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

2021 ◽  
Author(s):  
Rafael Neto Henriques ◽  
Marta Morgado Correia ◽  
Maurizio Maralle ◽  
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 grey 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 cognitive neuroscience research. It will ease the translation of DKI advantages into clinical applications.

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.

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 White matter microstructural integrity across the adult lifespan: Combined perspective of diffusion tensor and kurtosis imaging

2021 ◽  
Author(s):  
Hiba Taha ◽  
Jordan A Chad ◽  
J. Jean Chen
Keyword(s):  
White Matter ◽  
Brain Aging ◽  
Diffusion Tensor ◽  
Diffusion Imaging ◽  
General Pattern ◽  
B Value ◽  
Diffusion Kurtosis Imaging ◽  
Adult Lifespan ◽  
Non Gaussian ◽  
Diffusion Kurtosis

Studies of healthy brain aging have reported diffusivity patterns associated with white matter degeneration using diffusion tensor imaging (DTI), which assumes that diffusion measured at the typical b-value (approximately 1000 s/mm2) is Gaussian. Diffusion kurtosis imaging (DKI) is an extension of DTI that measures non-Gaussian diffusion (kurtosis) to better capture microenvironmental changes by incorporating additional data at a higher b-value. In this study, using UK Biobank data (b values of 1000 and 2000 s/mm2), we investigate (1) the extent of novel information gained from adding diffusional kurtosis to diffusivity observations in aging, and (2) how conventional DTI metrics in aging compare with diffusivity metrics derived from DKI, which are corrected for kurtosis. We find a general pattern of lower kurtosis alongside higher diffusivity among older adults. We also find differences between diffusivity metrics derived from DTI and DKI, emphasizing the importance of accounting for non-Gaussian diffusion. This work highlights the utility of measuring diffusional kurtosis as a simple addition to conventional diffusion imaging of aging.

White-matter relaxation time and myelin water fraction differences in young adults with autism

2014 ◽  
Vol 45 (4) ◽  
pp. 795-805 ◽  
Author(s):  
S. C. L. Deoni ◽  
J. R. Zinkstok ◽  
E. Daly ◽  
C. Ecker ◽  
S. C. R. Williams ◽  
...  
Keyword(s):  
White Matter ◽  
Diffusion Tensor ◽  
Brain Connectivity ◽  
Critical Role ◽  
Relaxation Times ◽  
Imaging Study ◽  
Autism Diagnostic Observation Schedule ◽  
Cross Sectional ◽  
Water Fraction ◽  
Myelin Water Fraction

BackgroundIncreasing evidence suggests that autism is associated with abnormal white-matter (WM) anatomy and impaired brain ‘connectivity’. While myelin plays a critical role in synchronized brain communication, its aetiological role in autistic symptoms has only been indirectly addressed by WM volumetric, relaxometry and diffusion tensor imaging studies. A potentially more specific measure of myelin content, termed myelin water fraction (MWF), could provide improved sensitivity to myelin alteration in autism.MethodWe performed a cross-sectional imaging study that compared 14 individuals with autism and 14 age- and IQ-matched controls. T1 relaxation times (T1), T2 relaxation times (T2) and MWF values were compared between autistic subjects, diagnosed using the Autism Diagnostic Interview – Revised (ADI-R), with current symptoms assessed using the Autism Diagnostic Observation Schedule (ADOS) and typical healthy controls. Correlations between T1, T2 and MWF values with clinical measures [ADI-R, ADOS, and the Autism Quotient (AQ)] were also assessed.ResultsIndividuals with autism showed widespread WM T1 and MWF differences compared to typical controls. Within autistic individuals, worse current social interaction skill as measured by the ADOS was related to reduced MWF although not T1. No significant differences or correlations with symptoms were observed with respect to T2.ConclusionsAutistic individuals have significantly lower global MWF and higher T1, suggesting widespread alteration in tissue microstructure and biochemistry. Areas of difference, including thalamic projections, cerebellum and cingulum, have previously been implicated in the disorder; however, this is the first study to specifically indicate myelin alteration in these regions.

scholarly journals Myelin Water Fraction in Relation To Fractional Anisotropy and Reading in 10-Year-Old Children

2021 ◽  
Author(s):  
Maria Economou ◽  
Thibo Billiet ◽  
Jan Wouters ◽  
Pol Ghesquière ◽  
Jolijn Vanderauwera ◽  
...  
Keyword(s):  
White Matter ◽  
Fractional Anisotropy ◽  
Reading Ability ◽  
Word Reading ◽  
Diffusion Imaging ◽  
Water Fraction ◽  
Diffusion Weighted ◽  
White Matter Microstructure ◽  
Myelin Water Fraction

