MNTP Summer Workshop DTI module

1. Jordan Hamm (BA, BSc) University of Georgia, Athens, Georgia Alexandra Reichenbach (MSc, Dipl-Ing) Max Planck Institute for Biological Cybernetics, Tuebingen, Germany MNTP Summer Workshop DTI module

2. Outline of Program • Technical considerations • Mean ADC values, FA, and tract volume as measurements • Application • Rationale of the project • Approaches • Automatized / manual • Tract / ROI based • Results • Conclusions

3. Technical Considerations What is b-value? -higher b-values may probe different diffusion -more sensitive to differences in restricted (Assaf, 2004) Do more angles provide any benefit beyond more SNR? -i.e. are more gradient directions just redundant? -6 dir(8 times) or 50 directions (1 time)? Is motion correction effective? - Leemans vector table rotation

4. Technical Considerations What effect does b-value, angular resolution, and motion correction have on common diffusion metrics? - Scanned 2 subjects - Compared parameters in -tract reconstructions -5x5mm ROIs for maximum sensitivity

5. Qualitative analyses Tract-based analysis: Anterior portion of corpus callosum Raw 6 dir, b1200 50 dir, b1200 50 dir, b2400 Motion Corrected -Tracts produced with FACT algorithm (BF approach) using tensors in 6 direction data and using non-negativity constrained spherical de-convolution in 50 direction data.

6. Evaluation of b-value, ang. res., and motion correction in tract reconstructions First compared average FA of a tract to overall tract volume As volume of a tract increases, overall average FA of that tract decreases - so tract integrity is not necessarily revealed in a tract based analysis. Instead, tract volume and/or number of “tracts” are best used for tract based analyses

7. Effect of b-value on tractography Assessed number of voxels involved in each reconstructed tract from each scan. Initially, b-value didn’t appear to affect tractability…. But….

8. Effect of b-value on tractography Motion correction (12 parameter) with vector table rotation reveals benefit of higher b-values (Leemans and Jones, 2009)

9. Benefit of motion correction Motion correction appears to improve tracking, but differentially for different b-values. Why? - longer scans more movement? - b2400 scan 10% longer (2 min) -higher b-values are more sensitive -scan artifacts

10. ROI based analyses Manual selection of 3x3 voxel ROI Compared between b-values, ang. res., and raw/motion corrected data -Mean diffusivity (verified with known values) -FA estimate

11. Diffusion coefficient estimate Mean diffusivity variable between b=1200 and b=2400 before motion correction • -Overall variance of ADC values reduced after motion correction • -also closer to prescribed 7.0 X 10^-4 (Johansen-Berg and Behrmans, 2009) • B=2400 with motion correction is best • ROI close to CSF, to which lower b-values are more sensitive. • Again, differential effects of motion correction seen

12. Analysis of ROI FA values Why does FA in a voxel cluster decrease with more resolution, but tract volume increase? -Higher b-values yield more consistent measure of fractional anisotropy across subjects -Some anisotropy captured by low b-values could be non-axonal which does not contribute to long range tractography -lower b-values have more “hindered” and less “restricted”

13. DTI application: Project on Congenital Prosopagnosia (CP) Learning aims • Learn different DTI analysis software and their strengths & weaknesses • Explore a real scientific question with different DTI approaches • Get to know pitfalls and possible difficulties on real data Haxby et al. (2000)

14. CP project: Rationale • Familiar vs. unknown faces elicit specificBOLD activation in healthy controls but notin CP patients in • left precuneus/posterior cingulate cortex • anterior paracingulate cortex • Outside the ‘core system’ for face processing • HypothesisStructural changes in white matter tractsbetween these regions might underlie thefunctional differences • Target tract: Cingulum Avidan & Behrmann (2009)

15. CP project: Approaches • Measurements (for ROIs or tracts) • Fractional anisotrophy (FA) • Radial diffusivity (RD) • Transverse diffusitivity (TD) • Number of detected fibers (# fibers) • Number of voxels within detected tract (# voxels) • Approaches • Automaticfiber seeding based on fMRI group coordinates • Extraction of cingulum fibers based on anatomy (manual seeding) • ROI analysis of sup. cingulum with automatic seeding based on standard space coordinates • (probabilistic tracking from fMRI group coordinates, FSL) • Data: previously acquired from 17 controls & 6 patients • TR/TE = 4900/82ms; 6 directions; b = 850 s/mm2; 1.6*1.6*3mm voxel size • Is this angular resolution sufficient for these regions (fiber crossing!)?

16. CP project: Results of automatic seeding based on fMRI data • Transformation of fMRI MNI coordinates in native space (FSL FLIRT) • Construction of spheric ROIs around these coordinates (MATLAB) • Extraction of tracts traversing both ROIs (ExploreDTI) • Only about 1/3 of the subjects had tractable fibers • Increasing the radius of the ROI did not solve the problem background: FA values ROIs: 18mm diameter anterior paracingulate cortex precuneus / posterior cingulate cortex

17. CP project: Results of cingulum tracts based on anatomy • Analysis with DTI Studio, manual seeding by 2 independent investigators • Comparison of left & right cingulum in healthy controls and DTI patients • Results (whole tracts as ROI) • Inter-rater reliability: > .8 • No group differences in corpus callosum (CC) • control tract • FA & TD larger in left than in right cingulum • consistent with literature • Significant differences in # fibers total   in line with fMRI data: no activation of left precuneus/ PCC in patients * (*)

18. CP project: ROI cingulum analysis • Analysis with Explore DTI, MNI coord of ROI transformed in native space • Results (only ROI voxels included) • Larger FA value left than right in controls can be explained by a smaller RD  fibers more directed • TD left in CP patients smaller than in controls fibers more directed in controls  in line with fMRI data: activation of left precuneus/PCC in controls but not in patients

19. CP project: Discussion • Automatic seeding based on fMRI data fails • Possibly due to large inter-individual differences – BUT no individual fMRI available • Possibly due to insufficient tractability with 6 direction data – higher angular resolution data is acquired at the moment  ExploreDTI can model multiple fibers in a voxel (CSD) • Analysis data-driven, no operator bias • Manual cingulum tracking • High inter-rater reliability due to ‘standardized’ method of ROI definition DTI Studio: easy-to-use & user-friendly GUI, ideal for exploration and manual interventionBUT supports only tensor model • Results in controls are consistent with literature • Automatic seeded ROI analysis • No manual intervention, no operator bias  Besides ILF and IFOF the left cingulum is another tract involved in face processing that seems to be compromised in CP patients

20. Achnowledgements • Seong-Gi Kim & Bill Eddy • Kwan-Jin Jung • Marlene Behrmann • John Migliozzi • Tomika Cohen • Rebecca Clark • NIH