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Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation

Multicomponent driven equilibrium steady-state observation of T(1) and T(2) (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin conte...

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Autores principales: West, Daniel J., Teixeira, Rui P.A.G., Wood, Tobias C., Hajnal, Joseph V., Tournier, Jacques-Donald, Malik, Shaihan J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7100802/
https://www.ncbi.nlm.nih.gov/pubmed/30930311
http://dx.doi.org/10.1016/j.neuroimage.2019.03.049
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author West, Daniel J.
Teixeira, Rui P.A.G.
Wood, Tobias C.
Hajnal, Joseph V.
Tournier, Jacques-Donald
Malik, Shaihan J.
author_facet West, Daniel J.
Teixeira, Rui P.A.G.
Wood, Tobias C.
Hajnal, Joseph V.
Tournier, Jacques-Donald
Malik, Shaihan J.
author_sort West, Daniel J.
collection PubMed
description Multicomponent driven equilibrium steady-state observation of T(1) and T(2) (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin content. mcDESPOT has a clinically feasible acquisition time and high signal-to-noise ratio (SNR) relative to other MWF techniques. However, disagreement exists in the literature between experimental studies that show MWF maps with plausible grey matter-white matter (GM-WM) contrast and theoretical work that questions the accuracy and precision of mcDESPOT. We demonstrate that mcDESPOT parameter estimation is inaccurate and imprecise if intercompartmental exchange is included in the microstructural model, but that significant bias results if exchange is neglected. The source of apparent MWF contrast is likely due to the complex convergence behaviour of the Stochastic Region Contraction (SRC) method commonly used to fit the mcDESPOT model. mcDESPOT-derived parameter estimates are hence not directly relatable to the underlying microstructural model and are only comparable to others using similar acquisition schemes and fitting constraints.
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spelling pubmed-71008022020-03-27 Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation West, Daniel J. Teixeira, Rui P.A.G. Wood, Tobias C. Hajnal, Joseph V. Tournier, Jacques-Donald Malik, Shaihan J. Neuroimage Article Multicomponent driven equilibrium steady-state observation of T(1) and T(2) (mcDESPOT) aims to quantify the Myelin Water Fraction (MWF) using a two-pool microstructural model. The MWF has been used to track neurodevelopment and neurodegeneration and has been histologically correlated to myelin content. mcDESPOT has a clinically feasible acquisition time and high signal-to-noise ratio (SNR) relative to other MWF techniques. However, disagreement exists in the literature between experimental studies that show MWF maps with plausible grey matter-white matter (GM-WM) contrast and theoretical work that questions the accuracy and precision of mcDESPOT. We demonstrate that mcDESPOT parameter estimation is inaccurate and imprecise if intercompartmental exchange is included in the microstructural model, but that significant bias results if exchange is neglected. The source of apparent MWF contrast is likely due to the complex convergence behaviour of the Stochastic Region Contraction (SRC) method commonly used to fit the mcDESPOT model. mcDESPOT-derived parameter estimates are hence not directly relatable to the underlying microstructural model and are only comparable to others using similar acquisition schemes and fitting constraints. 2019-07-15 2019-03-28 /pmc/articles/PMC7100802/ /pubmed/30930311 http://dx.doi.org/10.1016/j.neuroimage.2019.03.049 Text en http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
West, Daniel J.
Teixeira, Rui P.A.G.
Wood, Tobias C.
Hajnal, Joseph V.
Tournier, Jacques-Donald
Malik, Shaihan J.
Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title_full Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title_fullStr Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title_full_unstemmed Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title_short Inherent and unpredictable bias in multi-component DESPOT myelin water fraction estimation
title_sort inherent and unpredictable bias in multi-component despot myelin water fraction estimation
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7100802/
https://www.ncbi.nlm.nih.gov/pubmed/30930311
http://dx.doi.org/10.1016/j.neuroimage.2019.03.049
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