Measurement of translational displacement probabilities by NMR: An indicator of compartmentation

Cory, David G.; Garroway, A. N.

doi:10.1002/mrm.1910140303

Cited by 410 publications

(405 citation statements)

References 18 publications

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“…In fact, the diffusion MRI experiment produces a signal that is the Fourier transform of the diffusion PDF at every imaged brain location. Through this fundamental relationship between MR signal and PDF, it is possible to recover for every imaging voxel the local diffusion PDF, provided that the MR signal is appropriately sampled (Callaghan, 1991;Cory and Garroway, 1990;Wedeen et al, 2005).…”

Section: Mapping the Connectome With Mrimentioning

confidence: 99%

MR connectomics: Principles and challenges

Hagmann

Cammoun

Gigandet

et al. 2010

Journal of Neuroscience Methods

256

207

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a b s t r a c t MR connectomics is an emerging framework in neuro-science that combines diffusion MRI and whole brain tractography methodologies with the analytical tools of network science. In the present work we review the current methods enabling structural connectivity mapping with MRI and show how such data can be used to infer new information of both brain structure and function. We also list the technical challenges that should be addressed in the future to achieve high-resolution maps of structural connectivity. From the resulting tremendous amount of data that is going to be accumulated soon, we discuss what new challenges must be tackled in terms of methods for advanced network analysis and visualization, as well data organization and distribution. This new framework is well suited to investigate key questions on brain complexity and we try to foresee what fields will most benefit from these approaches.

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Section: Mapping the Connectome With Mrimentioning

confidence: 99%

MR connectomics: Principles and challenges

Hagmann

Cammoun

Gigandet

et al. 2010

Journal of Neuroscience Methods

256

207

View full text Add to dashboard Cite

show abstract

“…This was also done Second, non-uniform q-space signals were regridded onto a 9x9x9 Cartesian lattice using a bilinear interpolation algorithm (MATLAB function "griddatan") (Barder et al, 1996). After sample interpolation, the probability density function (PDF) of the water diffusion displacement at the diffusion time Δ was calculated using the Fourier Transform (FT) of the normalized q-space signals (Callaghan, 1991;Cory and Garroway, 1990;Wedeen et al, 2000Wedeen et al, , 2005,…”

Section: Hydi Data Processingmentioning

confidence: 99%

“…In this study, the definition of Po was extended to a three dimensional calculation. The definition of the "mean-displacement", however, was slightly different as they calculated the mean-displacement using the FWHM described in the paper by Cory et al (1990).…”

Section: Hydi Data Processingmentioning

confidence: 99%

“…The most basic approach is diffusion spectrum imaging (DSI), which obtains diffusion-weighted samples on a Cartesian sampling lattice in q-space (Wedeen et al, 2000(Wedeen et al, , 2005. Diffusion displacement spectra are related to the q-space measurements by a Fourier transform (Callaghan, 1991;Cory and Garroway, 1990;King et al, 1994King et al, , 1997. While Cartesian sampling facilitates the straightforward FFT for estimation of the displacement densities of water molecules, it is not required.…”

Section: Introductionmentioning

confidence: 99%

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Hybrid diffusion imaging

2007

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Diffusion measurements in the human central nervous system are complex to characterize and a broad spectrum of methods have been proposed. In this study, a comprehensive diffusion encoding and analysis approach, Hybrid Diffusion Imaging (HYDI), is described. The HYDI encoding scheme is composed of multiple concentric "shells" of constant diffusion-weighting, which may be used to characterize the signal behavior with low, moderate and high diffusion-weighting. HYDI facilitates the application of multiple data-analyses strategies including diffusion tensor imaging (DTI), multiexponential diffusion measurements, diffusion spectrum imaging (DSI) and q-ball imaging (QBI). These different analysis strategies may provide complementary information. DTI measures (mean diffusivity and fractional anisotropy) may be estimated from either data in the inner shells or the entire HYDI data. Fast and slow diffusivities were estimated using a nonlinear least-squares biexponential fit on geometric means of the HYDI shells. DSI measurements from the entire HYDI data yield empirical model-independent diffusion information and are well-suited for characterizing tissue regions with complex diffusion behavior. DSI measurements were characterized using the zero displacement probability and the mean squared displacement. The outermost HYDI shell was analyzed using QBI analysis to estimate the orientation distribution function (ODF), which is useful for characterizing the directions of multiple fiber groups within a voxel. In this study, a HYDI encoding scheme with 102 diffusion-weighted measurements was obtained over most of the human cerebrum in under 30 minutes.

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“…7. The NAA signal attenuation curves are non- Recently, Assaf et al 48 have reported the use of the qspace analysis 49 as a promising means to extract structural information from DW-MRS. In the q-space approach, the displacement profile [i.e.…”

Section: Brainmentioning

confidence: 99%

Diffusion NMR spectroscopy

Nicolay¹,

Braun²,

Graaf³

et al. 2001

NMR in Biomedicine

170

177

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MR offers unique tools for measuring molecular diffusion. This review focuses on the use of diffusionweighted MR spectroscopy (DW-MRS) to non-invasively quantitate the translational displacement of endogenous metabolites in intact mammalian tissues. Most of the metabolites that are observed by in vivo MRS are predominantly located in the intracellular compartment. DW-MRS is of fundamental interest because it enables one to probe the in situ status of the intracellular space from the diffusion characteristics of the metabolites, while at the same time providing information on the intrinsic diffusion properties of the metabolites themselves. Alternative techniques require the introduction of exogenous probe molecules, which involves invasive procedures, and are also unable to measure molecular diffusion in and throughout intact tissues. The length scale of the process(es) probed by MR is in the micrometer range which is of the same order as the dimensions of many intracellular entities. DW-MRS has been used to estimate the dimensions of the cellular elements that restrict intracellular metabolite diffusion in muscle and nerve tissue. In addition, it has been shown that DW-MRS can provide novel information on the cellular response to pathophysiological changes in relation to a range of disorders, including ischemia and excitotoxicity of the brain and cancer.

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Measurement of translational displacement probabilities by NMR: An indicator of compartmentation

Cited by 410 publications

References 18 publications

MR connectomics: Principles and challenges

MR connectomics: Principles and challenges

Hybrid diffusion imaging

Diffusion NMR spectroscopy

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