scholarly journals Tractography-based connectomes are dominated by false-positive connections

2016 ◽  
Author(s):  
Klaus H. Maier-Hein ◽  
Peter Neher ◽  
Jean-Christophe Houde ◽  
Marc-Alexandre Côté ◽  
Eleftherios Garyfallidis ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
State Of The Art ◽  
Diffusion Imaging ◽  
Ground Truth ◽  
Fiber Tractography ◽  
Research Groups ◽  
Non Invasive ◽  
Reconstruction Methods ◽  
Orientation Information

AbstractFiber 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.

scholarly journals Anatomy and white matter connections of the orbitofrontal gyrus

2018 ◽  
Vol 128 (6) ◽  
pp. 1865-1872 ◽  
Author(s):  
Joshua D. Burks ◽  
Andrew K. Conner ◽  
Phillip A. Bonney ◽  
Chad A. Glenn ◽  
Cordell M. Baker ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
Internal Capsule ◽  
Ground Truth ◽  
Outcome Evaluation ◽  
Anterior Cingulate ◽  
Anatomical Dissection ◽  
Visual Spatial ◽  
Human Connectome Project

OBJECTIVEThe orbitofrontal cortex (OFC) is understood to have a role in outcome evaluation and risk assessment and is commonly involved with infiltrative tumors. A detailed understanding of the exact location and nature of associated white matter tracts could significantly improve postoperative morbidity related to declining capacity. Through diffusion tensor imaging–based fiber tracking validated by gross anatomical dissection as ground truth, the authors have characterized these connections based on relationships to other well-known structures.METHODSDiffusion imaging from the Human Connectome Project for 10 healthy adult controls was used for tractography analysis. The OFC was evaluated as a whole based on connectivity with other regions. All OFC tracts were mapped in both hemispheres, and a lateralization index was calculated with resultant tract volumes. Ten postmortem dissections were then performed using a modified Klingler technique to demonstrate the location of major tracts.RESULTSThe authors identified 3 major connections of the OFC: a bundle to the thalamus and anterior cingulate gyrus, passing inferior to the caudate and medial to the vertical fibers of the thalamic projections; a bundle to the brainstem, traveling lateral to the caudate and medial to the internal capsule; and radiations to the parietal and occipital lobes traveling with the inferior fronto-occipital fasciculus.CONCLUSIONSThe OFC is an important center for processing visual, spatial, and emotional information. Subtle differences in executive functioning following surgery for frontal lobe tumors may be better understood in the context of the fiber-bundle anatomy highlighted by this study.

scholarly journals Prevalence of white matter pathways coming into a single diffusion MRI voxel orientation: the bottleneck issue in tractography

2021 ◽  
Author(s):  
Kurt Schilling ◽  
Chantal M.W. Tax ◽  
Francois M.W. Rheault ◽  
Bennett A Landman ◽  
Adam W Anderson ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Diffusion Mri ◽  
Brain Connectivity ◽  
False Negative ◽  
Fiber Tractography ◽  
Single Voxel ◽  
Ill Posed ◽  
Pass Through

Characterizing and understanding the limitations of diffusion MRI fiber tractography is a prerequisite for methodological advances and innovations which will allow these techniques to accurately map the connections of the human brain. The so-called "crossing fiber problem" has received tremendous attention and has continuously triggered the community to develop novel approaches for disentangling distinctly oriented fiber populations. Perhaps an even greater challenge occurs when multiple white matter bundles converge within a single voxel, or throughout a single brain region, and share the same parallel orientation, before diverging and continuing towards their final cortical or sub-cortical terminations. These so-called "bottleneck" regions contribute to the ill-posed nature of the tractography process, and lead to both false positive and false negative estimated connections. Yet, as opposed to the extent of crossing fibers, a thorough characterization of bottleneck regions has not been performed. The aim of this study is to quantify the prevalence of bottleneck regions. To do this, we use diffusion tractography to segment known white matter bundles of the brain, and assign each bundle to voxels they pass through and to specific orientations within those voxels (i.e. fixels). We demonstrate that bottlenecks occur in greater than 50-70% of fixels in the white matter of the human brain. We find that all projection, association, and commissural fibers contribute to, and are affected by, this phenomenon, and show that even regions traditionally considered "single fiber voxels" often contain multiple fiber populations. Together, this study shows that a majority of white matter presents bottlenecks for tractography which may lead to incorrect or erroneous estimates of brain connectivity or quantitative tractography (i.e., tractometry), and underscores the need for a paradigm shift in the process of tractography and bundle segmentation for studying the fiber pathways of the human brain.

