Gabriel Girard

Towards quantitative connectivity analysis: reducing tractography biases

Diffusion MRI tractography is often used to estimate structural connections between brain areas and there is a fast-growing interest in quantifying these connections based on their position, shape, size and length. However, a portion of the connections reconstructed with tractography is biased by their position, shape, size and length. Thus, connections reconstructed are not equally distributed in all white matter bundles. Quantitative measures of connectivity based on the streamline distribution in the brain such as streamline count (density), average length and spatial extent (volume) are biased by erroneous streamlines produced by tractography algorithms. In this paper, solutions are proposed to reduce biases in the streamline distribution. First, we propose to optimize tractography parameters in terms of connectivity. Then, we propose to relax the tractography stopping criterion with a novel probabilistic stopping criterion and a particle filtering method, both based on tissue partial volume estimation maps calculated from a T1-weighted image. We show that optimizing tractography parameters, stopping and seeding strategies can reduce the biases in position, shape, size and length of the streamline distribution. These tractography biases are quantitatively reported using in-vivo and synthetic data. This is a critical step towards producing tractography results for quantitative structural connectivity analysis.

Tractometer: Towards validation of tractography pipelines

We have developed the Tractometer: an online evaluation and validation system for tractography processing pipelines. One can now evaluate the results of more than 57,000 fiber tracking outputs using different acquisition settings (b-value, averaging), different local estimation techniques (tensor, q-ball, spherical deconvolution) and different tracking parameters (masking, seeding, maximum curvature, step size). At this stage, the system is solely based on a revised FiberCup analysis, but we hope that the community will get involved and provide us with new phantoms, new algorithms, third party libraries and new geometrical metrics, to name a few. We believe that the new connectivity analysis and tractography characteristics proposed can highlight limits of the algorithms and contribute in solving open questions in fiber tracking: from raw data to connectivity analysis. Overall, we show that (i) averaging improves quality of tractography, (ii) sharp angular ODF profiles helps tractography, (iii) seeding and multi-seeding has a large impact on tractography outputs and must be used with care, and (iv) deterministic tractography produces less invalid tracts which leads to better connectivity results than probabilistic tractography.

The challenge of mapping the human connectome based on diffusion tractography

Tractography based on non-invasive diffusion imaging is central to the study of human brain connectivity. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain data set with ground truth tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. Here, we report the encouraging finding that most state-of-the-art algorithms produce tractograms containing 90% of the ground truth bundles (to at least some extent). However, the same tractograms contain many more invalid than valid bundles, and half of these invalid bundles occur systematically across research groups. Taken together, our results demonstrate and confirm fundamental ambiguities inherent in tract reconstruction based on orientation information alone, which need to be considered when interpreting tractography and connectivity results. Our approach provides a novel framework for estimating reliability of tractography and encourages innovation to address its current limitations.Though tractography is widely used, it has not been systematically validated. Here, authors report results from 20 groups showing that many tractography algorithms produce both valid and invalid bundles.

Tractography-based connectomes are dominated by false-positive connections

Fiber tractography based on non-invasive diffusion imaging is at the heart of connectivity studies of the human brain. To date, the approach has not been systematically validated in ground truth studies. Based on a simulated human brain dataset with ground truth white matter tracts, we organized an open international tractography challenge, which resulted in 96 distinct submissions from 20 research groups. While most state-of-the-art algorithms reconstructed 90% of ground truth bundles to at least some extent, on average they produced four times more invalid than valid bundles. About half of the invalid bundles occurred systematically in the majority of submissions. Our results demonstrate fundamental ambiguities inherent to tract reconstruction methods based on diffusion orientation information, with critical consequences for the approach of diffusion tractography in particular and human connectivity studies in general.

