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Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data

Wiggermann, Vanessa ; Kolind, Shannon L ; Vavasour, Irene M ; MacKay, Alexander L ; Helms, Gunther LU orcid and Rauscher, Alexander (2020) In NMR in Biomedicine 33(12).
Abstract
Multi‐compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non‐negative least squares fitting of multi‐echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi‐compartment T2 and MWF maps. We generated multi‐echo... (More)
Multi‐compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non‐negative least squares fitting of multi‐echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi‐compartment T2 and MWF maps. We generated multi‐echo spin‐echo T2 decay curves following the Carr‐Purcell‐Meiboom‐Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra−/extracellular water geometric mean T2 (gmT2). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1. Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra−/extracellular water gmT2 differed by approximately 0.13–4 percentage points and 3–4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal‐to‐noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo. (Less)
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author
; ; ; ; and
organization
publishing date
type
Contribution to journal
publication status
published
subject
keywords
flip angles, myelin, noise, non-negative least squares, relaxation, spin echo, T2 decay, T2 distribution
in
NMR in Biomedicine
volume
33
issue
12
article number
e4277
publisher
John Wiley & Sons Inc.
external identifiers
  • scopus:85080993764
  • pmid:32124505
ISSN
0952-3480
DOI
10.1002/nbm.4277
project
T2 mapping and myelin water imaging at 7T using 3D GraSe
language
English
LU publication?
yes
id
7e6e17c8-a395-4538-bdd5-3c0e32832d50
date added to LUP
2020-03-03 10:05:33
date last changed
2022-04-18 20:52:41
@article{7e6e17c8-a395-4538-bdd5-3c0e32832d50,
  abstract     = {{Multi‐compartment T2 mapping has gained particular relevance for the study of myelin water in the brain. As a facilitator of rapid saltatory axonal signal transmission, myelin is a cornerstone indicator of white matter development and function. Regularized non‐negative least squares fitting of multi‐echo T2 data has been widely employed for the computation of the myelin water fraction (MWF), and the obtained MWF maps have been histopathologically validated. MWF measurements depend upon the quality of the data acquisition, B1+ homogeneity and a range of fitting parameters. In this special issue article, we discuss the relevance of these factors for the accurate computation of multi‐compartment T2 and MWF maps. We generated multi‐echo spin‐echo T2 decay curves following the Carr‐Purcell‐Meiboom‐Gill approach for various myelin concentrations and myelin T2 scenarios by simulating the evolution of the magnetization vector between echoes based on the Bloch equations. We demonstrated that noise and imperfect refocusing flip angles yield systematic underestimations in MWF and intra−/extracellular water geometric mean T2 (gmT2). MWF estimates were more stable than myelin water gmT2 time across different settings of the T2 analysis. We observed that the lower limit of the T2 distribution grid should be slightly shorter than TE1. Both TE1 and the acquisition echo spacing also have to be sufficiently short to capture the rapidly decaying myelin water T2 signal. Among all parameters of interest, the estimated MWF and intra−/extracellular water gmT2 differed by approximately 0.13–4 percentage points and 3–4 ms, respectively, from the true values, with larger deviations observed in the presence of greater B1+ inhomogeneities and at lower signal‐to‐noise ratio. Tailoring acquisition strategies may allow us to better characterize the T2 distribution, including the myelin water, in vivo.}},
  author       = {{Wiggermann, Vanessa and Kolind, Shannon L and Vavasour, Irene M and MacKay, Alexander L and Helms, Gunther and Rauscher, Alexander}},
  issn         = {{0952-3480}},
  keywords     = {{flip angles, myelin, noise, non-negative least squares, relaxation, spin echo, T2 decay, T2 distribution}},
  language     = {{eng}},
  number       = {{12}},
  publisher    = {{John Wiley & Sons Inc.}},
  series       = {{NMR in Biomedicine}},
  title        = {{Non-negative least squares computation for in vivo myelin mapping using simulated multi-echo spin-echo T2 decay data}},
  url          = {{http://dx.doi.org/10.1002/nbm.4277}},
  doi          = {{10.1002/nbm.4277}},
  volume       = {{33}},
  year         = {{2020}},
}