Takotsubo Syndrome – Predictable from brain imaging data

Abstract Takotsubo syndrome (TTS) is characterized by acute left ventricular dysfunction, with a hospital-mortality rate similar to acute coronary syndrome (ACS). However, the aetiology of TTS is still unknown. In the present study, a multivariate pattern analysis using machine learning with multimo...

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Autores principales:	Carina Klein, Thierry Hiestand, Jelena-Rima Ghadri, Christian Templin, Lutz Jäncke, Jürgen Hänggi
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2017
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/bd2f292601b84e14897a85ddc605c516
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spelling	oai:doaj.org-article:bd2f292601b84e14897a85ddc605c5162021-12-02T11:51:11ZTakotsubo Syndrome – Predictable from brain imaging data10.1038/s41598-017-05592-72045-2322https://doaj.org/article/bd2f292601b84e14897a85ddc605c5162017-07-01T00:00:00Zhttps://doi.org/10.1038/s41598-017-05592-7https://doaj.org/toc/2045-2322Abstract Takotsubo syndrome (TTS) is characterized by acute left ventricular dysfunction, with a hospital-mortality rate similar to acute coronary syndrome (ACS). However, the aetiology of TTS is still unknown. In the present study, a multivariate pattern analysis using machine learning with multimodal magnetic resonance imaging (MRI) data of the human brain of TTS patients and age- and gender-matched healthy control subjects was performed. We found consistent structural and functional alterations in TTS patients compared to the control group. In particular, anatomical and neurophysiological measures from brain regions constituting the emotional-autonomic control system contributed to a prediction accuracy of more than 82%. Thus, our findings demonstrate homogeneous neuronal alterations in TTS patients and substantiate the importance of the concept of a brain-heart interaction in TTS.Carina KleinThierry HiestandJelena-Rima GhadriChristian TemplinLutz JänckeJürgen HänggiNature PortfolioarticleMedicineRScienceQENScientific Reports, Vol 7, Iss 1, Pp 1-7 (2017)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Carina Klein Thierry Hiestand Jelena-Rima Ghadri Christian Templin Lutz Jäncke Jürgen Hänggi Takotsubo Syndrome – Predictable from brain imaging data
description	Abstract Takotsubo syndrome (TTS) is characterized by acute left ventricular dysfunction, with a hospital-mortality rate similar to acute coronary syndrome (ACS). However, the aetiology of TTS is still unknown. In the present study, a multivariate pattern analysis using machine learning with multimodal magnetic resonance imaging (MRI) data of the human brain of TTS patients and age- and gender-matched healthy control subjects was performed. We found consistent structural and functional alterations in TTS patients compared to the control group. In particular, anatomical and neurophysiological measures from brain regions constituting the emotional-autonomic control system contributed to a prediction accuracy of more than 82%. Thus, our findings demonstrate homogeneous neuronal alterations in TTS patients and substantiate the importance of the concept of a brain-heart interaction in TTS.
format	article
author	Carina Klein Thierry Hiestand Jelena-Rima Ghadri Christian Templin Lutz Jäncke Jürgen Hänggi
author_facet	Carina Klein Thierry Hiestand Jelena-Rima Ghadri Christian Templin Lutz Jäncke Jürgen Hänggi
author_sort	Carina Klein
title	Takotsubo Syndrome – Predictable from brain imaging data
title_short	Takotsubo Syndrome – Predictable from brain imaging data
title_full	Takotsubo Syndrome – Predictable from brain imaging data
title_fullStr	Takotsubo Syndrome – Predictable from brain imaging data
title_full_unstemmed	Takotsubo Syndrome – Predictable from brain imaging data
title_sort	takotsubo syndrome – predictable from brain imaging data
publisher	Nature Portfolio
publishDate	2017
url	https://doaj.org/article/bd2f292601b84e14897a85ddc605c516
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Takotsubo Syndrome – Predictable from brain imaging data

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