The Corticocortical Structural Connectivity of the Human Insula

Abstract The insula is a complex structure involved in a wide range of functions. Tracing studies on nonhuman primates reveal a wide array of cortical connections in the frontal (orbitofrontal and prefrontal cortices, cingulate areas and supplementary motor area), parietal (primary and secondary somatosensory cortices) and temporal (temporal pole, auditory, prorhinal and entorhinal cortices) lobes. However, recent human tractography studies have not observed connections between the insula and the cingulate cortices, although these structures are thought to be functionally intimately connected. In this work, we try to unravel the structural connectivity between these regions and other known functionally connected structures, benefiting from a higher number of subjects and the latest state‐of‐the‐art high angular resolution diffusion imaging (HARDI) tractography algorithms with anatomical priors. By performing an HARDI tractography analysis on 46 young normal adults, our study reveals a wide array of connections between the insula and the frontal, temporal, parietal and occipital lobes as well as limbic regions, with a rostro‐caudal organization in line with tracing studies in macaques. Notably, we reveal for the first time in humans a clear structural connectivity between the insula and the cingulate, parahippocampal, supramarginal and angular gyri as well as the precuneus and occipital regions.

Tractography in the study of the human brain: a neurosurgical perspective.

BACKGROUND The brain functions as an integrated multi-networked organ. Complex neurocognitive functions are not attributed to a single brain area but depend on the dynamic interactions of distributed brain areas operating in large-scale networks. This is especially important in the field of neurosurgery where intervention within a spatially localized area may indirectly lead to unwanted effects on distant areas. As part of a preliminary integrated work on functional connectivity, we present our initial work on diffusion tensor imaging tractography to produce in vivo white matter tracts dissection. METHODS Diffusion weighted data and high-resolution T1- weighted images were acquired from a healthy right-handed volunteer (25 years old) on a whole-body 3 T scanner. Two approaches were used to dissect the tractography results: 1) a standard region of interest technique and 2) the use of Brodmann’s area as seeding points, which represents an innovation in terms of seeds initiation. RESULTS Results are presented as tri-dimensional tractography images. The uncinate fasciculus, the inferior longitudinal fasciculus, the inferior fronto-occipital fasiculus, the corticospinal tract, the corpus callosum, the cingulum, and the optic radiations where studied by conventional seeding approach, while Broca’s and Wernicke’s areas, the primary motor as well as the primary visual cortices were used as seeding areas in the second approach. CONCLUSIONS We report state-of-the-art tractography results of some of the major white matter bundles in a normal subject using DTI. Moreover, we used Brodmann’s area as seeding areas for fiber tracts to study the connectivity of known major functional cortical areas.

Tractometer: online evaluation system for tractography

We have developed a tractometer: an online evaluation system for tractography processing pipelines. One can now evaluate the end effects on fiber tracts of different acquisition parameters (b-value, number of directions, denoising or not, averaging or not), different local estimation techniques (tensor, q-ball, spherical deconvolution, spherical wavelets) and to different tractography parameters (masking, seeding, stopping criteria). At this stage, the system is solely based on a revised FiberCup analysis, but we hope that the community gets involved and provides us with new phantoms, new algorithms, third party libraries and new geometrical metrics, to name a few. We believe that the new connectivity analysis and tractography characteristics proposed can highlight limits of the algorithms and contribute in elucidating the open questions in fiber tracking: from raw data to connectivity analysis.

Revisiting the human uncinate fasciculus, its subcomponents and asymmetries with stem-based tractography and microdissection validation

