Using measurements of water diffusion, dMRI can give unique insights into the microstructure and cellular orientation of tissues. There is a growing awareness in the neurosurgery community that diffusion models must move beyond the current clinical standard of the diffusion tensor for better anatomical accuracy of fiber tracts. But several informatics challenges prevent advances in dMRI from easily reaching clinical cancer researchers: 1) Advances in dMRI are not supported by commercial clinical software, 2) dMRI research software is not designed for clinical cancer settings, and 3) a lack of common file format standards prevents interoperability between dMRI software packages. The goal of this proposal is to address these challenges by providing improvements to the technical informatics capability for dMRI brain cancer research. We propose to achieve this goal by providing state-of- the-art dMRI functionality in an NIH-supported community software package 3D Slicer that is widely used in cancer research, and by developing a standalone standards-compliant library for interoperability of dMRI tractography data. Specific aims of the project are to (1) extend diffusion MRI infrastructure and interoperability, (2) create cancer research workflows with feedback from clinical collaborators, (3) document, test, and release software to the community.
National Cancer Institute