Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data

Jeurissen, Ben; Tournier, Jacques‐Donald; Dhollander, Thijs; Connelly, Alan; Sijbers, Jan

doi:10.1016/j.neuroimage.2014.07.061

Cited by 1,204 publications

(1,152 citation statements)

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“…The response functions of dataset 2 are depicted on the left in Fig. 4, and compared to the response functions of WM, GM, and CSF, estimated as described in [8] based on a prior segmentation of the T1 image (dashed lines). The RFs estimated in our (unsupervised) method qualitatively correspond to those obtained from the supervised method, up to a scaling factor.…”

Section: Results On Human Brain Datamentioning

confidence: 99%

“…When S b and F t are represented in the basis of real, symmetric spherical harmonics (SH) of maximum order max , and the response functions H t,b are represented as zonal harmonics (phase m = 0), the convolution reduces to a multiplication of the coefficients of corresponding order , i.e., [4,8]. We then structure the SH coefficients of all voxels v and shells b in the tensor equation…”

Section: Methodsmentioning

confidence: 99%

“…We solve (2) for the ODFsF in each voxel by unrolling all tensors along the dimensions of shells and SH coefficients. This results in the constrained least-squares expression identical to multi-shell multi-tissue spherical deconvolution [8], which is solved with quadratic programming (QP) given the non-negativity constraints onF . Subsequently, (2) can be solved forH by unrolling across all voxels and SH coefficients.…”

Section: Methodsmentioning

confidence: 99%

“…1. The phantom contains 3 tissue classes, mimicking WM, GM and CSF regions, each simulated by a ground-truth RF that was originally estimated from in vivo data according to the procedure advised in [8]. The WM ODF is represented at max = 10.…”

Section: Monte-carlo Simulationsmentioning

confidence: 99%

“…Recent work has extended SD to multiple tissue types [8]. Yet, for calibrating the tissue response functions they rely on a prior tissue segmentation obtained from a T1-weighted MR image, which may not always be available or may not be well aligned to the DWI data, e.g., due to EPI distortion [9].…”

Section: Introductionmentioning

confidence: 99%

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Convex Non-negative Spherical Factorization of Multi-Shell Diffusion-Weighted Images

Christiaens

Maes

Sunaert

et al. 2015

Lecture Notes in Computer Science

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Abstract. Diffusion-weighted imaging (DWI) allows to probe tissue microstructure non-invasively and study healthy and diseased white matter (WM) in vivo. Yet, less research has focussed on modelling grey matter (GM), cerebrospinal fluid (CSF) and other tissues. Here, we introduce a fully data-driven approach to spherical deconvolution, based on convex non-negative matrix factorization. Our approach decomposes multi-shell DWI data, represented in the basis of spherical harmonics, into tissuespecific orientation distribution functions and corresponding response functions. We evaluate the proposed method in phantom simulations and in vivo brain images, and demonstrate its ability to reconstruct WM, GM and CSF, unsupervised and solely relying on DWI.

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Section: Results On Human Brain Datamentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Monte-carlo Simulationsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Convex Non-negative Spherical Factorization of Multi-Shell Diffusion-Weighted Images

Christiaens

Maes

Sunaert

et al. 2015

Lecture Notes in Computer Science

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Neuroanatomical Substrates and Symptoms Associated With Magnetic Resonance Imaging of Patients With Mild Traumatic Brain Injury

et al. 2021

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Early Cognitive, Structural, and Microstructural Changes in Presymptomatic C9orf72 Carriers Younger Than 40 Years

et al. 2018

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; for the Predict to Prevent Frontotemporal Lobar Degeneration and Amyotrophic Lateral Sclerosis (PREV-DEMALS) Study Group IMPORTANCE Presymptomatic carriers of chromosome 9 open reading frame 72 (C9orf72) mutation, the most frequent genetic cause of frontotemporal lobar degeneration and amyotrophic lateral sclerosis, represent the optimal target population for the development of disease-modifying drugs. Preclinical biomarkers are needed to monitor the effect of therapeutic interventions in this population. OBJECTIVES To assess the occurrence of cognitive, structural, and microstructural changes in presymptomatic C9orf72 carriers. DESIGN, SETTING, AND PARTICIPANTS The PREV-DEMALS study is a prospective, multicenter, observational study of first-degree relatives of individuals carrying the C9orf72 mutation. Eighty-four participants entered the study between October 2015 and April 2017; 80 (95%) were included in cross-sectional analyses of baseline data. All participants underwent neuropsychological testing and magnetic resonance imaging; 63 (79%) underwent diffusion tensor magnetic resonance imaging. Gray matter volumes and diffusion tensor imaging metrics were calculated within regions of interest. Anatomical and microstructural differences between individuals who carried the C9orf72 mutation (C9+) and those who did not carry the C9orf72 mutation (C9−) were assessed using linear mixed-effects models. Data were analyzed from October 2015 to April 2017. MAIN OUTCOMES AND MEASURES Differences in neuropsychological scores, gray matter volume, and white matter integrity between C9+ and C9− individuals. RESULTS Of the 80 included participants, there were 41 C9+ individuals (24 [59%] female; mean [SD] age, 39.8 [11.1] years) and 39 C9− individuals (24 [62%] female; mean [SD] age, 45.2 [13.9] years). Compared with C9− individuals, C9+ individuals had lower mean (SD) praxis scores (163.4 [6.1] vs 165.3 [5.9]; P = .01) and intransitive gesture scores (34.9 [1.6] vs 35.7 [1.5]; P = .004), atrophy in 8 cortical regions of interest and in the right thalamus, and white matter alterations in 8 tracts. When restricting the analyses to participants younger than 40 years, compared with C9− individuals, C9+ individuals had lower praxis scores and intransitive gesture scores, atrophy in 4 cortical regions of interest and in the right thalamus, and white matter alterations in 2 tracts. CONCLUSIONS AND RELEVANCE Cognitive, structural, and microstructural alterations are detectable in young C9+ individuals. Early and subtle praxis alterations, underpinned by focal atrophy of the left supramarginal gyrus, may represent an early and nonevolving phenotype related to neurodevelopmental effects of C9orf72 mutation. White matter alterations reflect the future phenotype of frontotemporal lobar degeneration/amyotrophic lateral sclerosis, while atrophy appears more diffuse. Our results contribute to a better understanding of the preclinical phase of C9orf72 disease and of the respective contribution of magnetic resonance biomarkers. TRIAL REGIS...

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Multi-tissue constrained spherical deconvolution for improved analysis of multi-shell diffusion MRI data

Cited by 1,204 publications

References 68 publications

Convex Non-negative Spherical Factorization of Multi-Shell Diffusion-Weighted Images

Convex Non-negative Spherical Factorization of Multi-Shell Diffusion-Weighted Images

Neuroanatomical Substrates and Symptoms Associated With Magnetic Resonance Imaging of Patients With Mild Traumatic Brain Injury

Early Cognitive, Structural, and Microstructural Changes in Presymptomatic C9orf72 Carriers Younger Than 40 Years

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