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Proceedings Paper

Effects of EPI distortion correction pipelines on the connectome in Parkinson's Disease
Author(s): Justin Galvis; Adam F. Mezher; Anjanibhargavi Ragothaman; Julio E. Villalon-Reina; P. Thomas Fletcher; Paul M. Thompson; Gautam Prasad
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Paper Abstract

Echo-planar imaging (EPI) is commonly used for diffusion-weighted imaging (DWI) but is susceptible to nonlinear geometric distortions arising from inhomogeneities in the static magnetic field. These inhomogeneities can be measured and corrected using a fieldmap image acquired during the scanning process. In studies where the fieldmap image is not collected, these distortions can be corrected, to some extent, by nonlinearly registering the diffusion image to a corresponding anatomical image, either a T1- or T2-weighted image. Here we compared two EPI distortion correction pipelines, both based on nonlinear registration, which were optimized for the particular weighting of the structural image registration target. The first pipeline used a 3D nonlinear registration to a T1-weighted target, while the second pipeline used a 1D nonlinear registration to a T2-weighted target. We assessed each pipeline in its ability to characterize high-level measures of brain connectivity in Parkinson’s disease (PD) in 189 individuals (58 healthy controls, 131 people with PD) from the Parkinson’s Progression Markers Initiative (PPMI) dataset. We computed a structural connectome (connectivity map) for each participant using regions of interest from a cortical parcellation combined with DWI-based whole-brain tractography. We evaluated test-retest reliability of the connectome for each EPI distortion correction pipeline using a second diffusion scan acquired directly after the participants’ first. Finally, we used support vector machine (SVM) classification to assess how accurately each pipeline classified PD versus healthy controls using each participants’ structural connectome.

Paper Details

Date Published: 21 March 2016
PDF: 7 pages
Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97843D (21 March 2016); doi: 10.1117/12.2217377
Show Author Affiliations
Justin Galvis, The Univ. of Southern California (United States)
Adam F. Mezher, The Univ. of Southern California (United States)
Anjanibhargavi Ragothaman, The Univ. of Southern California (United States)
Julio E. Villalon-Reina, The Univ. of Southern California (United States)
P. Thomas Fletcher, The Univ. of Utah (United States)
Paul M. Thompson, The Univ. of Southern California (United States)
Gautam Prasad, The Univ. of Southern California (United States)


Published in SPIE Proceedings Vol. 9784:
Medical Imaging 2016: Image Processing
Martin A. Styner; Elsa D. Angelini, Editor(s)

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