Despite its significant functional and clinical interest, the anatomy of the uncinate fasciculus (UF) has received little attention. It is known as a ‘hook-shaped’ fascicle connecting the frontal and anterior temporal lobes and is believed to consist of multiple subcomponents. However, the knowledge of its precise connectional anatomy in humans is lacking, and its subcomponent divisions are unclear. In the present study, we evaluate the anatomy of the UF and provide its detailed normative description in 30 healthy subjects with advanced particle-filtering tractography with anatomical priors and robustness to crossing fibers with constrained spherical deconvolution. We extracted the UF by defining its stem encompassing all streamlines that converge into a compact bundle, which consisted not only of the classic hook-shaped fibers, but also of straight horizontally oriented. We applied an automatic-clustering method to subdivide the UF bundle and revealed five subcomponents in each hemisphere with distinct connectivity profiles, including different asymmetries. A layer-by-layer microdissection of the ventral part of the external and extreme capsules using Klingler’s preparation also demonstrated five types of uncinate fibers that, according to their pattern, depth, and cortical terminations, were consistent with the diffusion-based UF subcomponents. The present results shed new light on the UF cortical terminations and its multicomponent internal organization with extended cortical connections within the frontal and temporal cortices. The different lateralization patterns we report within the UF subcomponents reconcile the conflicting asymmetry findings of the literature. Such results clarifying the UF structural anatomy lay the groundwork for more targeted investigations of its functional role, especially in semantic language processing.

AxTract: Microstructure-Driven Tractography Based on the Ensemble Average Propagator.

We propose a novel method to simultaneously trace brain white matter (WM) fascicles and estimate WM microstructure characteristics. Recent advancements in diffusion-weighted imaging (DWI) allow multi-shell acquisitions with b-values of up to 10,000 s/mm2 in human subjects, enabling the measurement of the ensemble average propagator (EAP) at distances as short as 10 μm. Coupled with continuous models of the full 3D DWI signal and the EAP such as Mean Apparent Propagator (MAP) MRI, these acquisition schemes provide unparalleled means to probe the WM tissue in vivo. Presently, there are two complementary limitations in tractography and microstructure measurement techniques. Tractography techniques are based on models of the DWI signal geometry without taking specific hypotheses of the WM structure. This hinders the tracing of fascicles through certain WM areas with complex organization such as branching, crossing, merging, and bottlenecks that are indistinguishable using the orientation-only part of the DWI signal. Microstructure measuring techniques, such as AxCaliber, require the direction of the axons within the probed tissue before the acquisition as well as the tissue to be highly organized. Our contributions are twofold. First, we extend the theoretical DWI models proposed by Callaghan et al. to characterize the distribution of axonal calibers within the probed tissue taking advantage of the MAP-MRI model. Second, we develop a simultaneous tractography and axonal caliber distribution algorithm based on the hypothesis that axonal caliber distribution varies smoothly along a WM fascicle. To validate our model we test it on insilico phantoms and on the HCP dataset.

Improving Fiber Alignment in HARDI by Combining Contextual PDE Flow with Constrained Spherical Deconvolution.

We propose two strategies to improve the quality of tractography results computed from diffusion weighted magnetic resonance imaging (DW-MRI) data. Both methods are based on the same PDE framework, defined in the coupled space of positions and orientations, associated with a stochastic process describing the enhancement of elongated structures while preserving crossing structures. In the first method we use the enhancement PDE for contextual regularization of a fiber orientation distribution (FOD) that is obtained on individual voxels from high angular resolution diffusion imaging (HARDI) data via constrained spherical deconvolution (CSD). Thereby we improve the FOD as input for subsequent tractography. Secondly, we introduce the fiber to bundle coherence (FBC), a measure for quantification of fiber alignment. The FBC is computed from a tractography result using the same PDE framework and provides a criterion for removing the spurious fibers. We validate the proposed combination of CSD and enhancement on phantom data and on human data, acquired with different scanning protocols. On the phantom data we find that PDE enhancements improve both local metrics and global metrics of tractography results, compared to CSD without enhancements. On the human data we show that the enhancements allow for a better reconstruction of crossing fiber bundles and they reduce the variability of the tractography output with respect to the acquisition parameters. Finally, we show that both the enhancement of the FODs and the use of the FBC measure on the tractography improve the stability with respect to different stochastic realizations of probabilistic tractography. This is shown in a clinical application: the reconstruction of the optic radiation for epilepsy surgery planning.