Human brain tractography: A DTI vs DKI comparison analysis

Loução, Ricardo; Nunes, Rita G.; Neto-Henriques, Rafael; Correia, Marta; Ferreira, Hugo Alexandre

doi:10.1109/enbeng.2015.7088820

Cited by 2 publications

(1 citation statement)

References 2 publications

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“…In recent years, an increasing number of works in the field of neuroimaging are stressing the importance to move beyond simplistic assumptions of Diffusion Tensor Imaging (DTI) model (Tournier, 2019) towards more advanced diffusion MRI (dMRI) methods, among which DKI (Jensen et al, 2005) is one of the most promising (Farquharson et al, 2013; Loucao et al, 2015; Mader and Urbach, 2013).…”

Section: Introductionmentioning

confidence: 99%

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

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et al. 2021

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Diffusion Kurtosis Imaging (DKI) has undisputed advantages over more classical diffusion Magnetic Resonance Imaging (dMRI), as witnessed by a fast-increasing number of clinical applications and software packages widely adopted in brain imaging domain. Despite its power in probing tissue microstructure compared to conventional MRI, DKI is still largely underutilized in Spinal Cord (SC) imaging because of its inherently demanding technological requirements. If state-of-the-art hardware advancements have recently allowed to make great strides in applying this emerging method to adult and child SC, the same does not apply to neonatal setting. Indeed, amplified technical issues related to SC district in this age range have made this field still unexplored. However, results arising from recent application of DKI to adult and child SC are promising enough to suggest how informative this technique would be in investigating newborns, too. Due to its extreme sensitivity to non-gaussian diffusion, DKI proves particularly suitable for detecting complex, subtle, fast microstructural changes occurring in this area at this early and critical stage of development, and not identifiable with only DTI. Given the multiplicity of congenital anomalies of the spinal canal, their crucial effect on later developmental outcome, and the close interconnection between SC region and the above brain, managing to apply such a method to neonatal cohort becomes of utmost importance. In this work, we illustrate the first semi-automated pipeline for handling with DKI data of neonatal SC, from acquisition setting to estimation of diffusion (DTI & DKI) measures, through accurate adjustment of processing algorithms customized for adult SC. Each processing step of this pipeline, built on Spinal Cord Toolbox (SCT) software, has undergone Quality Control check by supervision of an expert pediatric neuroradiologist, and the overall procedure has preliminarily been tested in a pilot clinical case study. Results of this application agree with findings achieved in a corresponding adult survey, thus confirming validity of adopted pipeline and diagnostic value of DKI in pediatrics. This novel tool hence paves the wave for extending its application also to other promising advanced dMRI models, such as Neurite Orientation Dispersion and Density Imaging (NODDI), and to a wider range of potential clinical applications concerning neonatal period.

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Section: Introductionmentioning

confidence: 99%

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

Trò

Roascio

Tortora

et al. 2021

Preprint

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A critical review of connectome validation studies

2021

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Diffusion MRI tractography is the most widely used macroscale method for mapping connectomes in vivo. However, tractography is prone to various errors and biases, and thus tractography-derived connectomes require careful validation. Here, we critically review studies that have developed or utilized phantoms and tracer maps to validate tractography-derived connectomes, either quantitatively or qualitatively. We identify key factors impacting connectome reconstruction accuracy, including streamline seeding, propagation and filtering methods, and consider the strengths and limitations of state-of-the-art connectome phantoms and associated validation studies. These studies demonstrate the inherent limitations of current fiber orientation models and tractography algorithms and their impact on connectome reconstruction accuracy. Reconstructing connectomes with both high sensitivity and high specificity is challenging, given that some tractography methods can generate an abundance of spurious connections, while others can overlook genuine fiber bundles.We argue that streamline filtering can minimize spurious connections and potentially improve the biological plausibility of connectomes derived from tractography. We find that algorithmic choices such as the tractography seeding methodology, angular threshold, and streamline propagation method can substantially impact connectome reconstruction accuracy. Hence, careful application of tractography is necessary to reconstruct accurate connectomes. Improvements in diffusion MRI acquisition techniques will not necessarily overcome current tractography limitations without accompanying modeling and algorithmic advances. | INTRODUCTIONDiffusion-weighted MRI (dMRI) can be used to non-invasively infer microstructural properties of the brain. Tractography is a reconstruction method based on dMRI to compute the trajectories of white matter (WM) fiber bundles. The primary objective of tractography is to reconstruct non-invasively WM fiber bundles from dMRI. More recently, tractography has been used to map the human structural connectome 1-3 i.e. a comprehensive network description of WM fiber bundles connecting pairs of gray matter (GM) regions (also referred to as structural connectivity).Structural connectomes model the physical links between brain regions, whereas functional connectomes represent the network of functionally connected regions. These connectomes are a static representation of the brain that could change over time. 4,5 When referring to connectomes in this review, we specifically mean structural connectomes mapped with tractography.Generally, connectome mapping using tractography is a five-step process involving (1) dMRI acquisition, (2) segmenting the cortex into regions of interest (ROIs)-cortical parcellation, (3) diffusion/fiber orientation estimation, (4) streamline generation using tractography, and

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Human brain tractography: A DTI vs DKI comparison analysis

Cited by 2 publications

References 2 publications

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

Diffusion Kurtosis Imaging of neonatal Spinal Cord in clinical routine

A critical review of connectome validation studies

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