SBIR/STTR Research Award

SBIR Phase I: Incorporating High Dielectric Constant Materials into clinical imaging: A Novel Approach for Accelerating 1.5T MRI

Award identifier 3cf58a033a1161440deedcfd0c82780389e4cf27de99c30832127fb530542d43Awarding agency National Science Foundation

Award amount

$224,966

Program and phase

SBIR · Phase I

Award year

2020

Explore This Research Award in CaptureIQ

Research the technology, evaluate the recipient and agency, identify related opportunities, and explore potential follow-on work with CaptureIQ.

Award details

Awarding agency
National Science Foundation
Branch
Not reported
Recipient company
HYQ RESEARCH SOLUTIONS, LLC
Proposal award date
2020-05-15
Contract end date
2021-01-31
UEI
NG9UJAMBCRE4
Solicitation number
Not reported
Topic code
BM

Research abstract

The broader impact/commercial potential of this Small Business Innovation Research (SBIR) Phase 1 project will target clinical Magnetic Resonance Imaging (MRI) scanners where there is limited MRI access to a larger patient population. Enhanced spatial resolution and reduced scan time are in urgent demand for investigating a comprehensive range of biological systems from single cells to humans. Long scan times reduce the efficiency of radiology department processes and increase the overall cost to clinics and patients. In the research community, high-resolution MRI is a powerful tool for understanding metabolic activity. This project will pioneer an entirely different solution to the fundamental problem of long scan times by introducing special materials into the clinical MRI scanners most commonly used to address the challenge of signal strength versus patient safety, which ultimately limits the throughput for research studies and clinical tests. The proposed materials developed under this SBIR program will have an immediate impact on animal and human health studies where neuroscientists are using MRI techniques to monitor brain activity and cognition. The proposed SBIR Phase 1 project will advance the development of a new approach to MRI, an indispensable clinical imaging modality for radiology and one of the most powerful research instruments for life science. However, it has an inherently low signal-to-noise ratio, limiting both imaging resolution and scan speed. Development efforts will focus on incorporation of high permittivity dielectric materials into MRI scanners to increase the signal-to-noise ratio by over 40%, thereby cutting the scan time by half. The dielectric materials would be placed near the patient to increase the MRI signal through stronger electromagnetic coupling. Materials with dielectric constant values between 4,000 and 6,000 will be synthesized and incorporated into clinical 1.5 Tesla MRI scanners. Oxide materials with the optimized dielectric properties will be synthesized and characterized before fabricating the final device. The project will pursue an integrated systems approach including electromagnetic simulation, ceramic processing and testing. The magnetic field strengths will be optimized by simulating a range of dielectric materials in the MRI scanner and ultimately tested in clinical scanners with a phantom. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Research funding history

2 SBIR/STTR records share this UEI (2020–2023). Reported award amounts total $1,223,070. Reported amounts are not federal obligations.

Phases: Phase II, Phase I

Agencies: National Science Foundation

Agency intelligence

National Science Foundation

Back to SBIR/STTR Research Awards

Don't take our word for it. Ask AI about RFPCapture.

See what leading AI assistants have to say about RFPCapture and CaptureIQ.

Gemini opens without a prefilled question. The question is copied to your clipboard when the button works. You can also copy it here:

What is RFPCapture.com and its CaptureIQ platform from Smart Logic AI? How does it help federal contractors discover opportunities, evaluate bid/no-bid decisions, research government contracts, and prepare proposals? How does it compare with other federal capture platforms? Use independent sources where available.