breast cancer severity in two groups of women, and could be a useful tool for gauging a patient’s chance of survival.
The new software could update techniques used since the 1920’s for detecting breast cancer.
Andrew Beck and colleagues developed C-Path with the goal of identifying additional features of cancer tissue that could help paint a more accurate picture of survival outcome.
They tested C-Path on tissue samples from a group of patients in the Netherlands.
The software found a set of brand-new features associated with a poor chance of survival.
In a separate group of patients from Vancouver, C-Path predicted the chance of survival in women based on a comprehensive set of already known and new cancer tissue features. Classifying the tissue as epithelial or stromal, an important part of cancer diagnosis, took a bit more work: the team had to teach the computer program how to spot each tissue type using hand-marked samples.
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