scholarly journals Euclidean distance as a measure to distinguish ventral and dorsal white matter connectivity in the human brain

2016 ◽  
Author(s):  
Philipp Kellmeyer ◽  
Magnus-Sebastian Vry
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Cognitive Processing ◽  
Euclidean Distance ◽  
Large Scale ◽  
Diffusion Tensor ◽  
Large Body ◽  
Coordinate Space ◽  
Fiber Tractography

AbstractFiber tractography based on diffusion tensor imaging (DTI) has become an important research tool for investigating the anatomical connectivity between brain regions in vivo. Combining DTI with functional magnetic resonance imaging (fMRI) allows for the mapping of structural and functional architecture of large-scale networks for cognitive processing. This line of research has shown that ventral and dorsal fiber pathways subserve different aspects of bottom-up- and top-down processing in the human brain.Here, we investigate the feasibility and applicability of Euclidean distance as a simple geometric measure to differentiate ventral and dorsal long-range white matter fiber pathways tween parietal and inferior frontal cortical regions, employing a body of studies that used probabilistic tractography.We show that ventral pathways between parietal and inferior frontal cortex have on average a significantly longer Euclidean distance in 3D-coordinate space than dorsal pathways. We argue that Euclidean distance could provide a simple measure and potentially a boundary value to assess patterns of connectivity in fMRI studies. This would allow for a much broader assessment of general patterns of ventral and dorsal large-scale fiber connectivity for different cognitive operations in the large body of existing fMRI studies lacking additional DTI data.

scholarly journals Investigating The Functional Consequence Of White Matter Damage: An Automatic Pipeline To Create Longitudinal Disconnection Tractograms

2017 ◽  
Author(s):  
Kesshi Marin Jordan ◽  
Anisha Keshavan ◽  
Eduardo Caverzasi ◽  
Joseph Osorio ◽  
Nico Papinutto ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Large Scale ◽  
Diffusion Imaging ◽  
White Matter Injury ◽  
High Angular Resolution ◽  
Single Subject ◽  
White Matter Damage ◽  
Time Investment ◽  
Manual Intervention

Neurosurgical resection is one of the few opportunities researchers have to image the human brain both prior to and following focal damage. One of the challenges associated with studying brains undergoing surgical resection is that they often do not fit the brain templates most image-processing methodologies are based on, so manual intervention is required to reconcile the pathology and the most extreme cases must be excluded. Manual intervention requires significant time investment and introduces reproducibility concerns. We propose an automatic longitudinal pipeline based on High Angular Resolution Diffusion Imaging acquisitions to facilitate a Pathway Lesion Symptom Mapping analysis relating focal white matter injury to functional deficits. This two-part approach includes (i) automatic segmentation of focal white matter injury from anisotropic power differences, and (ii) modeling disconnection using tractography on the single-subject level, which specifically identifies the disconnections associated with focal white matter damage. The advantages of this approach stem from (1) objective and automatic lesion segmentation and tractogram generation, (2) objective and precise segmentation of affected tissue likely to be associated with damage to long-range white matter pathways (defined by anisotropic power), (3) good performance even in the cases of anatomical distortions by use of nonlinear tensor-based registration in the patient space, which aligns images using white matter contrast. Mapping a system as variable and complex as the human brain requires sample sizes much larger than the current technology can support. This pipeline can be used to execute large-scale, sufficiently powered analyses by meeting the need for an automatic approach to objectively quantify white matter disconnection.

