Multi-component apparent diffusion coefficients in human brain: Relationship to spin-lattice relaxation

Mulkern, Robert V.; Zengingönül, Hale Pınar; Robertson, Richard L.; Bogner, Péter; Zou, Kelly H.; Guðbjartsson, Hákon; Guttmann, Charles R.G.; Holtzman, David; Kyriakos, Walid E.; Jólesz, Ferenc A.; Maier, Stephan E.

doi:10.1002/1522-2594(200008)44:2<292::aid-mrm17>3.0.co;2-q

Cited by 101 publications

(78 citation statements)

References 41 publications

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“…[90][91][92] Recent interpretations of diffusion data in neural fibres by several groups whose analysis schemes have typically used bi-exponential fitting of the curves have favoured the former hypothesis. [81][82][83][84][85][86]88 As discussed below, when the data is taken over an even larger range of b values, bi-exponential fits are no longer adequate to fit the diffusion curves in neural tissue, and it becomes exceedingly difficult to arbitrarily assign fitted components to individual compartments like intra-and extracellular space. In fact, simulations have shown that non-monoexponential behaviour of the diffusion attenuation curves could be due to a wide range of axon sizes in the neural fibres.…”

Section: -85mentioning

confidence: 92%

“…45 The non-monoexponential signal attenuation of the diffusion curves has subsequently been confirmed in other neural fibres such as the rat sciatic nerve, 80 bovine optic nerve, 57,60,61 frog sciatic nerve, 58 rat spinal cord white matter, 62,81 and human brain white matter. [82][83][84][85] The degree of curvature and the signal amplitude at which the curves level off are typically greater for neural fibres than for grey matter in the rat brain [86][87][88][89] or human brain.…”

Section: Mgmentioning

confidence: 98%

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The basis of anisotropic water diffusion in the nervous system – a technical review

2002

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Anisotropic water diffusion in neural fibres such as nerve, white matter in spinal cord, or white matter in brain forms the basis for the utilization of diffusion tensor imaging (DTI) to track fibre pathways. The fact that water diffusion is sensitive to the underlying tissue microstructure provides a unique method of assessing the orientation and integrity of these neural fibres, which may be useful in assessing a number of neurological disorders. The purpose of this review is to characterize the relationship of nuclear magnetic resonance measurements of water diffusion and its anisotropy (i.e. directional dependence) with the underlying microstructure of neural fibres. The emphasis of the review will be on model neurological systems both in vitro and in vivo. A systematic discussion of the possible sources of anisotropy and their evaluation will be presented followed by an overview of various studies of restricted diffusion and compartmentation as they relate to anisotropy. Pertinent pathological models, developmental studies and theoretical analyses provide further insight into the basis of anisotropic diffusion and its potential utility in the nervous system.

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Section: -85mentioning

confidence: 92%

Section: Mgmentioning

confidence: 98%

The basis of anisotropic water diffusion in the nervous system – a technical review

2002

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“…The interval for the exchange time was postulated, t i ʦ [1.0, 4.0] s, whereas the other priors were based on previous studies of white matter (34)(35)(36): (21). The scaling was given by…”

Section: Crlb-based Optimizationmentioning

confidence: 95%

“…The relaxation time constants were given fixed values, T 1 /T 2 ¼ 700/50 ms/ms, which were both low compared with values reported in white matter (35,37,38), but chosen to err on the safe side of low SNR (FEXI loses SNR for short T 1 due to relaxation during t m ). Calculation of the echo times were based on g and s EPI , according to…”

Section: Crlb-based Optimizationmentioning

confidence: 99%

Optimal experimental design for filter exchange imaging: Apparent exchange rate measurements in the healthy brain and in intracranial tumors

Lampinen

Szczepankiewicz

Westen

et al. 2017

Magnetic Resonance in Med

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Purpose: Filter exchange imaging (FEXI) is sensitive to the rate of diffusional water exchange, which depends, eg, on the cell membrane permeability. The aim was to optimize and analyze the ability of FEXI to infer differences in the apparent exchange rate (AXR) in the brain between two populations. Methods: A FEXI protocol was optimized for minimal measurement variance in the AXR. The AXR variance was investigated by test-retest acquisitions in six brain regions in 18 healthy volunteers. Preoperative FEXI data and postoperative microphotos were obtained in six meningiomas and five astrocytomas. Results: Protocol optimization reduced the coefficient of variation of AXR by approximately 40%. Test-retest AXR values were heterogeneous across normal brain regions, from 0.3 6 0.2 s À1

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“…Since the number of radial samples is highly limited, we expect the radial signal to be sparse in R n , i.e. to capture the radial attenuation of E with a few orders n. Several studies [49,50,51,52,53] have reported that the signal decay seems to be a composition of Gaussian functions, the number of functions being determined by the wave-vector norm ||q||. Based on experimental observations, some studies have proposed to model this local diffusion using a bi-exponential function [51,52], suggesting a slow and a fast free diffusion in correspondence to the intra and extra cellular compartments.…”

Section: Spherical Polar Fourier Expansionmentioning

confidence: 99%

Efficient and robust computation of PDF features from diffusion MR signal

Assemlal

Tschumperlé

Brun

2009

Medical Image Analysis

131

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We present a method for the estimation of various features of the tissue micro-architecture using the diffusion magnetic resonance imaging. The considered features are designed from the displacement probability density function (PDF). The estimation is based on two steps: first the approximation of the signal by a series expansion made of Gaussian-Laguerre and Spherical Harmonics functions; followed by a projection on a finite dimensional space. Besides, we propose to tackle the problem of the robustness to Rician noise corrupting in-vivo acquisitions. Our feature estimation is expressed as a variational minimization process leading to a variational framework which is robust to noise. This approach is very flexible regarding the number of samples and enables the computation of a large set of various features of the local tissues structure. We demonstrate the effectiveness of the method with results on both synthetic phantom and real MR datasets acquired in a clinical time-frame.

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Multi-component apparent diffusion coefficients in human brain: Relationship to spin-lattice relaxation

Cited by 101 publications

References 41 publications

The basis of anisotropic water diffusion in the nervous system – a technical review

The basis of anisotropic water diffusion in the nervous system – a technical review

Optimal experimental design for filter exchange imaging: Apparent exchange rate measurements in the healthy brain and in intracranial tumors

Efficient and robust computation of PDF features from diffusion MR signal

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