High-throughput, multiscale imaging of metabolism with AI help
Official title: High-throughput, Multiscale Imaging Spatial Metabolomics
Funded at University of Illinois at Urbana-Champaign · NIH-11331540 · Data updated 2026-11-12
Aims to create faster, smarter imaging tools that map where metabolites are in tissues, using AI to guide data collection and analysis, with potential benefits for understanding diseases.
Quick facts
| Grant type | NIH-funded research |
|---|---|
| Study type | NIH-funded research |
| Funding institution | University of Illinois at Urbana-Champaign NIH-funded |
| Lab location | 1 site (Champaign, United States) |
| Project start | September 18, 2021 |
| Project end | August 31, 2031 |
| Funding year | 2026 |
| Award (this year) | $493,704 |
| NIH project number | 2R35GM142969-06 |
| Project ID | NIH-11331540 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients whose diseases involve tissue metabolism and metabolic heterogeneity may benefit from future imaging-based diagnostics and therapies.
✕Less likely to help
If imaging needs or disease context do not align with the imaging modalities developed, direct patient benefit may be limited.
What this research studies
This project seeks to combine magnetic resonance and mass spectrometry with artificial intelligence to map metabolic activity in tissues across multiple scales. A novel AI-powered sampling and signal reconstruction approach will speed up data collection while keeping important chemical details. It also introduces a framework called CRISP to achieve cell-level understanding of tissue metabolism without requiring extremely high-resolution imaging. The goal is to reveal how metabolic patterns relate to health and disease, enabling insights that could inform diagnosis and treatment. The work is conducted at the University of Illinois at Urbana-Champaign under a leadership team headed by Fan Lam.
Why it matters
Potential benefit: If successful, patients could benefit from faster, more precise metabolic imaging that informs diagnosis and personalized treatment planning.
How similar studies have gone: Prior spatial metabolomics efforts showed promise, and AI-assisted imaging is an emerging area with early demonstrations of faster data acquisition and improved interpretation.
Where this research is happening
-
University of Illinois at Urbana-Champaign
Champaign, United States Active
Researchers
- Principal investigator: Lam, Fan — University of Illinois at Urbana-Champaign
- Study coordinator: Lam, Fan
Related research
Other NIH-funded projects on the same topics.
-
Newborn screening: using gene and metabolite data to refine true vs false positives
A study using genetic and metabolomic data from newborn blood spots to better distinguish real metabolic disorders from false alarms.
-
IDEAL: How early-life immune development shapes vaccine responses and asthma risk
A child-focused project that looks at how the developing immune system in early life affects vaccine responses, respiratory infections, and asthma.
-
Integrative metabolomics to improve sarcoidosis diagnosis and prognosis
A research project from UCLA aims to find blood-based biomarkers that help diagnose sarcoidosis earlier and predict how it will progress, especially in African American women.
-
Metabolomics clues to how ultra-processed foods affect risk of type 2 diabetes
A scientist-led study will look at how eating different ultra-processed foods may change diabetes risk by using a controlled feeding trial and big population data, focusing on adults.
-
Longitudinal metabolomics in infants with food allergies
A study in infants aims to understand how gut metabolites relate to the development of food allergies, including IgE-mediated and non-IgE cases.
-
Biospecimen, Metabolomics, and Pathology Core for Endometrial Cancer Research
A national, multi-institutional resource collects and analyzes tissue, blood, and metabolites from endometrial cancer patients to support multiple research projects.
About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.