UT Southwestern researchers have developed a software tool that uses artificial intelligence to recognize cancer cells from digital pathology images – giving clinicians a powerful way of predicting patient outcomes.
The spatial distribution of different types of cells can reveal a cancer’s growth pattern, its relationship with the surrounding microenvironment, and the body’s immune response. But the process of manually identifying all the cells in a pathology slide is extremely labor intensive and error-prone.
“As there are usually millions of cells in a tissue sample, a pathologist can only analyze so many slides in a day. To make a diagnosis, pathologists usually only examine several ‘representative’ regions in detail, rather than thoroughly examine the entire slide. However, some important details could be missed by this approach,” said Dr. Guanghua “Andy” Xiao, corresponding author of a study published in December in EBioMedicine and Professor of Population and Data Sciences at UT Southwestern.
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