Severity: Warning
Message: file_get_contents(https://...@gmail.com&api_key=61f08fa0b96a73de8c900d749fcb997acc09): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 143
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 143
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 209
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 994
Function: getPubMedXML
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3134
Function: GetPubMedArticleOutput_2016
File: /var/www/html/application/controllers/Detail.php
Line: 574
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 488
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
Background: In atrial fibrillation (AF) management, understanding left atrial (LA) substrate is crucial. While both electroanatomic mapping (EAM) and late gadolinium enhancement magnetic resonance imaging (LGE-MRI) are accepted methods for assessing the atrial substrate and are associated with ablation outcome, recent findings have highlighted discrepancies between low-voltage areas (LVAs) in EAM and LGE areas.
Objective: The purpose of this study was to explore the relationship between LGE regions and unipolar and bipolar LVAs using multipolar high-density mapping.
Methods: Twenty patients scheduled for AF ablation underwent preablation LGE-MRI. LA segmentation was conducted using a deep learning approach, which subsequently generated a 3-dimensional mesh integrating the LGE data. High-density EAM was performed in sinus rhythm for each patient. The electroanatomic map and LGE-MRI mesh were coregistered. LVAs were defined using cutoffs of 0.5 mV for bipolar voltage and 2.5 mV for unipolar voltage. The correspondence between LGE areas and LVAs in the LA was analyzed using confusion matrices and performance metrics.
Results: A considerable 87.3% of LGE regions overlapped with unipolar LVAs, compared with only 16.2% overlap observed with bipolar LVAs. Across all performance metrics, unipolar LVAs outperformed bipolar LVAs in identifying LGE areas (precision: 78.6% vs 61.1%; sensitivity: 87.3% vs 16.2%; F score: 81.3% vs 26.0%; accuracy: 74.0% vs 35.3%).
Conclusion: Our findings demonstrate that unipolar LVAs strongly correlate with LGE regions. These findings support the integration of unipolar mapping alongside bipolar mapping into clinical practice. This would offer a nuanced approach to diagnose and manage AF by revealing critical insights into the complex architecture of the atrial substrate.
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Source |
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http://dx.doi.org/10.1016/j.hrthm.2024.10.015 | DOI Listing |
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