TractographyWorkshop Core1 ActionPlan

At the Workshop we agreed to complete the following:

1. Define a NA-MIC endorsed DWI pre- and post processing pipeline that uses NA-MIC toolkit software when available and other freely available software if unanimously agreed upon by the group (e.g. some FSL tools are in widespread use).
2. Curate and post in the NA-MIC Publication database one or more sets of DWI data to be used within NA-MIC for analytic tool development, testing and calibration.
3. Complete a rigorous analysis of the properties of the tractography approaches in use or under development within NA-MIC Core 1 teams on these data sets, including test-retest reliability.
4. Prepare and submit for publication a scholarly report of this work, with Sonia Pujol taking the lead under the mentorship of CF Westin, Ross, Guido and Randy. All participants in the work will share authorship.

Brief summary of the presentations, comparative analysis of tractography methods/approaches:

1. There were both common and disparate results across tractography approaches. In particular, the data sets were found to be outliers in several of the algorithms. We were all struck by the range of results of the different tractography algorithms even after controlling for most of the preprosessing steps. The presentations also highlighted the exact details of how different preprocessing steps and choice of ROIs affected the outcome of the different algorithms. This led to a unanimous agreement to chose only one pre-processing pipeline for the next phase of our work and greatly simplified the decision-making for the next phase.

Methods for NA-MIC DWI tractography analysis

1. General Taxonomy (based on ROI requirements)- use all those presented at this conference and FSL tool
2. Reproducibility of tractography approaches
3. Our same 5 ROIs + CC. Sonia and Randy to make first pass in 1 subject, validate with Marek's lab and then send around to be sure work with algorithms.

Need data sets, appropriate ROIs. Iterate beginning with n=1 for ROI generation.

Exploration of potential data sets (UNC n=1, 10 acquisitions with 6 directions; MIND n=10, 8 acquisitions, 2x at each of 3 sites with 6 directions and 2x at 1 site with 60 directions).

Sylvain volunteers to make nrrd headers for the 10 MIND subjects data from MGH test/retest with Jeremy, Vince, Randy.

Outcome metrics

1. User interface, hardware/software (processor speed, platform, RAM), operator time

Preprocessing stream:

1. DWI with NiFTY header + gradient directions
2. Field Map correction (NMN.Iowa.MGH) if we verify that this is helpful
3. Eddy Current Correction (affine registration) (BWH)
4. nrrd (BWH)
5. weighted least squares (FSL won't match on this step) tensor estimation using #TEEM library (BWH)
6. T1 white matter mask co-registered to Eddy current corrected DWI data (NA-MIC affine registration tool) (Freesurfer white matter + ? vs. EMSegmentation- Sonia/Sylvain)
7. ROIs in DWI/DTI space
8. Affine registration transformation to bring retest into test space (use this for mapping ROIs and outcome label maps only from test to retest for each subject)

Outcome metrics:

1. Space carved (Casey's DTIprocess tool that generates a volume label map measure from traceline). This will give volumes, overlap, mean and Std Dev of FA, trace, mode. Use these for test-retest metrics. Pass these label maps to Sonia she will generate these.
2. Casey's FiberCompare multiple traceline visualization tool
3. Staple method to find common agreement (specificity and sensitivity)
4. Further discussion of how best to parameterize tracts at January AHM

Next steps:

1. T-con November 16th 2 PM EST/ noon MST Agenda items include feedback on sample data set & ROIs
2. Next face to face gathering will be at the AHM, Randy to schedule time on the agenda t continue this project
3. Proper implementation of DTI gradient orientation system in ITK, nrrd, TEEM, etc (Casey/Tom to file bug report, bring it up in an upcoming Engineering T-con, plan for work on it next Project week))