A new artificial intelligence-powered tool called MISO (Multi-modal Spatial Omics) can detect cell-level characteristics of cancer by looking at data from extremely small pieces of tissue—some as small as 400 square micrometers, equivalent to the width of five human hairs.  Constructed by researchers at the Perelman School of Medicine at the University of Pennsylvania, the tool analyzes reams of data and can apply insights to even the smallest spots on medical imaging. It could guide doctors to the individual therapies that work best for a variety of cancers, according to a new paper detailing MISO that was published today in Nature Methods.

MISO was developed to work in “spatial multi-omics,” a field of study in which researchers attempt to gain insight on different conditions through considering the physical layout of tissue by looking at different “-omics” modalities, like transcriptomics (study of gene expression), proteomics (proteins), and metabolomics (metabolites and their processes), among others.

As the field of spatial omics advances, it has become possible to measure multiple -omics modalities from the same tissue slice, providing complementary information and offering a more comprehensive, insightful view,” said Mingyao Li, PhD, the study’s senior author and a professor of Biostatistics and Digital Pathology. “MISO addresses a huge data challenge by enabling simultaneous analysis of all spatial -omics modalities, as well as microscopic anatomy images when available. It is the only method that is able to handle datasets like these with hundreds of thousands of cells per sample.

When using spatial transcriptomics to look at an image, a single pixel in a single image contains 20,000 to 30,000 data points to be analyzed through the lens of -omics, and that number can double and triple if multiple -omics are being considered. MRI and CT scans have just one data point (shades of gray) per pixel to interpret. Without some type of artificial intelligence tool to assist them, doctors and researchers examining medical images would almost never be able to pick up on some of the insights that MISO can.

Source: https://www.pennmedicine.org/news/news-releases/2025/january/ai-analyzes-30k-data-points-per-pixel-in-cancer-search