Abstract Diffusion-weighted imaging studies have repeatedly shown that white matter correlates with reading throughout development. However, the neurobiological interpretation of this relationship is constrained by the limited microstructural specificity of diffusion imaging. A critical component of white matter microstructure is myelin, which can be investigated noninvasively using MRI. Here, diffusion-weighted as well as myelin water imaging were applied to examine the links of myelin water fraction (MWF) with fractional anisotropy (FA; a common diffusion index) and reading ability in 10-year-old children (n = 69). The results replicate previous reports on a positive relationship between FA and MWF, which is significant in dorsal but not ventral tracts. Moreover, our findings revealed a negative correlation between word reading and MWF in left reading-related white matter tracts. Altogether, this study contributes important insights into the role of myelin-related processes in the relationship between reading and white matter structure.

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 Structural abnormalities in thalamo-prefrontal tracks revealed by high angular resolution diffusion imaging predict working memory scores in concussed children

2019 ◽  
Author(s):  
Guido I. Guberman ◽  
Jean-Christophe Houde ◽  
Alain Ptito ◽  
Isabelle Gagnon ◽  
Maxime Descoteaux
Keyword(s):  
Working Memory ◽  
White Matter ◽  
Memory Function ◽  
Diffusion Imaging ◽  
Free Water ◽  
Anterior Cingulate ◽  
High Angular Resolution ◽  
Axonal Loss ◽  
Water Fraction ◽  
The Right

AbstractBecause of their massive prevalence, wide-ranging sequelae, and insidious nature, concussions are a potentially devastating neurological condition, especially in children. Shearing forces transmitted across the brain during concussions often result in white matter damage. The neuropathological impact of concussions has been discerned from animal studies and includes inflammation, demyelination, and axonal loss. These pathologies can overlap during the subacute stage of recovery. However, due to the challenges of accurately modelling complex white matter structure, these neuropathologies have not yet been differentiated in children in vivo. In the present study, we leveraged recent advances in diffusion imaging modelling, tractography, and tractometry to better understand the neuropathology underlying working memory problems in concussion. Studying a sample of 16 concussed and 46 healthy youths, we used novel tractography methods to isolate 11 working memory tracks. Along these tracks, we measured fractional anisotropy, diffusivities, track volume, apparent fiber density, and free water fraction. In three tracks connecting the right thalamus to the right dorsolateral prefrontal cortex (DLPFC), we found microstructural differences suggestive of myelin alterations. In another track connecting the left anterior-cingulate cortex with the left DLPFC, we found microstructural changes suggestive of axonal loss. Structural differences and tractography reconstructions were reproduced using test-retest analyses. White matter structure in the three thalamo-prefrontal tracks, but not the cingulo-prefrontal track, appeared to play a key role in working memory function. The present results improve understanding of working memory neuropathology in concussions, which constitutes an important first step towards developing neuropathologically-informed biomarkers of concussion in children.

scholarly journals Tractography Alterations in the Arcuate and Uncinate Fasciculi in Post-Stroke Aphasia

2021 ◽  
Vol 11 (1) ◽  
pp. 53
Author(s):  
Sara Kierońska ◽  
Milena Świtońska ◽  
Grzegorz Meder ◽  
Magdalena Piotrowska ◽  
Paweł Sokal
Keyword(s):  
White Matter ◽  
Brain Connectivity ◽  
Three Dimensional ◽  
Cerebral White Matter ◽  
Neural Pathways ◽  
Uncinate Fasciculus ◽  
Arcuate Fasciculus ◽  
Fiber Tractography ◽  
Post Stroke

Fiber tractography based on diffuse tensor imaging (DTI) can reveal three-dimensional white matter connectivity of the human brain. Tractography is a non-invasive method of visualizing cerebral white matter structures in vivo, including neural pathways surrounding the ischemic area. DTI may be useful for elucidating alterations in brain connectivity resulting from neuroplasticity after stroke. We present a case of a male patient who developed significant mixed aphasia following ischemic stroke. The patient had been treated by mechanical thrombectomy followed by an early rehabilitation, in conjunction with transcranial direct current stimulation (tDCS). DTI was used to examine the arcuate fasciculus and uncinate fasciculus upon admission and again at three months post-stroke. Results showed an improvement in the patient’s symptoms of aphasia, which was associated with changes in the volume and numbers of tracts in the uncinate fasciculus and the arcuate fasciculus.

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