Nuclear Magnetic Resonance (NMR) offers established advantages for biomarker detection, but has not become clinically standard largely due to a lack of sensitivity in the detection of non-1H nuclei at clinical field strengths. Array coils offer a natural and practical approach to increase sensitivity in MR experiments, and are standard in nearly all imaging applications. As such, clinical scanners are typically equipped with multiple receiver channels for 1H (imaging), but only a single broadband receiver channel capable of receiving second-nuclei information. Collection of non-1H data is therefore limited to serial studies per nucleus (long experiment times and changing of coils between studies) and cannot achieve increased sensitivity through the use of array coils. This project proposes a practical way to address clinical hardware limitations and validates the utility of the approach with application to Duchenne Muscular Dystrophy (DMD). DMD is a genetic disorder that affects ~1:5,000 newborn boys and causes degeneration of skeletal and cardiac muscle, resulting in a loss of ambulation in the teenage years, cardiac/respiratory issues in the late 20?s, and death in the third decade. The value of animal models in the study of DMD (and all diseases) is well established, but is of particular importance to DMD at this time due to the exploding development of experimental therapies ? molecular, cellular, and pharmacologic. One of the most established colonies of golden retrievers with muscular dystrophy (GRMD) in the world resides at Texas A&M University ? an animal model proven to be superior for relevant assessment of therapies. This project will show the viability of achieving the benefits of clinical NMR-based biomarker detection with a straightforward hardware addition and simultaneously allow for data collection in a manner that is painless, non-invasive, and minimizes anesthesia time for dogs in DMD studies at the Texas Institute for Preclinical Sciences (TIPS).
Aim 1 - Design and construct multi-tuned RF coil arrays for detection of 1H, 31P, and 23Na. Completion of this aim will result in RF coils designed for SNR-enhanced in vivo NMR-based biomarker detection with minimal changes to the current GRMD scanning protocol.
Aim 2 - Build an add-on multi-channel frequency translation system to provide multi-channel multinuclear spectroscopy on the Siemens 3T scanner. Completion of this aim will result in a modular system, straightforwardly interfaced to the existing 32-channel 1H receiver that will allow acquisition of up to 16 channels of 1H data and up to eight channel data from two additional nuclei ? in this case, 31P and 23Na.
Aim 3 - Obtain 1H-31P-23Na data from already-characterized existing ex vivo preserved muscle samples. Completion of this aim will result in the initial testing of the frequency translation system and will verify the sensitivity and specificity of NMR-based detection.
Aim 4 - Obtain in vivo 1H-31P-23Na data from GRMD disease models as an ?add on? procedure to current scans using the hardware interface to modify the 3T scanner for multi-nuclear multi-channel acquisition. Completion of this aim will confirm the utility of in vivo NMR-based biomarker detection as a practical option in clinical scanning.

Public Health Relevance

Nuclear Magnetic Resonance Imaging & Spectroscopy (MRI/S) play a unique role in the effort to identify biomarkers to understand, prevent, diagnose, and treat disease, with the potential for spectroscopy, in particular, to provide an in vivo ?chemical signature?. This work aims to engineer hardware solutions to incorporate meaningful and sensitive spectroscopy studies into clinical MRI scans with minimal additional scan time and system modifications and demonstrate the clear benefit in characterizing Duchenne Muscular Dystrophy.

Agency
National Institute of Health (NIH)
Institute
National Institute of Biomedical Imaging and Bioengineering (NIBIB)
Type
Research Project (R01)
Project #
1R01EB028533-01A1
Application #
9974125
Study Section
Enabling Bioanalytical and Imaging Technologies Study Section (EBIT)
Program Officer
Wang, Shumin
Project Start
2020-04-01
Project End
2023-12-31
Budget Start
2020-04-01
Budget End
2020-12-31
Support Year
1
Fiscal Year
2020
Total Cost
Indirect Cost
Name
Texas Engineering Experiment Station
Department
Biomedical Engineering
Type
Biomed Engr/Col Engr/Engr Sta
DUNS #
847205572
City
College Station
State
TX
Country
United States
Zip Code
77843