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Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging

INTRODUCTION: Susceptibility weighted imaging (SWI) is a very sensitive technique that often depicts prominent focal veins (PFV) in patients with acute migraine with aura (MwA). Interpretation of visual venous asymmetry (VVA) between brain hemispheres on SWI may help support the clinical diagnosis o...

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Autores principales: Breiding, Philipe Sebastian, Kellner-Weldon, Frauke, Grunder, Lorenz, Scutelnic, Adrian, Fischer, Urs, Meinel, Thomas Raphael, Slavova, Nedelina, Gralla, Jan, El-Koussy, Marwan, Denier, Niklaus
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269254/
https://www.ncbi.nlm.nih.gov/pubmed/32492059
http://dx.doi.org/10.1371/journal.pone.0233992
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author Breiding, Philipe Sebastian
Kellner-Weldon, Frauke
Grunder, Lorenz
Scutelnic, Adrian
Fischer, Urs
Meinel, Thomas Raphael
Slavova, Nedelina
Gralla, Jan
El-Koussy, Marwan
Denier, Niklaus
author_facet Breiding, Philipe Sebastian
Kellner-Weldon, Frauke
Grunder, Lorenz
Scutelnic, Adrian
Fischer, Urs
Meinel, Thomas Raphael
Slavova, Nedelina
Gralla, Jan
El-Koussy, Marwan
Denier, Niklaus
author_sort Breiding, Philipe Sebastian
collection PubMed
description INTRODUCTION: Susceptibility weighted imaging (SWI) is a very sensitive technique that often depicts prominent focal veins (PFV) in patients with acute migraine with aura (MwA). Interpretation of visual venous asymmetry (VVA) between brain hemispheres on SWI may help support the clinical diagnosis of MwA. Our goal was to develop an automated algorithm for segmentation and quantification of cerebral veins using SWI. MATERIALS AND METHODS: Expert readers visually evaluated SWI of patients with acute MwA for VVA. Subsequently a fully automated algorithm based on 3D normalization and 2D imaging processing using SPM and MATLAB image processing software including top-hat transform was used to quantify cerebral veins and to calculate volumetric differences between hemispheres. RESULTS: Fifty patients with MwA were examined with SWI. VVA was present in 20 of 50 patients (40%). In 95% of patients with VVA, the fully automated calculation agreed with the side that visually harboured more PFV. Our algorithm showed a sensitivity of 95%, specificity of 90% and accuracy of 92% for detecting VVA. Patients with VVA had significantly larger vein volume on the hemisphere with more PFV compared to patients without (15.90 ± 5.38 ml vs 11.93 ± 5.31 ml; p = 0.013). The mean difference in venous volume between hemispheres in patients with VVA was larger compared to patients without VVA (16.34 ± 7.76% vs 4.31 ± 3.26% p < 1E-10). The average time between aura onset and SWI correlated negatively with venous volume of the dominant brain hemisphere (r = -0.348; p = 0.038). CONCLUSION: A fully automated algorithm can accurately identify and quantify cerebral venous distribution on SWI. Absolute quantification may be useful for the future assessment of patients with suspected diseases, which may be associated with a unilateral abnormal degree of venous oxygenation.
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spelling pubmed-72692542020-06-10 Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging Breiding, Philipe Sebastian Kellner-Weldon, Frauke Grunder, Lorenz Scutelnic, Adrian Fischer, Urs Meinel, Thomas Raphael Slavova, Nedelina Gralla, Jan El-Koussy, Marwan Denier, Niklaus PLoS One Research Article INTRODUCTION: Susceptibility weighted imaging (SWI) is a very sensitive technique that often depicts prominent focal veins (PFV) in patients with acute migraine with aura (MwA). Interpretation of visual venous asymmetry (VVA) between brain hemispheres on SWI may help support the clinical diagnosis of MwA. Our goal was to develop an automated algorithm for segmentation and quantification of cerebral veins using SWI. MATERIALS AND METHODS: Expert readers visually evaluated SWI of patients with acute MwA for VVA. Subsequently a fully automated algorithm based on 3D normalization and 2D imaging processing using SPM and MATLAB image processing software including top-hat transform was used to quantify cerebral veins and to calculate volumetric differences between hemispheres. RESULTS: Fifty patients with MwA were examined with SWI. VVA was present in 20 of 50 patients (40%). In 95% of patients with VVA, the fully automated calculation agreed with the side that visually harboured more PFV. Our algorithm showed a sensitivity of 95%, specificity of 90% and accuracy of 92% for detecting VVA. Patients with VVA had significantly larger vein volume on the hemisphere with more PFV compared to patients without (15.90 ± 5.38 ml vs 11.93 ± 5.31 ml; p = 0.013). The mean difference in venous volume between hemispheres in patients with VVA was larger compared to patients without VVA (16.34 ± 7.76% vs 4.31 ± 3.26% p < 1E-10). The average time between aura onset and SWI correlated negatively with venous volume of the dominant brain hemisphere (r = -0.348; p = 0.038). CONCLUSION: A fully automated algorithm can accurately identify and quantify cerebral venous distribution on SWI. Absolute quantification may be useful for the future assessment of patients with suspected diseases, which may be associated with a unilateral abnormal degree of venous oxygenation. Public Library of Science 2020-06-03 /pmc/articles/PMC7269254/ /pubmed/32492059 http://dx.doi.org/10.1371/journal.pone.0233992 Text en © 2020 Breiding et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Breiding, Philipe Sebastian
Kellner-Weldon, Frauke
Grunder, Lorenz
Scutelnic, Adrian
Fischer, Urs
Meinel, Thomas Raphael
Slavova, Nedelina
Gralla, Jan
El-Koussy, Marwan
Denier, Niklaus
Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title_full Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title_fullStr Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title_full_unstemmed Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title_short Quantification of cerebral veins in patients with acute migraine with aura: A fully automated quantification algorithm using susceptibility-weighted imaging
title_sort quantification of cerebral veins in patients with acute migraine with aura: a fully automated quantification algorithm using susceptibility-weighted imaging
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7269254/
https://www.ncbi.nlm.nih.gov/pubmed/32492059
http://dx.doi.org/10.1371/journal.pone.0233992
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