A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction

Oh In Kwon, Eung Je Woo, Yiping P. Du, Dosik Hwang

Research output: Contribution to journalArticle

9 Citations (Scopus)

Abstract

Quantitative assessment of the myelin content in white matter (WM) using MRI has become a useful tool for investigating myelin-related diseases, such as multiple sclerosis (MS). Myelin water fraction (MWF) maps can be estimated pixel-by-pixel by a determination of the T2 or T2; * spectrum from signal decay measurements at each individual image pixel. However, detection of parameters from the measured decay curve, assuming a combination of smooth multi-exponential curves, results in a nonlinear and seriously ill-posed problem. In this paper, we propose a new method to obtain a stable MWF map robust to the presence of noise while sustaining sufficient resolution, which uses weighted combinations of measured decay signals in a spatially independent neighborhood to combine tissues with similar relaxation parameters. To determine optimal weighting factors, we define a spatially independent neighborhood for each pixel and a distance with respect to decay rates that effectively includes pixels with similar decay characteristics, and which therefore have similar relaxation parameters. We recover the MWF values by using optimally weighted decay curves. We use numerical simulations and in vitro and in vivo experimental brain data scanned with a multi-gradient-echo sequence to demonstrate the feasibility of our proposed algorithm and to highlight its advantages compared to the conventional method.

Original languageEnglish
Pages (from-to)12-21
Number of pages10
JournalNeuroImage
Volume74
DOIs
Publication statusPublished - 2013 Jul 1

Fingerprint

Myelin Sheath
Water
Multiple Sclerosis
Noise
Brain

All Science Journal Classification (ASJC) codes

  • Neurology
  • Cognitive Neuroscience

Cite this

@article{21be128763584942988c4041ef61c725,
title = "A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction",
abstract = "Quantitative assessment of the myelin content in white matter (WM) using MRI has become a useful tool for investigating myelin-related diseases, such as multiple sclerosis (MS). Myelin water fraction (MWF) maps can be estimated pixel-by-pixel by a determination of the T2 or T2; * spectrum from signal decay measurements at each individual image pixel. However, detection of parameters from the measured decay curve, assuming a combination of smooth multi-exponential curves, results in a nonlinear and seriously ill-posed problem. In this paper, we propose a new method to obtain a stable MWF map robust to the presence of noise while sustaining sufficient resolution, which uses weighted combinations of measured decay signals in a spatially independent neighborhood to combine tissues with similar relaxation parameters. To determine optimal weighting factors, we define a spatially independent neighborhood for each pixel and a distance with respect to decay rates that effectively includes pixels with similar decay characteristics, and which therefore have similar relaxation parameters. We recover the MWF values by using optimally weighted decay curves. We use numerical simulations and in vitro and in vivo experimental brain data scanned with a multi-gradient-echo sequence to demonstrate the feasibility of our proposed algorithm and to highlight its advantages compared to the conventional method.",
author = "Kwon, {Oh In} and Woo, {Eung Je} and Du, {Yiping P.} and Dosik Hwang",
year = "2013",
month = "7",
day = "1",
doi = "10.1016/j.neuroimage.2013.01.064",
language = "English",
volume = "74",
pages = "12--21",
journal = "NeuroImage",
issn = "1053-8119",
publisher = "Academic Press Inc.",

}

A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction. / Kwon, Oh In; Woo, Eung Je; Du, Yiping P.; Hwang, Dosik.

In: NeuroImage, Vol. 74, 01.07.2013, p. 12-21.

Research output: Contribution to journalArticle

TY - JOUR

T1 - A tissue-relaxation-dependent neighboring method for robust mapping of the myelin water fraction

AU - Kwon, Oh In

AU - Woo, Eung Je

AU - Du, Yiping P.

AU - Hwang, Dosik

PY - 2013/7/1

Y1 - 2013/7/1

N2 - Quantitative assessment of the myelin content in white matter (WM) using MRI has become a useful tool for investigating myelin-related diseases, such as multiple sclerosis (MS). Myelin water fraction (MWF) maps can be estimated pixel-by-pixel by a determination of the T2 or T2; * spectrum from signal decay measurements at each individual image pixel. However, detection of parameters from the measured decay curve, assuming a combination of smooth multi-exponential curves, results in a nonlinear and seriously ill-posed problem. In this paper, we propose a new method to obtain a stable MWF map robust to the presence of noise while sustaining sufficient resolution, which uses weighted combinations of measured decay signals in a spatially independent neighborhood to combine tissues with similar relaxation parameters. To determine optimal weighting factors, we define a spatially independent neighborhood for each pixel and a distance with respect to decay rates that effectively includes pixels with similar decay characteristics, and which therefore have similar relaxation parameters. We recover the MWF values by using optimally weighted decay curves. We use numerical simulations and in vitro and in vivo experimental brain data scanned with a multi-gradient-echo sequence to demonstrate the feasibility of our proposed algorithm and to highlight its advantages compared to the conventional method.

AB - Quantitative assessment of the myelin content in white matter (WM) using MRI has become a useful tool for investigating myelin-related diseases, such as multiple sclerosis (MS). Myelin water fraction (MWF) maps can be estimated pixel-by-pixel by a determination of the T2 or T2; * spectrum from signal decay measurements at each individual image pixel. However, detection of parameters from the measured decay curve, assuming a combination of smooth multi-exponential curves, results in a nonlinear and seriously ill-posed problem. In this paper, we propose a new method to obtain a stable MWF map robust to the presence of noise while sustaining sufficient resolution, which uses weighted combinations of measured decay signals in a spatially independent neighborhood to combine tissues with similar relaxation parameters. To determine optimal weighting factors, we define a spatially independent neighborhood for each pixel and a distance with respect to decay rates that effectively includes pixels with similar decay characteristics, and which therefore have similar relaxation parameters. We recover the MWF values by using optimally weighted decay curves. We use numerical simulations and in vitro and in vivo experimental brain data scanned with a multi-gradient-echo sequence to demonstrate the feasibility of our proposed algorithm and to highlight its advantages compared to the conventional method.

UR - http://www.scopus.com/inward/record.url?scp=84874765333&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84874765333&partnerID=8YFLogxK

U2 - 10.1016/j.neuroimage.2013.01.064

DO - 10.1016/j.neuroimage.2013.01.064

M3 - Article

C2 - 23384527

AN - SCOPUS:84874765333

VL - 74

SP - 12

EP - 21

JO - NeuroImage

JF - NeuroImage

SN - 1053-8119

ER -