Improving MRI technology through better radiofrequency coil design
Official title: A Novel Open-Source Optimization Framework for the Design and Simulation of Radiofrequency Coils for Magnetic Resonance Imaging
Funded at New York University School of Medicine · NIH-11021543 · Data updated 2026-11-12
This study is working on a new software tool to help make MRI machines better by improving the design of the coils that capture images, which could lead to clearer pictures and more accurate diagnoses for patients getting MRI scans.
Quick facts
| Grant type | R01 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | New York University School of Medicine NIH-funded |
| Lab location | 1 site (New York, United States) |
| Project start | January 3, 2025 |
| Project end | December 31, 2028 |
| Funding year | 2025 |
| Award (this year) | $595,870 |
| NIH project number | 1R01EB036483-01 |
| Project ID | NIH-11021543 on NIH RePORTER |
Who could benefit from this research
✓Could help
Patients who require MRI scans for diagnostic purposes, particularly those with complex conditions affecting the brain or nervous system, would benefit from this research.
✕Less likely to help
Patients who do not require MRI imaging or those with conditions that can be diagnosed through other imaging modalities may not receive direct benefits from this research.
What this research studies
This research focuses on developing an innovative open-source framework to optimize the design and simulation of radiofrequency (RF) coils used in magnetic resonance imaging (MRI). By utilizing advanced algorithms and modeling techniques, the project aims to enhance the performance of RF coils, which are crucial for obtaining high-quality MRI images. The approach involves creating a software toolkit that can automatically adjust the shape and arrangement of coil elements to achieve optimal imaging results based on specific anatomical models. This could lead to improved imaging capabilities and better diagnostic outcomes for patients undergoing MRI scans.
Why it matters
Potential benefit: If successful, this research could significantly enhance the quality of MRI scans, leading to more accurate diagnoses and better patient care.
How similar studies have gone: Previous research has shown that advancements in RF coil design can lead to significant improvements in MRI imaging quality, indicating that this approach has the potential for success.
Where this research is happening
-
New York University School of Medicine
New York, United States Active
Researchers
- Principal investigator: Lattanzi, Riccardo — New York University School of Medicine
- Study coordinator: Lattanzi, Riccardo
Related research
Other NIH-funded projects on the same topics.
-
Systemic imaging probes for detecting tissue oxygen levels in cancer and other diseases
A researcher aims to develop a new europium-based MRI contrast agent that can be given systemically to visualize oxygen levels (hypoxia) in cancer and other diseases.
-
Improving deep brain stimulation with MRI and AI
We use brain scans and artificial intelligence to speed up and personalize deep brain stimulation settings for people getting DBS.
-
How teens’ social media use affects mood and behavior with brain clues
Teenagers’ use of social media and online interactions may shape their mood and behavior, and this project looks at how brain activity relates to those experiences.
-
Portable MRI to identify brain injury after cardiac arrest
A portable, low-field MRI test is being studied to quickly identify brain injury in adults after cardiac arrest to guide treatment in the emergency room or ICU.
-
Understanding heart fibrosis with AI, MRI, and genomics
A doctor-scientist is using artificial intelligence, advanced heart MRI, and genetic data to learn how scar tissue forms in the aging heart and how to prevent it.
-
Ultrashort Echo Time MRI of the Knee to Detect Early Osteoarthritis
A new MRI technique using ultrashort echo time sequences to image knee tissues and detect early signs of knee osteoarthritis in patients.
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.