Johns Hopkins DTI Projects Jonathan Farrell Bennett Landman, Hao Huang, Thomas Ng Man Cheuk, Susumu Mori

2 Progress Report Slides

To Do List from 2005 High SNR DTI Calibration 1.5T –Several studies wrap up & publish –Original and coregistered datapost –Useful software post DTI Database of 61 Healthy 1.5T –Original datapost –Coregistered and processed datapost Image Distortion Correction for DTI –Studywrap up & publish Tractography Reproducibility –Studywrap up & publish

Progress Report in 2006 High SNR DTI Calibration 1.5T –Several studies2 papers submitted –Original and coregistered dataPosted –Useful software2 posted + 1 soon DTI Database of 61 Healthy Controls 1.5T –Original data Posted –Coregistered and processed datasoon Image Distortion Correction for DTI –Studyunder revision (round 2) Tractography Reproducibility –Studyunder revision (round 2)

Summary of Each Project Goal Results Endpoints

DTI Calibration Study: SNR QUESTION: How does SNR affect DTI contrasts in vivo ? TAKE HOME POINT:Provide methods to calibrate SNR across sites ENDPOINT:Paper submitted September 2006

DTI Calibration Study: DW Scheme QUESTION:  Which diffusion weighting scheme should you use and why? TAKE HOME POINT:  Use a scheme with many directions ( ~ 30) to get uniform precision and accuracy at all fiber orientations. BUT…Effect size is small (less than intra and inter scan variability) ENDPOINT:Paper submitted October 2006

Multi-Site DTI Calibration Study GOAL:  Measure accuracy and precision of DTI contrasts at several imaging sites and scanners. DATA COLLECTION SITES:  Johns Hopkins  Duke  MGH  University of Texas South Western DETIALS:  Will make DTI-contrast vs SNR curves  Hopefully, the sites show similar behavior

Software: CATNAP GOAL:  To simplify and accelerate DTI & anatomical data processing HOW IT WORKS:  Coregistration with FSL FLIRT  Computes DTI gradient table  Computes diffusion tensor and DTI contrasts DETIALS:  Runs in MATLAB  Philips data only (so far)

Software: DTI_gradient_table_creator GOAL:  Figure out the gradient table for Philips DTI data HOW IT WORKS:  Takes scanner / imaging options & parameters into account Rules can be tricky ! DETIALS:  MATLAB function  JAVA applet (online)

Software: PARtoNRRD_Philips GOAL:  Create NRRD headers files for Philips DTI data .nhdr files contain all relevant DTI parameters  Resolution, FOV, Slices  Gradient directions, b-value, coordinate space  Compatible with Slicer HOW IT WORKS:  Uses.par file (Philips text file)  Uses DTI_gradient_table_creator_Philips_RelX WHAT YOU NEED : .nhdr file and.rec (data file)  Will be posted soon

GOAL:  Distribute DTI data for 61 healthy controls DTI Database of Healthy Controls ISSUES:  Data management, defacing and de-identification ENDPOINT:  Original data (posted), coregistered data (TBD), meta-data (TBD)

Tractography Reproducibility Cingulum Corticospinal tract Anterior thalamic radiation Superior long. fasciculus Inferior long. fasciculus Inferior frontocc. fasciculus Uncinate fasciculus Intra-rater Inter-rater Almost perfect Substantial Moderate Fair GOAL:  Test reproducibility of tractography  Performed multi-site inter-rater tests for 11 major WM tracts. RESULTS:  Substantial reproducibility was observed for the protocol developed under this project ENDPOINT:  Paper submitted and under revision

Image Distortion Correction for DTI a)Non distorted T1w image, b) DTI with distortion c)Landmark-based LDDMM correction d)Intensity –based SPM e) segmentation-based SPM. f) The LDDMM method undistorts the image smoothly g) Guantifies the distortion by Jacobian. Although the segmentation- based SPM could correct the distortion (e), the transformation contains severe discontinuity (h), which may cause DTI calculation errors. Paper is in preparation. Working on implementing other techniques (Song, others)