20
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

  • Upload
    garan

  • View
    45

  • Download
    0

Embed Size (px)

DESCRIPTION

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. Outline of Program. Technical considerations - PowerPoint PPT Presentation

Citation preview

Page 1: MNTP Summer Workshop  DTI module

Jordan Hamm (BA, BSc) University of Georgia, Athens, Georgia

Alexandra Reichenbach (MSc, Dipl-Ing)Max Planck Institute for Biological Cybernetics, Tuebingen, Germany

Page 2: MNTP Summer Workshop  DTI module

Technical considerations Mean ADC values, FA, and tract volume as

measurements

Application Rationale of the project Approaches

▪ Automatized / manual▪ Tract / ROI based

Results Conclusions

Page 3: MNTP Summer Workshop  DTI module

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

Page 4: MNTP Summer Workshop  DTI module

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

Page 5: MNTP Summer Workshop  DTI module

6 dir, b1200 50 dir, b1200 50 dir, b2400

Raw

MotionCorrected

Qualitative analyses

-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.

Page 6: MNTP Summer Workshop  DTI module

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

Page 7: MNTP Summer Workshop  DTI module

Initially, b-value didn’t appear to affect tractability…. But….

Assessed number of voxels involved in each reconstructed tract from each scan.

Page 8: MNTP Summer Workshop  DTI module

Motion correction (12 parameter) with vector table rotationreveals benefit of higher b-values (Leemans and Jones, 2009)

Page 9: MNTP Summer Workshop  DTI module

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

Page 10: MNTP Summer Workshop  DTI module

Manual selection of 3x3 voxel ROICompared between b-values, ang. res., and raw/motion corrected data

-Mean diffusivity (verified with known values) -FA estimate

Page 11: MNTP Summer Workshop  DTI module

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

Page 12: MNTP Summer Workshop  DTI module

-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”

Why does FA in a voxel cluster decrease with more resolution, but tract volume increase?

Page 13: MNTP Summer Workshop  DTI module

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)

Page 14: MNTP Summer Workshop  DTI module

Avidan & Behrmann (2009)

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

Page 15: MNTP Summer Workshop  DTI module

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 Automatic fiber 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!)?

Page 16: MNTP Summer Workshop  DTI module

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

precuneus / posterior cingulate cortex

anterior paracingulate cortex

ROIs: 18mm diameter

Page 17: MNTP Summer Workshop  DTI module

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

(*)*

Page 18: MNTP Summer Workshop  DTI module

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

Page 19: MNTP Summer Workshop  DTI module

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

Page 20: MNTP Summer Workshop  DTI module

Seong-Gi Kim & Bill EddyKwan-Jin JungMarlene Behrmann John MigliozziTomika CohenRebecca ClarkNIH