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Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain
Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matte...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146826/ https://www.ncbi.nlm.nih.gov/pubmed/32318015 http://dx.doi.org/10.3389/fneur.2020.00235 |
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author | Blesa, Manuel Galdi, Paola Sullivan, Gemma Wheater, Emily N. Stoye, David Q. Lamb, Gillian J. Quigley, Alan J. Thrippleton, Michael J. Bastin, Mark E. Boardman, James P. |
author_facet | Blesa, Manuel Galdi, Paola Sullivan, Gemma Wheater, Emily N. Stoye, David Q. Lamb, Gillian J. Quigley, Alan J. Thrippleton, Michael J. Bastin, Mark E. Boardman, James P. |
author_sort | Blesa, Manuel |
collection | PubMed |
description | Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10(−4). PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life. |
format | Online Article Text |
id | pubmed-7146826 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-71468262020-04-21 Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain Blesa, Manuel Galdi, Paola Sullivan, Gemma Wheater, Emily N. Stoye, David Q. Lamb, Gillian J. Quigley, Alan J. Thrippleton, Michael J. Bastin, Mark E. Boardman, James P. Front Neurol Neurology Preterm birth is closely associated with cognitive impairment and generalized dysconnectivity of neural networks inferred from water diffusion MRI (dMRI) metrics. Peak width of skeletonized mean diffusivity (PSMD) is a metric derived from histogram analysis of mean diffusivity across the white matter skeleton, and it is a useful biomarker of generalized dysconnectivity and cognition in adulthood. We calculated PSMD and five other histogram based metrics derived from diffusion tensor imaging (DTI) and neurite orientation and dispersion imaging (NODDI) in the newborn, and evaluated their accuracy as biomarkers of microstructural brain white matter alterations associated with preterm birth. One hundred and thirty five neonates (76 preterm, 59 term) underwent 3T MRI at term equivalent age. There were group differences in peak width of skeletonized mean, axial, and radial diffusivities (PSMD, PSAD, PSRD), orientation dispersion index (PSODI) and neurite dispersion index (PSNDI), all p < 10(−4). PSFA did not differ between groups. PSNDI was the best classifier of gestational age at birth with an accuracy of 81±10%, followed by PSMD, which had 77±9% accuracy. Models built on both NODDI metrics, and on all dMRI metrics combined, did not outperform the model based on PSNDI alone. We conclude that histogram based analyses of DTI and NODDI parameters are promising new image markers for investigating diffuse changes in brain connectivity in early life. Frontiers Media S.A. 2020-04-03 /pmc/articles/PMC7146826/ /pubmed/32318015 http://dx.doi.org/10.3389/fneur.2020.00235 Text en Copyright © 2020 Blesa, Galdi, Sullivan, Wheater, Stoye, Lamb, Quigley, Thrippleton, Bastin and Boardman. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Neurology Blesa, Manuel Galdi, Paola Sullivan, Gemma Wheater, Emily N. Stoye, David Q. Lamb, Gillian J. Quigley, Alan J. Thrippleton, Michael J. Bastin, Mark E. Boardman, James P. Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title | Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title_full | Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title_fullStr | Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title_full_unstemmed | Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title_short | Peak Width of Skeletonized Water Diffusion MRI in the Neonatal Brain |
title_sort | peak width of skeletonized water diffusion mri in the neonatal brain |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7146826/ https://www.ncbi.nlm.nih.gov/pubmed/32318015 http://dx.doi.org/10.3389/fneur.2020.00235 |
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