Evaluation of the accuracy and precision of the diffusion parameter EStImation with Gibbs and NoisE removal pipeline

Ades‐Aron, Benjamin; Veraart, Jelle; Kochunov, Peter; McGuire, Stephen A.; Sherman, Paul M.; Kellner, Elias; Novikov, Dmitry S.; Fieremans, Els

doi:10.1016/j.neuroimage.2018.07.066

Cited by 156 publications

(161 citation statements)

References 43 publications

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“…Diffusion images were processed using the DESIGNER pipeline (Ades‐Aron et al, ). DKI preprocessing steps including: Denoising using a principal component analysis technique (Veraart et al, ; Veraart, Fieremans, & Novikov, ), Rician bias correction within MRtrix (Version 3.0 rc2), Gibbs ringing correction (Kellner, Dhital, Kiselev, & Reisert, ), EPI distortion correction using topup (Andersson et al, ) in FMRIB's Software Library (FSL) version 5.0.11, eddy current and motion correction using eddy in FSL (Version 5.0.11; Andersson & Sotiropoulos, ), and signal outlier detection (Collier, Veraart, Jeurissen, den Dekker, & Sijbers, ).…”

Section: Methodsmentioning

confidence: 99%

White matter plasticity and maturation in human cognition

Bells

Lefebvre

Longoni

et al. 2019

Glia

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White matter plasticity likely plays a critical role in supporting cognitive development. However, few studies have used the imaging methods specific to white matter tissue structure or experimental designs sensitive to change in white matter necessary to elucidate these relations. Here we briefly review novel imaging approaches that provide more specific information regarding white matter microstructure. Furthermore, we highlight recent studies that provide greater clarity regarding the relations between changes in white matter and cognition maturation in both healthy children and adolescents and those with white matter insult. Finally, we examine the hypothesis that white matter is linked to cognitive function via its impact on neural synchronization. We test this hypothesis in a population of children and adolescents with recurrent demyelinating syndromes. Specifically, we evaluate group differences in white matter microstructure within the optic radiation; and neural phase synchrony in visual cortex during a visual task between 25 patients and 28 typically developing age‐matched controls. Children and adolescents with demyelinating syndromes show evidence of myelin and axonal compromise and this compromise predicts reduced phase synchrony during a visual task compared to typically developing controls. We investigate one plausible mechanism at play in this relationship using a computational model of gamma generation in early visual cortical areas. Overall, our findings show a fundamental connection between white matter microstructure and neural synchronization that may be critical for cognitive processing. In the future, longitudinal or interventional studies can build upon our knowledge of these exciting relations between white matter, neural communication, and cognition.

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Section: Methodsmentioning

confidence: 99%

White matter plasticity and maturation in human cognition

Bells

Lefebvre

Longoni

et al. 2019

Glia

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“…AWF is hypothesized to constitute the fraction of diffusion signal that originates from intra‐axonal water. K max is the maximum kurtosis along all directions, and D e ,║ and D e ,⊥ are the apparent axial and radial diffusivities of the extra‐axonal space (Ades‐Aron et al, ; Jelescu et al, ).…”

Section: Methodsmentioning

confidence: 99%

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Kochunov

Donohue

Mitchell

et al. 2018

Human Brain Mapping

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Imaging genetic analyses quantify genetic control over quantitative measurements of brain structure and function using coefficients of relationship (CR) that code the degree of shared genetics between subjects. CR can be inferred through self-reported relatedness or calculated empirically using genome-wide SNP scans. We hypothesized that empirical CR provides a more accurate assessment of shared genetics than self-reported relatedness. We tested this in 1,046 participants of the Human Connectome Project (HCP) (480 M/566 F) recruited from the Missouri twin registry.We calculated the heritability for 17 quantitative traits drawn from four categories (brain diffusion and structure, cognition, and body physiology) documented by the HCP. We compared the heritability and genetic correlation estimates calculated using self-reported and empirical CR methods Kinship-based INference for GWAS (KING) and weighted allelic correlation (WAC). The polygenetic nature of traits was assessed by calculating the empirical CR from chromosomal SNP sets. The heritability estimates based on whole-genome empirical CR were higher but remained significantly correlated (r $0.9) with those obtained using self-reported values. Population stratification in the HCP sample has likely influenced the empirical CR calculations and biased heritability estimates.Heritability values calculated using empirical CR for chromosomal SNP sets were significantly correlated with the chromosomal length (r 0.7) suggesting a polygenic nature for these traits. The Peter Kochunov and Brian Donohue have contributed equally to this work.

