2010 Winter Project Week DTI Fiber Tract Statistics
Visual explanation of the data processing happening through the tool (Image 1)
Visual explanation of the data processing happening through the tool (Image 2 ...continuation of Image 1)
Kernel regression along the fiber tract, also showing the scatter plot for DTI data.
Sub plots showing distribution of FA values in various cross-sections along the fiber tract length.
Key Investigators
- Utah: Anuja Sharma, Guido Gerig
Objective
The aim is to understand probabilistic models that can account for the behavior of water diffusion in white matter tracts. The long term goal is to use this to understand the changes in white matter structure with age, gender or a specific disease.
Approach, Plan
Various tract-oriented scalar diffusion measures are treated as a continuous function of fiber arc-length. To analyze the trend along the fiber tract, a command line tool performs kernel regression on this data. The idea is to try out different noise models and maximum likelihood estimates within kernel windows, such that they best represent the data and are robust to noise and Partial Volume effect.
Casey Goodlett's functional data analysis pipeline is then applied to this data. Here, multivariate hypothesis test is used to test for differences between populations.
Our plan for the project week is to try out the complete pipeline for a few datasets and see if we get statistically significant results. We also plan to work on the possibility of integrating this module into the Slicer environment.
Progress
The first version of the command line tool is ready. It provides the flexibility to choose the scalar diffusion measure to be tested; a choice between Gaussian and Beta noise models and Mean, median or mode as MLE. It also incorporates several visualization options which help in analyzing the best noise models and the best representative statistics to explain the distribution of DTI data along the fiber tract.
This week we figured out all interoperability issues which need to fixed to enable the tool's integration into the Slicer. We discussed with other groups working on DTI and discussed common data structures and file formats for easy interfacing between tools. As a result, we will be moving our files to the VTK format in the near future.
Another discussion with Maddah pointed out ways to minimize the need for manual intervention in our tool. Moreover, we would be collaborating with the University of Iowa in providing tools to process datasets related to Huntington's disease. We might also migrate another medical imaging software Fiber Viewer to Qt4 to enable integration into the Slicer environment.
During this week we also tried running the pipeline on several datasets. We are in the process of analyzing the results now.
Progress - revised
The command line tool is ready for upload into the NITRC. The features available in the tool currently, its use and input / output formats and other relevant details are provided in the first draft of the documentation (PDF). The tool is still a work in progress. More features will be added to it, specially the option to plot and visualize the results.
References
- Casey B. Goodlett, P. Thomas Fletcher, John H. Gilmore, Guido Gerig. Group Analysis of DTI Fiber Tract Statistics with Application to Neurodevelopment. NeuroImage 45 (1) Supp. 1, 2009. p. S133-S142
