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Torben Ellegaard Lund

Experimentally and computationally fast method for estimation of a mean kurtosis

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Experimentally and computationally fast method for estimation of a mean kurtosis. / Hansen, Brian; Lund, Torben Ellegaard; Sangill, Ryan; Jespersen, Sune Nørhøj.

In: Magnetic Resonance in Medicine, Vol. 69, No. 6, 06.2013, p. 1754-1760.

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@article{c6d330a73f36409a97e39d11b4234f2c,
title = "Experimentally and computationally fast method for estimation of a mean kurtosis",
abstract = "PURPOSE: Results from several recent studies suggest the magnetic resonance diffusion-derived metric mean kurtosis (MK) to be a sensitive marker for tissue pathology; however, lengthy acquisition and postprocessing time hamper further exploration. The purpose of this study is to introduce and evaluate a new MK metric and a rapid protocol for its estimation. METHODS: The protocol requires acquisition of 13 standard diffusion-weighted images, followed by linear combination of log diffusion signals, thus avoiding nonlinear optimization. The method was evaluated on an ex vivo rat brain and an in vivo human brain. Parameter maps were compared with MK estimated from a standard diffusion kurtosis imaging (DKI) data set comprising 160 diffusion-weighted images. RESULTS: The new MK displays remarkably similar contrast to MK, and the proposed protocol acquires the necessary data in less than 1 min for full human brain coverage, with a postprocessing time of a few seconds. Scan-rescan reproducibility was comparable with MK. CONCLUSION: The framework offers a robust and rapid method for estimating MK, with a protocol easily adapted on commercial scanners, as it requires only minimal modification of standard diffusion-weighting protocols. These properties make the method feasible in practically any clinical setting.",
author = "Brian Hansen and Lund, {Torben Ellegaard} and Ryan Sangill and Jespersen, {Sune N{\o}rh{\o}j}",
note = "Copyright {\textcopyright} 2012 American Association for the Study of Liver Diseases.",
year = "2013",
month = jun,
doi = "10.1002/mrm.24743",
language = "English",
volume = "69",
pages = "1754--1760",
journal = "Magnetic Resonance in Medicine",
issn = "0740-3194",
publisher = "JohnWiley & Sons, Inc.",
number = "6",

}

RIS

TY - JOUR

T1 - Experimentally and computationally fast method for estimation of a mean kurtosis

AU - Hansen, Brian

AU - Lund, Torben Ellegaard

AU - Sangill, Ryan

AU - Jespersen, Sune Nørhøj

N1 - Copyright © 2012 American Association for the Study of Liver Diseases.

PY - 2013/6

Y1 - 2013/6

N2 - PURPOSE: Results from several recent studies suggest the magnetic resonance diffusion-derived metric mean kurtosis (MK) to be a sensitive marker for tissue pathology; however, lengthy acquisition and postprocessing time hamper further exploration. The purpose of this study is to introduce and evaluate a new MK metric and a rapid protocol for its estimation. METHODS: The protocol requires acquisition of 13 standard diffusion-weighted images, followed by linear combination of log diffusion signals, thus avoiding nonlinear optimization. The method was evaluated on an ex vivo rat brain and an in vivo human brain. Parameter maps were compared with MK estimated from a standard diffusion kurtosis imaging (DKI) data set comprising 160 diffusion-weighted images. RESULTS: The new MK displays remarkably similar contrast to MK, and the proposed protocol acquires the necessary data in less than 1 min for full human brain coverage, with a postprocessing time of a few seconds. Scan-rescan reproducibility was comparable with MK. CONCLUSION: The framework offers a robust and rapid method for estimating MK, with a protocol easily adapted on commercial scanners, as it requires only minimal modification of standard diffusion-weighting protocols. These properties make the method feasible in practically any clinical setting.

AB - PURPOSE: Results from several recent studies suggest the magnetic resonance diffusion-derived metric mean kurtosis (MK) to be a sensitive marker for tissue pathology; however, lengthy acquisition and postprocessing time hamper further exploration. The purpose of this study is to introduce and evaluate a new MK metric and a rapid protocol for its estimation. METHODS: The protocol requires acquisition of 13 standard diffusion-weighted images, followed by linear combination of log diffusion signals, thus avoiding nonlinear optimization. The method was evaluated on an ex vivo rat brain and an in vivo human brain. Parameter maps were compared with MK estimated from a standard diffusion kurtosis imaging (DKI) data set comprising 160 diffusion-weighted images. RESULTS: The new MK displays remarkably similar contrast to MK, and the proposed protocol acquires the necessary data in less than 1 min for full human brain coverage, with a postprocessing time of a few seconds. Scan-rescan reproducibility was comparable with MK. CONCLUSION: The framework offers a robust and rapid method for estimating MK, with a protocol easily adapted on commercial scanners, as it requires only minimal modification of standard diffusion-weighting protocols. These properties make the method feasible in practically any clinical setting.

U2 - 10.1002/mrm.24743

DO - 10.1002/mrm.24743

M3 - Journal article

C2 - 23589312

VL - 69

SP - 1754

EP - 1760

JO - Magnetic Resonance in Medicine

JF - Magnetic Resonance in Medicine

SN - 0740-3194

IS - 6

ER -