According to a Jan 2. press release from Penn Medicine, a new artificial intelligence (AI) tool can interpret medical images that potentially could allow clinicians to dedicate more time to critical aspects of their job.
The press release states that “The tool, called iStar (Inferring Super-Resolution Tissue Architecture), was developed by researchers at the Perelman School of Medicine at the University of Pennsylvania, who believe they can help clinicians diagnose and better treat cancers that might otherwise go undetected. The imaging technique provides both highly detailed views of individual cells and a broader look of the full spectrum of how people’s genes operate, which would allow doctors and researchers to see cancer cells that might otherwise have been virtually invisible. This tool can be used to determine whether safe margins were achieved through cancer surgeries and automatically provide annotation for microscopic images, paving the way for molecular disease diagnosis at that level.”
Daiwei “David” Zhang, PhD, a research associate, and Mingyao Li, PhD, a professor of Biostatistics and Digital Pathology, published a paper on the method in Nature Biotechnology.
The press release adds that “Li said that iStar has the ability to automatically detect critical anti-tumor immune formations called ‘tertiary lymphoid structures,’ whose presence correlates with a patient’s likely survival and favorable response to immunotherapy, which is often given for cancer and requires high precision in patient selection. This means, Li said, that iStar could be a powerful tool for determining which patients would benefit most from immunotherapy.”
The research was funded by the National Institutes of Health.
Penn Medicine has the full press release.
