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Neuroimage. 2016 Jan 15;125:767-779. doi: 10.1016/j.neuroimage.2015.11.005. Epub 2015 Nov 6.

Automated retinofugal visual pathway reconstruction with multi-shell HARDI and FOD-based analysis.

Author information

1
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA; Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
2
Department of Radiology, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
3
Neuroscience Graduate Program, University of Southern California, Los Angeles, CA 90089, USA; Department of Psychology, University of Southern California, Los Angeles, CA 90089, USA.
4
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA.
5
Laboratory of Neuro Imaging, USC Stevens Neuroimaging and Informatics Institute, Keck School of Medicine, University of Southern California, Los Angeles, CA 90032, USA. Electronic address: yshi@loni.usc.edu.

Abstract

Diffusion MRI tractography provides a non-invasive modality to examine the human retinofugal projection, which consists of the optic nerves, optic chiasm, optic tracts, the lateral geniculate nuclei (LGN) and the optic radiations. However, the pathway has several anatomic features that make it particularly challenging to study with tractography, including its location near blood vessels and bone-air interface at the base of the cerebrum, crossing fibers at the chiasm, somewhat-tortuous course around the temporal horn via Meyer's Loop, and multiple closely neighboring fiber bundles. To date, these unique complexities of the visual pathway have impeded the development of a robust and automated reconstruction method using tractography. To overcome these challenges, we develop a novel, fully automated system to reconstruct the retinofugal visual pathway from high-resolution diffusion imaging data. Using multi-shell, high angular resolution diffusion imaging (HARDI) data, we reconstruct precise fiber orientation distributions (FODs) with high order spherical harmonics (SPHARM) to resolve fiber crossings, which allows the tractography algorithm to successfully navigate the complicated anatomy surrounding the retinofugal pathway. We also develop automated algorithms for the identification of ROIs used for fiber bundle reconstruction. In particular, we develop a novel approach to extract the LGN region of interest (ROI) based on intrinsic shape analysis of a fiber bundle computed from a seed region at the optic chiasm to a target at the primary visual cortex. By combining automatically identified ROIs and FOD-based tractography, we obtain a fully automated system to compute the main components of the retinofugal pathway, including the optic tract and the optic radiation. We apply our method to the multi-shell HARDI data of 215 subjects from the Human Connectome Project (HCP). Through comparisons with post-mortem dissection measurements, we demonstrate the retinotopic organization of the optic radiation including a successful reconstruction of Meyer's loop. Then, using the reconstructed optic radiation bundle from the HCP cohort, we construct a probabilistic atlas and demonstrate its consistency with a post-mortem atlas. Finally, we generate a shape-based representation of the optic radiation for morphometry analysis.

KEYWORDS:

FOD; HARDI; Multi-shell; Retinofugal pathway; Tractography; Vision

PMID:
26551261
PMCID:
PMC4691391
DOI:
10.1016/j.neuroimage.2015.11.005
[Indexed for MEDLINE]
Free PMC Article

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