QuantuMRI from Fermilab and NYU Langone Meets NIH Challenge

Quantitative Magnetic Resonance Imaging qMRI

A multidisciplinary scientific team led by Fermilab's Superconducting Quantum Materials and Systems (SQMS) Center and NYU Langone Health was named a finalist in the first NIH Quantum Computing Challenge, advancing diagnostics. After finishing in the top ten in the competition's first round, QuantuMRI got $10,000 and the chance to advance.

This work integrates clinical medicine, quantum information science, and high-energy physics. Quantum computing could revolutionize quantitative magnetic resonance imaging (qMRI) by giving doctors unprecedented accuracy and speed in diagnosing complex diseases.

Beyond Gross Structures: qMRI Promise

MRI provides crisp, non-invasive images of soft-tissue structures and is a standard diagnostic tool. Conventional MRI collects signals from atomic magnetic moments, such as hydrogen atoms in the body responding to radiofrequency pulses and strong external magnetic fields. Reconstructing these reactions into detailed representations allows clinicians to analyze gross anatomical aspects.

QuantuMRI, on the other hand, strives to go beyond conventional imaging with quantitative MRI (qMRI). Instead of only imaging tissue structure, qMRI measures and describes subtle biophysical characteristics like the following:

Relaxation time

Rates of diffusion

Transfer magnetization

These assessments can detect compositional changes, microstructural changes, and early illness indications that conventional imaging misses. Such insights are crucial for early detection, illness tracking, and personalized therapy of cancer, neurological, and cardiovascular diseases.

Computer bottleneck

Although promising, qMRI is very complicated. Modeling complicated human tissue signal exchanges requires a lot of processing power. Traditional classical computing methods struggle to construct high-resolution, exact simulations. QMRI is hard to apply in clinical settings because standard systems lack the processing power for real-time, high-precision diagnosis.

This is quantum computing's revolutionary advantage. Superposition and entanglement allow quantum processors to simulate processes that classical computers cannot or would take too long. The QuantuMRI method models tissue responses under MRI settings more accurately and effectively than any traditional option, enabling scalable, reproducible qMRI solutions.

A multidisciplinary powerhouse

QuantuMRI's success relies on multidisciplinary collaboration. The SQMS Center, a DOE national quantum research hub led by Fermilab, specializes on superconducting quantum materials and qubit technology. NYU Langone Health's Center for Biomedical Imaging offers advanced research and clinical expertise.

QuantuMRI's key players come from numerous institutions, including:

NYU Grossman School of Medicine radiology professor Riccardo Lattanzi.

NYU Langone Health's Jose Cruz Serralles.

Fermilab's Oluwadara Ogunkoya and Doga Kurkcuoglu.

Norm Tubman, NASA Ames Research Center.

Riccardo Lattanzi said this partnership “highlights the potential for quantum technology to transform medical imaging and accelerate the clinical translation of qMRI, helping doctors make better decisions and moving us closer to precise, personalized medicine”.

NIH Challenge and 2027 Roadmap

NCATS organizes the NIH Quantum Computing Challenge to foster biomedical-quantum computing innovation. Teams can tackle crucial topics like medication discovery and improved diagnostics.

After winning the first round, the Quantitative Magnetic Resonance Imaging qMRI team progressed to the second. This level requires technical benchmarking, extensive development, and validation in early clinical settings for finalists. At the end of 2027, winners will be picked based on performance, innovation, and clinical adoption.

Big Picture: Fermilab Quantum Innovation

QuantuMRI was created as part of Fermilab's SQMS Center and quantum research ecosystem. The center uses Fermilab's superconducting and particle accelerator technology to develop quantum systems.

The latest SQMS advancements are:

Improved Coherence Times: Researchers have developed new qubit fabrication methods that address material decoherence, making quantum processors more reliable.

“Quantum Garages”: Large cleanrooms and dilution coolers for computing, sensing, and metrology research.

Frontier Physics: SQMS uses quantum systems to study dark matter and medicine.

According to DOE Office of High Energy Physics program manager Zachary Goff-Eldredge, this infrastructure encourages “bold, cross-disciplinary thinking” that will shape medical innovations.

The Future of Patient Care

The QuantuMRI research shows a period where quantum-enhanced imaging is a widespread therapeutic tool, despite challenges like scaling quantum systems and decreasing quantum processing “noise”. Patients may receive more personalized care and faster response.