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Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia
Silent cerebral infarction (SCI) is the most commonly reported radiological abnormality in patients with sickle cell anemia (SCA) and is associated with future clinical stroke risk. To date, there have been few histological and quantitative MRI studies of SCI and multiple radiological definitions ex...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
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Frontiers Media S.A.
2022
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632444/ https://www.ncbi.nlm.nih.gov/pubmed/36341122 http://dx.doi.org/10.3389/fneur.2022.1000889 |
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author | Murdoch, Russell Stotesbury, Hanne Kawadler, Jamie M. Saunders, Dawn E. Kirkham, Fenella J. Shmueli, Karin |
author_facet | Murdoch, Russell Stotesbury, Hanne Kawadler, Jamie M. Saunders, Dawn E. Kirkham, Fenella J. Shmueli, Karin |
author_sort | Murdoch, Russell |
collection | PubMed |
description | Silent cerebral infarction (SCI) is the most commonly reported radiological abnormality in patients with sickle cell anemia (SCA) and is associated with future clinical stroke risk. To date, there have been few histological and quantitative MRI studies of SCI and multiple radiological definitions exist. As a result, the tissue characteristics and composition of SCI remain elusive. The objective of this work was therefore to investigate the composition of segmented SCI lesions using quantitative MRI for R [Formula: see text] and quantitative magnetic susceptibility mapping (QSM). 211 SCI lesions were segmented from 32 participants with SCA and 6 controls. SCI were segmented according to two definitions (FLAIR+/–T1w-based threshold) using a semi-automated pipeline. Magnetic susceptibility (χ) and R [Formula: see text] maps were calculated from a multi-echo gradient echo sequence and mean SCI values were compared to an equivalent region of interest in normal appearing white matter (NAWM). SCI χ and R [Formula: see text] were investigated as a function of SCI definition, patient demographics, anatomical location, and cognition. Compared to NAWM, SCI were significantly less diamagnetic (χ = –0.0067 ppm vs. –0.0153 ppm, p < 0.001) and had significantly lower R [Formula: see text] (16.7 s(−1) vs. 19.2 s(−1), p < 0.001). SCI definition had a significant effect on the mean SCI χ and R [Formula: see text] , with lesions becoming significantly less diamagnetic and having significantly lower R [Formula: see text] after the application of a more stringent T1w-based threshold. SCI-NAWM R [Formula: see text] decrease was significantly greater in patients with SCA compared with controls (–2.84 s(−1) vs. –0.64 s(−1), p < 0.0001). No significant association was observed between mean SCI–NAWM χ or R2(*) differences and subject age, lesion anatomical location, or cognition. The increased χ and decreased R [Formula: see text] in SCI relative to NAWM observed in both patients and controls is indicative of lower myelin or increased water content within the segmented lesions. The significant SCI–NAWM R [Formula: see text] differences observed between SCI in patients with SCA and controls suggests there may be differences in tissue composition relative to NAWM in SCI in the two populations. Quantitative MRI techniques such as QSM and R [Formula: see text] mapping can be used to enhance our understanding of the pathophysiology and composition of SCI in patients with SCA as well as controls. |
format | Online Article Text |
id | pubmed-9632444 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-96324442022-11-04 Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia Murdoch, Russell Stotesbury, Hanne Kawadler, Jamie M. Saunders, Dawn E. Kirkham, Fenella J. Shmueli, Karin Front Neurol Neurology Silent cerebral infarction (SCI) is the most commonly reported radiological abnormality in patients with sickle cell anemia (SCA) and is associated with future clinical stroke risk. To date, there have been few histological and quantitative MRI studies of SCI and multiple radiological definitions exist. As a result, the tissue characteristics and composition of SCI remain elusive. The objective of this work was therefore to investigate the composition of segmented SCI lesions using quantitative MRI for R [Formula: see text] and quantitative magnetic susceptibility mapping (QSM). 211 SCI lesions were segmented from 32 participants with SCA and 6 controls. SCI were segmented according to two definitions (FLAIR+/–T1w-based threshold) using a semi-automated pipeline. Magnetic susceptibility (χ) and R [Formula: see text] maps were calculated from a multi-echo gradient echo sequence and mean SCI values were compared to an equivalent region of interest in normal appearing white matter (NAWM). SCI χ and R [Formula: see text] were investigated as a function of SCI definition, patient demographics, anatomical location, and cognition. Compared to NAWM, SCI were significantly less diamagnetic (χ = –0.0067 ppm vs. –0.0153 ppm, p < 0.001) and had significantly lower R [Formula: see text] (16.7 s(−1) vs. 19.2 s(−1), p < 0.001). SCI definition had a significant effect on the mean SCI χ and R [Formula: see text] , with lesions becoming significantly less diamagnetic and having significantly lower R [Formula: see text] after the application of a more stringent T1w-based threshold. SCI-NAWM R [Formula: see text] decrease was significantly greater in patients with SCA compared with controls (–2.84 s(−1) vs. –0.64 s(−1), p < 0.0001). No significant association was observed between mean SCI–NAWM χ or R2(*) differences and subject age, lesion anatomical location, or cognition. The increased χ and decreased R [Formula: see text] in SCI relative to NAWM observed in both patients and controls is indicative of lower myelin or increased water content within the segmented lesions. The significant SCI–NAWM R [Formula: see text] differences observed between SCI in patients with SCA and controls suggests there may be differences in tissue composition relative to NAWM in SCI in the two populations. Quantitative MRI techniques such as QSM and R [Formula: see text] mapping can be used to enhance our understanding of the pathophysiology and composition of SCI in patients with SCA as well as controls. Frontiers Media S.A. 2022-10-20 /pmc/articles/PMC9632444/ /pubmed/36341122 http://dx.doi.org/10.3389/fneur.2022.1000889 Text en Copyright © 2022 Murdoch, Stotesbury, Kawadler, Saunders, Kirkham and Shmueli. https://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 Murdoch, Russell Stotesbury, Hanne Kawadler, Jamie M. Saunders, Dawn E. Kirkham, Fenella J. Shmueli, Karin Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title | Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title_full | Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title_fullStr | Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title_full_unstemmed | Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title_short | Quantitative susceptibility mapping (QSM) and R2(*) of silent cerebral infarcts in sickle cell anemia |
title_sort | quantitative susceptibility mapping (qsm) and r2(*) of silent cerebral infarcts in sickle cell anemia |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9632444/ https://www.ncbi.nlm.nih.gov/pubmed/36341122 http://dx.doi.org/10.3389/fneur.2022.1000889 |
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