We use cookies to understand how you use our site and to improve your experience. This includes personalizing content and advertising. To learn more, click here. By continuing to use our site, you accept our use of cookies. Cookie Policy.

Features Partner Sites Information LinkXpress hp
Sign In
Advertise with Us

Download Mobile App




AI Tool Analyzes 30K Data Points Per Medical Imaging Pixel in Cancer Search

By LabMedica International staff writers
Posted on 16 Jan 2025

A new artificial intelligence (AI)-powered tool can detect cell-level characteristics of cancer by analyzing data from very small tissue samples, some as tiny as 400 square micrometers, equivalent to the width of five human hairs. More...

The tool, called MISO (Multi-modal Spatial Omics), processes vast amounts of data and applies insights to even the smallest regions on medical images. It has the potential to guide doctors toward the most effective therapies for various cancers, according to a recent paper about MISO published in Nature Methods.

MISO was developed by researchers at the Perelman School of Medicine at the University of Pennsylvania (Philadelphia, PA, USA) to work in the field of "spatial multi-omics." This area of research aims to gain insights into different conditions by considering the physical arrangement of tissue while examining various "-omics" modalities, such as transcriptomics (gene expression), proteomics (proteins), and metabolomics (metabolites and their processes), among others. In spatial transcriptomics, for example, a single pixel in an image contains 20,000 to 30,000 data points that need to be analyzed across multiple -omics layers, and this number can increase significantly if multiple omic layers are considered. By comparison, MRI and CT scans have only one data point (shades of gray) per pixel to interpret. Without AI tools like MISO, doctors and researchers would find it nearly impossible to uncover the valuable insights that the system can detect.

Using MISO, the researchers uncovered new information about several types of cancer, including bladder, gastric, and colorectal cancers, by analyzing data and images from donated patient tissue. In bladder cancer, MISO identified a specific group of cells responsible for forming tertiary lymphoid structures, which are associated with better responses to immunotherapy. In gastric cancer, MISO was able to differentiate cancer cells from the surrounding mucosa. In colorectal cancer, the system identified various sub-classes of cancer cells, shedding light on the distinct malignant cells within a single tumor. MISO was also used to analyze non-cancerous brain tissue structures.

These breakthroughs can guide more effective therapies, improve survival rates, and provide insights that are very challenging, if not impossible, to obtain without an advanced AI tool like MISO. Moving forward, the team aims to expand their knowledge of spatial -omics and pathology imaging to enhance MISO’s capabilities, including the ability to analyze multiple tissue samples simultaneously, which would greatly increase its output. While some data, such as epigenetic marks (chemicals that regulate DNA and are influenced by the environment), have not yet been widely measured, MISO’s AI system allows it to "learn" from the information it processes, enabling it to recognize new data as it becomes more available.

“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.”

Related Links:
Perelman School of Medicine


Gold Member
Quantitative POC Immunoassay Analyzer
EASY READER+
3-Part Differential Hematology Analyzer
Swelab Alfa Plus Sampler
New
Gel Cards
DG Gel Cards
New
ESR Analyzer
TEST1 2.0
Read the full article by registering today, it's FREE! It's Free!
Register now for FREE to LabMedica.com and get access to news and events that shape the world of Clinical Laboratory Medicine.
  • Free digital version edition of LabMedica International sent by email on regular basis
  • Free print version of LabMedica International magazine (available only outside USA and Canada).
  • Free and unlimited access to back issues of LabMedica International in digital format
  • Free LabMedica International Newsletter sent every week containing the latest news
  • Free breaking news sent via email
  • Free access to Events Calendar
  • Free access to LinkXpress new product services
  • REGISTRATION IS FREE AND EASY!
Click here to Register








Channels

Molecular Diagnostics

view channel
Image: The ONC IN-CYT platform leverages cross indication biomarker cyto-signatures (Photo courtesy of OraLiva)

AI-Powered Cytology Tool Detects Early Signs of Oral Cancer

Each year, 54,000 Americans are diagnosed with oral cancer, yet only 28% of cases are identified at an early stage, when the five-year survival rate exceeds 85%. Most diagnoses occur in later stages, when... Read more

Hematology

view channel
Image: The microfluidic device for passive separation of platelet-rich plasma from whole blood (Photo courtesy of University of the Basque Country)

Portable and Disposable Device Obtains Platelet-Rich Plasma Without Complex Equipment

Platelet-rich plasma (PRP) plays a crucial role in regenerative medicine due to its ability to accelerate healing and repair tissue. However, obtaining PRP traditionally requires expensive centrifugation... Read more

Immunology

view channel
Image: PD-1 protein blockade is the standard treatment for advanced melanoma among the different types of immunotherapy (Photo courtesy of 123RF)

Precision Tool Predicts Immunotherapy Treatment Failure in Melanoma Patients

Melanoma, though accounting for only about 4% of skin tumors, is the deadliest form of skin cancer due to its high potential to metastasize. While immunotherapy, especially PD-1 protein blockade, has revolutionized... Read more
Copyright © 2000-2025 Globetech Media. All rights reserved.