Jean-Christophe Houde

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.

Structural network underlying visuospatial imagery in humans

INTRODUCTION Several neuroimaging studies have shown that visuospatial imagery is associated with a multitude of activation nodes spanning occipital, parietal, temporal and frontal brain areas. However, the anatomical connectivity profile linking these areas is not well understood. Specifically, it is unknown whether cortical areas activated during visuospatial imagery are directly connected to one another, or whether few act as hubs which facilitate indirect connections between distant sites. Addressing this is important since mental imagery tasks are commonly used in clinical settings to assess complex cognitive functions such as spatial orientation. METHODS We recorded functional magnetic resonance imaging (fMRI) data while participants (N = 18) performed a visuospatial imagery task. In the same subjects, we acquired diffusion MRI (dMRI) and used state-of-the-art tractography robust to fiber crossings to reconstruct the white matter tracts linking the fMRI activation sites. For each pair of these sites, we then computed the fraction of subjects showing a connection between them. RESULTS Robust fMRI activation was observed in cortical areas spanning the dorsal (extrastriate, parietal and prefrontal areas) and ventral (temporal and lingual areas) pathways, as well as moderate deactivation in striate visual cortex. In over 80% of subjects, striate cortex showed anatomical connectivity with extrastriate (medial occipital) and lingual (posterior cingulate cortex-PCC) sites with the latter showing divergent connections to ventral (parahippocampus) and dorsal (BA7) activation areas. CONCLUSION Our results demonstrate that posterior cingulate cortex is not only activated by visuospatial imagery, but also serves as an anatomical hub linking activity in occipital, parietal and temporal areas. This finding adds to the growing body of evidence pointing to PCC as a connector hub which may facilitate integration across widespread cortical areas.

Strengths and weaknesses of state of the art fiber tractography pipelines – A comprehensive in-vivo and phantom evaluation study using Tractometer

Many different tractography approaches and corresponding isolated evaluation attempts have been presented over the last years, but a comparative and quantitative evaluation of tractography algorithms still remains a challenge, particularly in-vivo. The recently presented evaluation framework Tractometer is the first attempt to approach this challenge in a quantitative, comparative, persistent and open-access way. Tractometer is currently based on the evaluation of several global connectivity and tract-overlap metrics on hardware phantom data. The work presented in this paper focuses on extending Tractometer with a metric that enables the assessment of the local consistency of tractograms with the underlying image data that is not only applicable to phantom dataset but allows the quantitative and purely data-driven evaluation of in-vivo tractography. We furthermore present an extensive reference-based evaluation study of 25,000 tractograms obtained on phantom and in-vivo datasets using the presented local metric as well as all the methods already established in Tractometer. The experiments showed that the presented local metric successfully reflects the behavior of in-vivo tractography under different conditions and that it is consistent with the results of previous studies. Additionally our experiments enabled a multitude of conclusions with implications for fiber tractography in general, including recommendations regarding optimal choice of a local modeling technique, tractography algorithm, and parameterization, confirming and complementing the results of earlier studies.

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.

Using fMRI non-local means denoising to uncover activation in sub-cortical structures at 1.5 T for guided HARDI tractography

In recent years, there has been ever-increasing interest in combining functional magnetic resonance imaging (fMRI) and diffusion magnetic resonance imaging (dMRI) for better understanding the link between cortical activity and connectivity, respectively. However, it is challenging to detect and validate fMRI activity in key sub-cortical areas such as the thalamus, given that they are prone to susceptibility artifacts due to the partial volume effects (PVE) of surrounding tissues (GM/WM interface). This is especially true on relatively low-field clinical MR systems (e.g., 1.5 T). We propose to overcome this limitation by using a spatial denoising technique used in structural MRI and more recently in diffusion MRI called non-local means (NLM) denoising, which uses a patch-based approach to suppress the noise locally. To test this, we measured fMRI in 20 healthy subjects performing three block-based tasks : eyes-open closed (EOC) and left/right finger tapping (FTL, FTR). Overall, we found that NLM yielded more thalamic activity compared to traditional denoising methods. In order to validate our pipeline, we also investigated known structural connectivity going through the thalamus using HARDI tractography: the optic radiations, related to the EOC task, and the cortico-spinal tract (CST) for FTL and FTR. To do so, we reconstructed the tracts using functionally based thalamic and cortical ROIs to initiates seeds of tractography in a two-level coarse-to-fine fashion. We applied this method at the single subject level, which allowed us to see the structural connections underlying fMRI thalamic activity. In summary, we propose a new fMRI processing pipeline which uses a recent spatial denoising technique (NLM) to successfully detect sub-cortical activity which was validated using an advanced dMRI seeding strategy in single subjects at 1.5 T.

A new compression format for fiber tracking datasets

A single diffusion MRI streamline fiber tracking dataset may contain hundreds of thousands, and often millions of streamlines and can take up to several gigabytes of memory. This amount of data is not only heavy to compute, but also difficult to visualize and hard to store on disk (especially when dealing with a collection of brains). These problems call for a fiber-specific compression format that simplifies its manipulation. As of today, no fiber compression format has yet been adopted and the need for it is now becoming an issue for future connectomics research. In this work, we propose a new compression format, .zfib, for streamline tractography datasets reconstructed from diffusion magnetic resonance imaging (dMRI). Tracts contain a large amount of redundant information and are relatively smooth. Hence, they are highly compressible. The proposed method is a processing pipeline containing a linearization, a quantization and an encoding step. Our pipeline is tested and validated under a wide range of DTI and HARDI tractography configurations (step size, streamline number, deterministic and probabilistic tracking) and compression options. Similar to JPEG, the user has one parameter to select: a worst-case maximum tolerance error in millimeter (mm). Overall, we find a compression factor of more than 96% for a maximum error of 0.1mm without any perceptual change or change of diffusion statistics (mean fractional anisotropy and mean diffusivity) along bundles. This opens new opportunities for connectomics and tractometry applications.