The goal of this TR&D project is to develop novel, open-source, DICOM compliant, cross-platform software tools for reconstruction, quantification and visualization of hyperpolarized MR data as driven by the needs of the Collaborative Projects. There are currently no other packages available for analysis of the results obtained using the fast imaging and spectroscopy pulse sequences associated with this new in vivo technology. This address a pressing need because the multi-dimensional data produced following injection of pre-polarized imaging probes provide dramatic improvements in sensitivity over conventional methods and unique information about metabolic processes within living systems.
Specific Aim 1 will start with the SIVIC software framework being developed at UCSF for evaluation of MR metabolic imaging data and will expand the underlying libraries to include modules for interpreting vendor specific file formats and acquisition parameters, processing raw data and displaying the resulting temporal and spatial arrays. The enhanced package will be made available to the Service Projects and the general research community through a web portal that provides comprehensive documentation, test datasets, bug reporting and user feedback.
Specific Aim 2 will focus on the specialized reconstruction algorithms needed for analysis of the data. Acquisition strategies considered for imaging and spectroscopy datasets include parallel sampling, echo planar, spiral or other variable k-space sampling and compressed sensing. Frequency specific imaging, view-sharing and keyhole imaging may also be utilized for monitoring dynamic processes.
Specific Aim 3 will address the quantitative analysis of hyperpolarized MR data using non-linear fitting techniques to estimate spectral peak intensifies and by modeling dynamic processes to determine rate constants and metabolite radios. The general strategy will be to develop modular processing pipelines that can be put together in a flexible fashion in order to represent a wide range of different metabolic pathways. There will be regular training sessions for users associated with the Collaborative and Service Projects, as well as ongoing dialogue about the ease of use and requirements for new capabilities. Contributions from researchers in other institutions will be encouraged by free, open sharing of the source code and methodology.
In this project we will focus on developing a comprehensive, open source software framework that includes reconstruction and post-processing algorithms to quantify and visualize multi-dimensional hyperpolarized MR imaging and spectroscopy data. These computational tools are critical for moving the technology forward and investigating the broad range of applications proposed by our collaborative and service projects.
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