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

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.

Probabilistic Tractography for Topographically Organized Connectomes

“…Following the method in [16], we automatically generate V1 ROI and its retinotopic map that assigns each vertex in V1 cortex two coordinates: angle and eccentricity. ROI for LGN was generated using the method proposed in [14]. Inferior bundle of the optic radiation has an unconventional trajectory which first courses anteriorly before it runs posteriorly towards the visual cortex forming the elusive Meyer’s loop.…”

“…This correspondence between the topography of the retina and axonal projections provides a great opportunity for localized mapping of retina disease to visual pathway integrity. Another distinct aspect of this fiber system is the Meyer’s loop that bends sharply toward the anterior aspect before moving toward the visual cortex[14]. Given these anatomical knowledge about the topography and geometric organization of the optic radiation, we believe it is an ideal testbed for tractography algorithms.…”

Complementary research models and methods to study axonal regeneration in the vertebrate retinofugal system

“…Yet, thanks to technical advances in diffusion imaging over the last decade (which are beyond the scope of this review), brain studies on a larger scale have been made feasible. DTI has even been used in a recent study of the retinofugal pathway in human subjects (Kammen et al 2016). Nevertheless, despite these advances of in vivo magnetic resonance imaging (MRI), the acquired resolution is lower than what can be obtained using conventional fluorescent microscopy, precluding the visualization of a single axon.…”

Active delineation of Meyer's loop using oriented priors through MAGNEtic tractography (MAGNET)

“…A large number of studies have attempted to reconstruct the OR using diffusion tensor imaging (DTI) (Yamamoto et al, 2005; Sherbondy et al, 2008b; Yogarajah et al, 2009; Hofer et al, 2010; Clatworthy et al, 2010; Winston et al, 2011; Wu et al, 2012; Tax et al, 2014a; Benjamin et al, 2014; Lilja et al, 2014; Dayan et al, 2015) and high order models based on high angular resolution diffusion imaging (HARDI) acquisitions (Nowell et al, 2015; Martinez-Heras et al, 2015; Kammen et al, 2015; Bernier et al, 2014). The clinical motivation behind most of these studies was to obtain an accurate model of the OR for the preoperative planning in anterior temporal lobe resection surgery.…”

“…To achieve a dense coverage of Meyer’s loop, the majority of aforementioned techniques employ brute force probabilistic tractography of all possible streamlines, then rely on multiple regions of interest (ROIs) to eliminate a considerable amount of false positive streamlines. Clustering techniques (O’Donnell and Westin, 2007; Garyfallidis et al, 2012) are also employed to extract the final bundle and increase accuracy (Kammen et al, 2015). These pipelines can take several hours to compute structural connectivity and may be suboptimal for neurosurgical planning where time is often a key-factor.…”