scholarly journals Pandora: 4-D white matter bundle population-based atlases derived from diffusion MRI fiber tractography

2020 ◽  
Author(s):  
Colin B Hansen ◽  
Qi Yang ◽  
Ilwoo Lyu ◽  
Francois Rheault ◽  
Cailey Kerley ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Mri ◽  
State Of The Art ◽  
Population Based ◽  
Small Sample ◽  
Fiber Tractography ◽  
Statistical Inferences ◽  
Small Sample Sizes ◽  
The Brain ◽  
Brain Atlases

AbstractBrain atlases have proven to be valuable neuroscience tools for localizing regions of interest and performing statistical inferences on populations. Although many human brain atlases exist, most do not contain information about white matter structures, often neglecting them completely or labelling all white matter as a single homogenous substrate. While few white matter atlases do exist based on diffusion MRI fiber tractography, they are often limited to descriptions of white matter as spatially separate “regions” rather than as white matter “bundles” or fascicles, which are well-known to overlap throughout the brain. Additional limitations include small sample sizes, few white matter pathways, and the use of outdated diffusion models and techniques. Here, we present a new population-based collection of white matter atlases represented in both volumetric and surface coordinates in a standard space. These atlases are based on 2443 subjects, and include 216 white matter bundles derived from 6 different state-of-the-art tractography techniques. This atlas is freely available and will be a useful resource for parcellation and segmentation.

High-Definition Fiber Tractography of the Human Brain

Neurosurgery ◽  
2012 ◽  
Vol 71 (2) ◽  
pp. 430-453 ◽  
Author(s):  
Juan C. Fernandez-Miranda ◽  
Sudhir Pathak ◽  
Johnathan Engh ◽  
Kevin Jarbo ◽  
Timothy Verstynen ◽  
...  
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Structural Connectivity ◽  
Low Grade ◽  
Superior Cerebellar Peduncle ◽  
Fiber Tractography ◽  
Imaging Data ◽  
Thalamic Nuclei ◽  
High Definition ◽  
Diffusion Spectrum Imaging

Abstract BACKGROUND: High-definition fiber tracking (HDFT) is a novel combination of processing, reconstruction, and tractography methods that can track white matter fibers from cortex, through complex fiber crossings, to cortical and subcortical targets with subvoxel resolution. OBJECTIVE: To perform neuroanatomical validation of HDFT and to investigate its neurosurgical applications. METHODS: Six neurologically healthy adults and 36 patients with brain lesions were studied. Diffusion spectrum imaging data were reconstructed with a Generalized Q-Ball Imaging approach. Fiber dissection studies were performed in 20 human brains, and selected dissection results were compared with tractography. RESULTS: HDFT provides accurate replication of known neuroanatomical features such as the gyral and sulcal folding patterns, the characteristic shape of the claustrum, the segmentation of the thalamic nuclei, the decussation of the superior cerebellar peduncle, the multiple fiber crossing at the centrum semiovale, the complex angulation of the optic radiations, the terminal arborization of the arcuate tract, and the cortical segmentation of the dorsal Broca area. From a clinical perspective, we show that HDFT provides accurate structural connectivity studies in patients with intracerebral lesions, allowing qualitative and quantitative white matter damage assessment, aiding in understanding lesional patterns of white matter structural injury, and facilitating innovative neurosurgical applications. High-grade gliomas produce significant disruption of fibers, and low-grade gliomas cause fiber displacement. Cavernomas cause both displacement and disruption of fibers. CONCLUSION: Our HDFT approach provides an accurate reconstruction of white matter fiber tracts with unprecedented detail in both the normal and pathological human brain. Further studies to validate the clinical findings are needed.

