We propose to update and expand upon three magnetic resonance spectroscopy (MRS) software tools that have been used extensively by the MRS research community for over a decade. By merging them into an integrated, open source, open development research platform, we will address a number of their individual limitations. The current software tools provide resources for spectral simulation, RF pulse design and spectral data analysis (GAVA/GAMMA, MatPulse and VeSPA programs, respectively). The proposed research platform will be called MrSPA (Magnetic Resonance Simulation, Pulse design and Analysis). Clinical MRS research design encompasses: 1) the research question, 2) pulse sequence re-design for specific data acquisition, and 3) robust spectral processing and data analysis. Amalgamation of the three programs into an integrated development platform will facilitate all three steps. Implementation using an open development model and current """"""""best programming practices"""""""" will lower the initial learning curve for users and developers, and will encourage rapid new development.
The aims of the first part of this proposal will focus on the unification and integration of the initial programs into one package. This process will address a number of limitations of the current software including: non-standard data access, closed source multiple language software that complicates algorithm extension and comparison, lack of integration between programs for sharing prior information, and incomplete or missing documentation and educational content.
The aims of the second half of this proposal will expand the development platform functionality both globally, via distributed computing options, plug-and-play extensibility, and networked data sharing;and also in each module with specific tools and algorithms. Software will be made available online for free. We will provide and support a simple transition pathway for the user communities of the current programs. We will partner with the NIPY consortium (NeuroImaging in Python) to provide industry standard open development tools and to facilitate dissemination of both easy to install packages for users and for source code repository access for developers.
This proposal will update and expand upon three existing magnetic resonance spectroscopy (MRS) software tools by merging them into a single integrated research platform. MRS is a powerful non-invasive tool for quantifying metabolite changes both in vivo and in vitro without the use of ionizing radiation. The importance of MRS as a clinical investigation tool is its potential to detect disease specific changes that may be observed where only non-specific MR imaging (MRI) findings are manifested or metabolic changes that may occur in the absence of structural abnormalities seen using MRI alone. It has found applications clinically in normal aging, traumatic brain injury, multiple sclerosis, Alzheimer's disease, epilepsy and brain tumor evaluation, to name a few, and an even wider spread of applications in animal and in vitro experiments. Clinical MRS research has experienced a tremendous growth in the last decade, owing to the rapid development of the necessary technology to support higher magnetic field MR scanners, and the great progress made in various MR data acquisition schemes. Merging these three MRS tools into an integrated platform will facilitate and encourage the use of comprehensive MRS research designs that incorporate all steps of data acquisition and analysis to investigate specific research questions.
| Davitz, Matthew S; Wu, William E; Soher, Brian J et al. (2017) Quantifying global-brain metabolite level changes with whole-head proton MR spectroscopy at 3T. Magn Reson Imaging 35:15-19 |
| Chawla, S; Ge, Y; Lu, H et al. (2015) Whole-Brain N-Acetylaspartate Concentration Is Preserved during Mild Hypercapnia Challenge. AJNR Am J Neuroradiol 36:2055-61 |
| Soher, Brian J; Wu, William E; Tal, Assaf et al. (2014) Automated whole-brain N-acetylaspartate proton MRS quantification. NMR Biomed 27:1275-84 |
| Kornak, John; Young, Karl; Soher, Brian J et al. (2010) Bayesian k -space-time reconstruction of MR spectroscopic imaging for enhanced resolution. IEEE Trans Med Imaging 29:1333-50 |