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“…We followed this motion correction strategy on purpose, as our focus was to study the effects of thermal noise mitigation on parametric maps. It is possible that the benefits of MP-PCA may extend beyond thermal noise mitigation and may also improve post-processing such as motion correction, as shown in other studies (Ades-Aron et al, 2018), which will be the subject of future investigations.…”

Section: In Vivo Studymentioning

confidence: 83%

“…We synthesised a unique noise-free signal profile in each tissue voxel by simulating within-tissue variability in WM and GM. This ensures that each synthetic voxel has its own unique sources of signal, avoiding obvious redundancies within the set of synthetic signals, as these could lead to overestimation of the performances of MP-PCA denoising (Ades-Aron et al, 2018). In practice, we drew voxel-wise values for each of ( , T 1 , T 2 , AD, RD, , T 2 F , T 2 B , BPF) from a tissue-specific Gaussian distribution, with parameters inspired by values known from literature (Battiston et al, 2018a;Grussu et al, 2015;Smith et al, 2008) (parameters in Table 2).…”

Section: Signal Synthesismentioning

confidence: 99%

Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising

Grussu

Battiston

Veraart

et al. 2019

Preprint

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Multi-parametric quantitative MRI (qMRI) of the spinal cord is a promising non-invasive tool to probe early microstructural damage in neurological disorders. It is usually performed by combining acquisitions with multiple signal readouts, which exhibit different thermal noise levels, geometrical distortions and susceptibility to physiological noise. This ultimately hinders joint multi-contrast modelling and makes the geometric correspondence of parametric maps challenging. We propose an approach to overcome these limitations, by implementing state-of-the-art microstructural MRI of the spinal cord with a unified signal readout. We base our acquisition on single-shot echo planar imaging with reduced field-of-view, and obtain data from two different vendors (vendor 1: Philips Achieva; vendor 2: Siemens Prisma). Importantly, the unified acquisition allows us to compare signal and noise across contrasts, thus enabling overall quality enhancement via Marchenko-Pastur (MP) Principal Component Analysis (PCA) denoising. MP-PCA is a recent method relying on redundant acquisitions, i.e. such that the number of measurements is much larger than the number of informative principal components. Here we used in vivo and synthetic data to test whether a unified readout enables more efficient denoising of less redundant acquisitions, since these can be denoised jointly with more redundant ones. We demonstrate that a unified readout provides robust multi-parametric maps, including diffusion and kurtosis tensors from diffusion MRI, myelin metrics from twopool magnetisation transfer, and T1 and T2 from relaxometry. Moreover, we show that MP-PCA improves the quality of our multi-contrast acquisitions, since it reduces the coefficient of variation (i.e. variability) by up to 15% for mean kurtosis, 8% for bound pool fraction (BPF, myelin-sensitive), and 13% for T1, while enabling more efficient denoising of modalities limited in redundancy (e.g. relaxometry). In conclusion, multiparametric spinal cord qMRI with unified readout is feasible and provides robust microstructural metrics with matched resolution and distortions, whose quality benefits from MP-PCA denoising, a useful pre-processing tool for spinal cord MRI. KeywordsSpinal cord Signal readout Quantitative MRI Multi-parametric MRI Marchenko-Pastur PCA denoising 1. individual denoising of each modality among DW, IR, multi-TE and quantitative MT imaging respectively (importantly, IR, multi-TE have limited redundancy and

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Evaluation of the accuracy and precision of the diffusion parameter EStImation with Gibbs and NoisE removal pipeline

Cited by 156 publications

References 43 publications

White matter plasticity and maturation in human cognition

White matter plasticity and maturation in human cognition

Genomic kinship construction to enhance genetic analyses in the human connectome project data

Multi-parametric quantitative spinal cord MRI with unified signal readout and image denoising

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