Tractography of White Matter Fibers Using Diffusion MRI

2022 ◽  
pp. 98-112
Author(s):  
Strivathsav Ashwin Ramamoorthy
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Diffusion Mri ◽  
Neural Circuits ◽  
Water Molecules ◽  
Neural Connectivity ◽  
Non Invasive ◽  
Diffusion Weighted Images ◽  
Different Types ◽  
The Brain

To understand more about the human brain and how it works, it is vital to understand how the neural circuits connect different regions of the brain. The human brain is filled predominantly with water and the majority of the water molecules undergo diffusion which can be captured with the help of diffusion MRI. Diffusion weighted images enable us to reconstruct the neural circuits in a non-invasive manner, and this procedure is referred to as tractography. Tractography aids neurosurgeons to understand the neural connectivity of the patient. This chapter attempts to explain the procedure of tractography and different types of algorithms.

scholarly journals Diffusional Kurtosis Imaging in the Diffusion Imaging in Python Project

2021 ◽  
Vol 15 ◽  
Author(s):  
Rafael Neto Henriques ◽  
Marta M. Correia ◽  
Maurizio Marrale ◽  
Elizabeth Huber ◽  
John Kruper ◽  
...  
Keyword(s):  
White Matter ◽  
Brain Connectivity ◽  
Diffusion Imaging ◽  
Ground Truth ◽  
Biophysical Parameters ◽  
Tissue Microstructure ◽  
Diffusional Kurtosis Imaging ◽  
Water Fraction ◽  
Microstructural Alterations ◽  
Non Gaussian

Diffusion-weighted magnetic resonance imaging (dMRI) measurements and models provide information about brain connectivity and are sensitive to the physical properties of tissue microstructure. Diffusional Kurtosis Imaging (DKI) quantifies the degree of non-Gaussian diffusion in biological tissue from dMRI. These estimates are of interest because they were shown to be more sensitive to microstructural alterations in health and diseases than measures based on the total anisotropy of diffusion which are highly confounded by tissue dispersion and fiber crossings. In this work, we implemented DKI in the Diffusion in Python (DIPY) project—a large collaborative open-source project which aims to provide well-tested, well-documented and comprehensive implementation of different dMRI techniques. We demonstrate the functionality of our methods in numerical simulations with known ground truth parameters and in openly available datasets. A particular strength of our DKI implementations is that it pursues several extensions of the model that connect it explicitly with microstructural models and the reconstruction of 3D white matter fiber bundles (tractography). For instance, our implementations include DKI-based microstructural models that allow the estimation of biophysical parameters, such as axonal water fraction. Moreover, we illustrate how DKI provides more general characterization of non-Gaussian diffusion compatible with complex white matter fiber architectures and gray matter, and we include a novel mean kurtosis index that is invariant to the confounding effects due to tissue dispersion. In summary, DKI in DIPY provides a well-tested, well-documented and comprehensive reference implementation for DKI. It provides a platform for wider use of DKI in research on brain disorders and in cognitive neuroscience.

Diffusion Imaging Methods in Language Sciences

2019 ◽  
pp. 211-228
Author(s):  
Stephanie J. Forkel ◽  
Marco Catani
Keyword(s):  
White Matter ◽  
Human Brain ◽  
Animal Studies ◽  
Diffusion Imaging ◽  
Imaging Methods ◽  
Diffusion Tractography ◽  
Fast Pace ◽  
Normal Language ◽  
First Time

The field of neuroanatomy of language is moving forward at a fast pace. This progression is partially due to the development of diffusion tractography, which has been used to describe white matter connections in the living human brain. For the field of neurolinguistics, this advancement is timely and important for two reasons. First, it allows clinical researchers to liberate themselves from neuroanatomical models of language derived from animal studies. Second, for the first time, it offers the possibility of testing network correlates of neurolinguistic models directly in the human brain. This chapter introduces the reader to general principles of diffusion imaging and tractography. Examples of its applications to normal language and its disorders will be used to explicate its potentials and limitations.

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