dc.contributor.author |
Wang, Yufeng |
|
dc.contributor.author |
Xiong, Zhaohan |
|
dc.contributor.author |
Nalar, Aaqel |
|
dc.contributor.author |
Hansen, Brian J |
|
dc.contributor.author |
Kharche, Sanjay |
|
dc.contributor.author |
Seemann, Gunnar |
|
dc.contributor.author |
Loewe, Axel |
|
dc.contributor.author |
Fedorov, Vadim V |
|
dc.contributor.author |
Zhao, Jichao |
|
dc.coverage.spatial |
United States |
|
dc.date.accessioned |
2021-05-20T03:20:28Z |
|
dc.date.available |
2021-05-20T03:20:28Z |
|
dc.date.issued |
2019-11 |
|
dc.identifier.citation |
Computers in biology and medicine 114:103444 Nov 2019 |
|
dc.identifier.issn |
0010-4825 |
|
dc.identifier.uri |
https://hdl.handle.net/2292/55113 |
|
dc.description.abstract |
Atrial fibrillation (AF) is the most prevalent form of cardiac arrhythmia. The atrial wall thickness (AWT) can potentially improve our understanding of the mechanism underlying atrial structure that drives AF and provides important clinical information. However, most existing studies for estimating AWT rely on ruler-based measurements performed on only a few selected locations in 2D or 3D using digital calipers. Only a few studies have developed automatic approaches to estimate the AWT in the left atrium, and there are currently no methods to robustly estimate the AWT of both atrial chambers. Therefore, we have developed a computational pipeline to automatically calculate the 3D AWT across bi-atrial chambers and extensively validated our pipeline on both ex vivo and in vivo human atria data. The atrial geometry was first obtained by segmenting the atrial wall from the MRIs using a novel machine learning approach. The epicardial and endocardial surfaces were then separated using a multi-planar convex hull approach to define boundary conditions, from which, a Laplace equation was solved numerically to automatically separate bi-atrial chambers. To robustly estimate the AWT in each atrial chamber, coupled partial differential equations by coupling the Laplace solution with two surface trajectory functions were formulated and solved. Our pipeline enabled the reconstruction and visualization of the 3D AWT for bi-atrial chambers with a relative error of 8% and outperformed existing algorithms by >7%. Our approach can potentially lead to improved clinical diagnosis, patient stratification, and clinical guidance during ablation treatment for patients with AF. |
|
dc.format.medium |
Print-Electronic |
|
dc.language |
eng |
|
dc.publisher |
Elsevier BV |
|
dc.relation.ispartofseries |
Computers in biology and medicine |
|
dc.rights |
Items in ResearchSpace are protected by copyright, with all rights reserved, unless otherwise indicated. Previously published items are made available in accordance with the copyright policy of the publisher. |
|
dc.rights.uri |
https://researchspace.auckland.ac.nz/docs/uoa-docs/rights.htm |
|
dc.rights.uri |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
dc.subject |
Heart Atria |
|
dc.subject |
Humans |
|
dc.subject |
Imaging, Three-Dimensional |
|
dc.subject |
Magnetic Resonance Imaging |
|
dc.subject |
Algorithms |
|
dc.subject |
Aged |
|
dc.subject |
Middle Aged |
|
dc.subject |
Female |
|
dc.subject |
Male |
|
dc.subject |
Atrial fibrillation |
|
dc.subject |
Atrial wall thickness |
|
dc.subject |
Human atria |
|
dc.subject |
Laplace solution |
|
dc.subject |
MRI |
|
dc.subject |
Aged |
|
dc.subject |
Algorithms |
|
dc.subject |
Female |
|
dc.subject |
Heart Atria |
|
dc.subject |
Humans |
|
dc.subject |
Imaging, Three-Dimensional |
|
dc.subject |
Magnetic Resonance Imaging |
|
dc.subject |
Male |
|
dc.subject |
Middle Aged |
|
dc.subject |
Science & Technology |
|
dc.subject |
Life Sciences & Biomedicine |
|
dc.subject |
Technology |
|
dc.subject |
Biology |
|
dc.subject |
Computer Science, Interdisciplinary Applications |
|
dc.subject |
Engineering, Biomedical |
|
dc.subject |
Mathematical & Computational Biology |
|
dc.subject |
Life Sciences & Biomedicine - Other Topics |
|
dc.subject |
Computer Science |
|
dc.subject |
Engineering |
|
dc.subject |
Atrial fibrillation |
|
dc.subject |
Atrial wall thickness |
|
dc.subject |
Laplace solution |
|
dc.subject |
Human atria |
|
dc.subject |
MRI |
|
dc.subject |
IMAGE-BASED MODEL |
|
dc.subject |
FIBRILLATION |
|
dc.subject |
ABLATION |
|
dc.subject |
ANATOMY |
|
dc.subject |
QUANTIFICATION |
|
dc.subject |
CONDUCTION |
|
dc.subject |
0801 Artificial Intelligence and Image Processing |
|
dc.subject |
1102 Cardiorespiratory Medicine and Haematology |
|
dc.subject |
Clinical Medicine and Science |
|
dc.subject |
Cardiovascular |
|
dc.subject |
Heart Disease |
|
dc.subject |
Clinical Research |
|
dc.subject |
Cardiovascular |
|
dc.subject |
08 Information and Computing Sciences |
|
dc.subject |
09 Engineering |
|
dc.subject |
11 Medical and Health Sciences |
|
dc.title |
A robust computational framework for estimating 3D Bi-Atrial chamber wall thickness. |
|
dc.type |
Journal Article |
|
dc.identifier.doi |
10.1016/j.compbiomed.2019.103444 |
|
pubs.begin-page |
103444 |
|
pubs.volume |
114 |
|
dc.date.updated |
2021-04-04T21:45:32Z |
|
dc.rights.holder |
Copyright: The author |
en |
pubs.author-url |
https://www.ncbi.nlm.nih.gov/pubmed/31542646 |
|
pubs.publication-status |
Published |
|
dc.rights.accessrights |
http://purl.org/eprint/accessRights/OpenAccess |
en |
pubs.subtype |
Research Support, Non-U.S. Gov't |
|
pubs.subtype |
research-article |
|
pubs.subtype |
Journal Article |
|
pubs.subtype |
Research Support, N.I.H., Extramural |
|
pubs.elements-id |
783882 |
|
dc.identifier.eissn |
1879-0534 |
|
dc.identifier.pii |
S0010-4825(19)30321-X |
|
pubs.number |
103444 |
|