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Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study

Background: Manifestations of typical migraine aura can be numerous. Investigation of its pathophysiological mechanisms can be challenging if a stratification of phenotypes is not performed. In this context, the Migraine Aura Complexity Score (MACS), recently developed, may help. Here we aimed to ca...

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Autores principales: Petrusic, Igor, Viana, Michele, Dakovic, Marko, Zidverc-Trajkovic, Jasna
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813918/
https://www.ncbi.nlm.nih.gov/pubmed/31681162
http://dx.doi.org/10.3389/fneur.2019.01112
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author Petrusic, Igor
Viana, Michele
Dakovic, Marko
Zidverc-Trajkovic, Jasna
author_facet Petrusic, Igor
Viana, Michele
Dakovic, Marko
Zidverc-Trajkovic, Jasna
author_sort Petrusic, Igor
collection PubMed
description Background: Manifestations of typical migraine aura can be numerous. Investigation of its pathophysiological mechanisms can be challenging if a stratification of phenotypes is not performed. In this context, the Migraine Aura Complexity Score (MACS), recently developed, may help. Here we aimed to categorize migraine patients into homogenous groups using MACS and to compare those groups with respect to patients' characteristics and neuroimaging findings. Methods: Participants who have a migraine with aura (MwA) were interviewed after each attack in order to obtain the characteristics of migraine aura. Thereafter, we scored the complexity of their auras by MACS. The MACS was used to categorize patients into three groups: MwA-S (with simple aura), MwA-MC (with moderately complex aura), and MwA-C (with complex aura). The patient characteristics and estimated cortical thickness of regions of interest, which are potentially linked to the symptoms that develop during the aura, were used to compare these groups. Results: In total, 338 MwA attacks were recorded in analyzed groups. Scotoma was the most frequently reported symptom in the groups, followed by somatosensory aura in the MwA-C group and zig-zag lines in the MwA-MC and MwA-S groups. Patients in the MwA-C and MwA-MC groups had a thicker cortex in the left primary visual cortex with respect to MwA-S group. In addition, patients in the MwA-C group had a thicker cortex in several visual and somatosensory cortical regions relative to the MwA-S group. Conclusions: Our results show that the newly developed MACS can be used for the stratification of MwA patients, herewith allowing the better investigation of changes in migraineurs' brains.
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spelling pubmed-68139182019-11-01 Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study Petrusic, Igor Viana, Michele Dakovic, Marko Zidverc-Trajkovic, Jasna Front Neurol Neurology Background: Manifestations of typical migraine aura can be numerous. Investigation of its pathophysiological mechanisms can be challenging if a stratification of phenotypes is not performed. In this context, the Migraine Aura Complexity Score (MACS), recently developed, may help. Here we aimed to categorize migraine patients into homogenous groups using MACS and to compare those groups with respect to patients' characteristics and neuroimaging findings. Methods: Participants who have a migraine with aura (MwA) were interviewed after each attack in order to obtain the characteristics of migraine aura. Thereafter, we scored the complexity of their auras by MACS. The MACS was used to categorize patients into three groups: MwA-S (with simple aura), MwA-MC (with moderately complex aura), and MwA-C (with complex aura). The patient characteristics and estimated cortical thickness of regions of interest, which are potentially linked to the symptoms that develop during the aura, were used to compare these groups. Results: In total, 338 MwA attacks were recorded in analyzed groups. Scotoma was the most frequently reported symptom in the groups, followed by somatosensory aura in the MwA-C group and zig-zag lines in the MwA-MC and MwA-S groups. Patients in the MwA-C and MwA-MC groups had a thicker cortex in the left primary visual cortex with respect to MwA-S group. In addition, patients in the MwA-C group had a thicker cortex in several visual and somatosensory cortical regions relative to the MwA-S group. Conclusions: Our results show that the newly developed MACS can be used for the stratification of MwA patients, herewith allowing the better investigation of changes in migraineurs' brains. Frontiers Media S.A. 2019-10-18 /pmc/articles/PMC6813918/ /pubmed/31681162 http://dx.doi.org/10.3389/fneur.2019.01112 Text en Copyright © 2019 Petrusic, Viana, Dakovic and Zidverc-Trajkovic. 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
Petrusic, Igor
Viana, Michele
Dakovic, Marko
Zidverc-Trajkovic, Jasna
Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title_full Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title_fullStr Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title_full_unstemmed Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title_short Application of the Migraine Aura Complexity Score (MACS): Clinical and Neuroimaging Study
title_sort application of the migraine aura complexity score (macs): clinical and neuroimaging study
topic Neurology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6813918/
https://www.ncbi.nlm.nih.gov/pubmed/31681162
http://dx.doi.org/10.3389/fneur.2019.01112
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