Profound Predictions
For patients diagnosed with glioma, a deadly form of brain tumor, the future can be very uncertain. While gliomas are often fatal within two years of diagnosis, some patients can survive for ten years or more. Predicting the course of a patient’s disease at diagnosis is critical in selecting the right therapy.
Researchers at Emory and Northwestern Universities have developed artificial intelligence software that can predict the survival of patients diagnosed with glioma by examining data from tissue biopsies. The approach, described in Proceedings of the National Academy of Sciences, is more accurate than the predictions of doctors.
Doctors currently use a combination of genomic tests and microscopic examination of tissues to predict how a patient’s disease will behave clinically or respond to therapy. While reliable, genomic testing does not completely explain patient outcomes. Microscopic examination is used to further refine prognosis; however, it is very subjective and interpretations can impact critical treatment decisions.
Researchers used an approach called deep learning to train software to learn visual patterns associated with patient survival using microscopic images of brain tumor tissue samples. The breakthrough resulted from combining this advanced technology with more conventional methods that statisticians use to analyze patient outcomes. When the software was trained using both images and genomic data, its predictions of how long patients survive beyond diagnosis were more accurate than those of human pathologists. The study used public data produced by the National Cancer Institute’s Cancer Genome Atlas project to develop and evaluate the algorithm.
“The eventual goal is to use this software to provide doctors with more accurate and consistent information. We want to identify patients where treatment can extend life,” says Lee Cooper, lead author and a professor of biomedical informatics at Emory School of Medicine and Winship Cancer Institute. Lead neuropathologist Daniel Brat, who began developing the software while at Emory, is now chair of pathology at Northwestern University Feinberg School of Medicine.
