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Constructing a Human Atrial Fibre Atlas, Roney et al.

Roney, Caroline

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    <dcat:keyword>Atrial Fibrillation, Atrial Fibres, Mesh, Finite Elements, Electrophysiology, Computational Models</dcat:keyword>
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    <dct:description>&lt;p&gt;&lt;strong&gt;Background:&lt;/strong&gt;&amp;nbsp;Atrial anisotropy affects electrical propagation patterns, anchor locations of atrial reentrant drivers, and atrial mechanics. However, patient-specific atrial fibre fields and anisotropy measurements are not currently available, and consequently assigning fibre fields to atrial models is challenging. We aimed to construct an atrial fibre atlas from a high-resolution DTMRI dataset that optimally reproduces electrophysiology simulation predictions corresponding to patient-specific fibre fields, and to develop a methodology for automatically assigning fibres to patient-specific anatomies.&lt;/p&gt; &lt;p&gt;&amp;nbsp;&lt;/p&gt; &lt;p&gt;&lt;strong&gt;Dataset Description:&lt;/strong&gt;&amp;nbsp;We include&amp;nbsp;endocardial and epicardial left and right atrial surfaces for each of the 7 anatomies included in our study (Constructing a Human Atrial Fibre Atlas, ABME, 2020),&amp;nbsp;together with their fibre fields. We also include&amp;nbsp;the average fibre field for each of the atrial surfaces displayed on anatomy number 6 (named *_A).&amp;nbsp;&lt;/p&gt; &lt;p&gt;For each of the surfaces, we also include universal atrial coordinate fields alpha and beta, which are a lateral-septal coordinate and posterior-anterior coordinate for the LA (IVC-SVC coordinate for the RA). More details on the coordinate construction are given in our manuscript and&amp;nbsp;&lt;a href="https://www.ncbi.nlm.nih.gov/pubmed/31026761"&gt;https://www.ncbi.nlm.nih.gov/pubmed/31026761&lt;/a&gt;. These coordinates can be used for registering datasets.&amp;nbsp;&lt;/p&gt; &lt;p&gt;These meshes are in vtk format, consisting of the nodes, triangular elements, the atrial coordinate fields defined on the nodes, and the fibre field defined on the elements.&amp;nbsp;&lt;/p&gt; &lt;p&gt;We have also included mesh files for the Cardiac Arrhythmia Research Package simulator. These are a list of nodal coordinates (.pts file), a list of triangular elements (.elem file), and a fibre file (.lon). More details on this file format and the carpentry simulator are available at:&amp;nbsp;&lt;a href="https://carpentry.medunigraz.at/carputils/index.html"&gt;https://carpentry.medunigraz.at/carputils/index.html&lt;/a&gt;.&amp;nbsp;&lt;/p&gt;</dct:description>
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    <dct:title>Predicting Atrial Fibrillation Mechanisms Through Deep Learning</dct:title>
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    <dct:title>Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy</dct:title>
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    <dct:title>Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models</dct:title>
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Publication date:
April 24, 2020
DOI:
10.5281/zenodo.3764917

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Keyword(s):
Atrial Fibrillation, Atrial Fibres, Mesh, Finite Elements, Electrophysiology, Computational Models
Grants:
Research Councils UK:
  • Predicting Atrial Fibrillation Mechanisms Through Deep Learning (MR/S015086/1)
  • Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy (EP/M012492/1)
  • Wellcome EPSRC Centre for Medical Engineering (NS/A000049/1)
  • Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models (EP/P01268X/1)
License (for files):
Creative Commons Attribution 4.0 International

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