Dataset Open Access
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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.</p>\n\n<p> </p>\n\n<p><strong>Dataset Description:</strong> We include 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), together with their fibre fields. We also include the average fibre field for each of the atrial surfaces displayed on anatomy number 6 (named *_A). </p>\n\n<p>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 <a href=\"https://www.ncbi.nlm.nih.gov/pubmed/31026761\">https://www.ncbi.nlm.nih.gov/pubmed/31026761</a>. These coordinates can be used for registering datasets. </p>\n\n<p>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. </p>\n\n<p>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: <a href=\"https://carpentry.medunigraz.at/carputils/index.html\">https://carpentry.medunigraz.at/carputils/index.html</a>. </p>", "contributors": [ { "affiliation": "King's College London", "type": "Researcher", "name": "Bendikas, Rokas" }, { "affiliation": "Beth Israel Deaconess Medical Center and Harvard Medical School", "type": "Researcher", "name": "Pashakhanloo, Farhad" }, { "affiliation": "King's College London", "type": "Researcher", "name": "Corrado, Cesare" }, { "affiliation": "LIRYC Electrophysiology and Heart Modeling Institute", "type": "Researcher", "name": "Vigmond, Edward" }, { "affiliation": "UC San Diego School of Engineering", "type": "Researcher", "name": "McVeigh, Elliot" }, { "affiliation": "Johns Hopkins University", "type": "Researcher", "name": "Trayanova, Natalia" }, { "orcid": "0000-0002-4612-6982", "affiliation": "King's College London", "type": "Researcher", "name": "Niederer, Steven" } ], "title": "Constructing a Human Atrial Fibre Atlas, Roney et al.", "license": { "id": "CC-BY-4.0" }, "relations": { "version": [ { "count": 1, "index": 0, "parent": { "pid_type": "recid", "pid_value": "3764916" }, "is_last": true, "last_child": { "pid_type": "recid", "pid_value": "3764917" } } ] }, "grants": [ { "code": "MR/S015086/1", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000690::MR/S015086/1" }, "title": "Predicting Atrial Fibrillation Mechanisms Through Deep Learning", "acronym": "", "program": "MRC", "funder": { "doi": "10.13039/501100000690", "acronyms": [], "name": "Research Councils UK", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000690" } } }, { "code": "EP/M012492/1", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000690::EP/M012492/1" }, "title": "Personalised Model Based Optimal Lead Guidance in Cardiac Resynchronisation Therapy", "acronym": "", "program": "EPSRC", "funder": { "doi": "10.13039/501100000690", "acronyms": [], "name": "Research Councils UK", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000690" } } }, { "code": "NS/A000049/1", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000690::NS/A000049/1" }, "title": "Wellcome EPSRC Centre for Medical Engineering", "acronym": "", "program": "EPSRC", "funder": { "doi": "10.13039/501100000690", "acronyms": [], "name": "Research Councils UK", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000690" } } }, { "code": "EP/P01268X/1", "links": { "self": "https://zenodo.org/api/grants/10.13039/501100000690::EP/P01268X/1" }, "title": "Uncertainty Quantification in Prospective and Predictive Patient Specific Cardiac Models", "acronym": "", "program": "EPSRC", "funder": { "doi": "10.13039/501100000690", "acronyms": [], "name": "Research Councils UK", "links": { "self": "https://zenodo.org/api/funders/10.13039/501100000690" } } } ], "keywords": [ "Atrial Fibrillation, Atrial Fibres, Mesh, Finite Elements, Electrophysiology, Computational Models" ], "publication_date": "2020-04-24", "creators": [ { "orcid": "0000-0001-6809-0928", "affiliation": "King's College London", "name": "Roney, Caroline" } ], "access_right": "open", "resource_type": { "type": "dataset", "title": "Dataset" }, "related_identifiers": [ { "scheme": "doi", "identifier": "10.5281/zenodo.3764916", "relation": "isVersionOf" } ] } }
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Views | 526 | 526 |
Downloads | 47 | 47 |
Data volume | 17.8 GB | 17.8 GB |
Unique views | 442 | 442 |
Unique downloads | 46 | 46 |