Researchers from the Perelman School of Medicine at the University of Pennsylvania in Philadelphia developed a tool that uses artificial intelligence to image cells and provide insight into gene activity.
A paper published Jan. 2 in Nature Biotechnology by Daiwei "David" Zhang, PhD, and Mingyao Li, PhD, explains the technology and aims of the Inferring Super-Resolution Tissue Architecture (iStar). iStar's purpose is to detect "tertiary lymphoid structures": anti-tumor formations that correlate with a patient's likelihood of survival and positive response to immunotherapy.
Dr. Li said iStar "can capture the overarching tissue structures and also focus on the minutiae in a tissue image," similar to how a pathologist would examine a tissue sample — but with a highly detailed and powerful lens.
"The speed of iStar makes it possible to reconstruct this huge amount of spatial data within a short period of time," Dr. Li said in a press release. With this increased speed, researchers hope to further their understanding of tissue microenvironments in thousands more samples.