Diffusion Tensor Imaging in Patients with focal dystonia

Description: Results of Tract-based tractography comparing patients with upper limb dystonia, cervical dystonia and healthy controls. Data was processed using FSL.6.01.10, following the steps: We extracted the first b0 volume from the DTI acquisition, corresponding to the anterior-posterior sequence. Using the acquisition with reversed gradient polarity, we applied the Topup tool to estimate susceptibility-induced field distortions and correct them. Through Brain Extraction tool (BET), a binary mask was used for skull extraction and applied to all images in the sequence using a fractional intensity threshold of 0.45. Next, to correct distortions caused by eddy currents—generated by the rapid switching of gradient directions—we used the Eddy Current Correction tool, part of the FMRIB Diffusion Toolbox (FSL). This process aligned the entire DTI sequence to the first b0 reference image using rigid-body registration to correct for head motion. Head motion (translation and rotation) was calculated using the susceptibility motion estimation tool incorporated into the Eddy Current Correction function. After this step, a visual inspection was performed to assess the image quality obtained after preprocessing the corrected DWI image. Diffusion tensors were estimated for each voxel (DTIFIT) using weighted linear least squares (WLLS) to improve accuracy. Finally, FA, AD, MD, and RD maps were generated and visually inspected for artifacts (e.g., signal dropout, geometric distortion, noise, and gross head motion) to assess the need for data exclusion. All FA maps were subsequently refined to create a mean FA skeleton. Skeletonized images for each subject were generated by projecting maximum FA values near the center of the white matter tracts onto the mean FA skeleton. The mean FA skeleton was then thresholded (FA ≤ 0.2) to focus on major fiber bundles. The exact transformations derived from the nonlinear registration of FA maps to standard space (MNI152) were applied to the AD, MD, and RD maps for combined processing of all image volumes.