Myocardial Ischemia Diagnosis Using a Reduced Lead System

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

Abstract

This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6% and specificity 82.7%). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis.
Original languageEnglish
Title of host publicationIEEE Engineering in Medicine and Biology Society. 2018
Pages5302-5305
Number of pages4
DOIs
Publication statusPublished - Jul 2018

Cite this

Aranda Hernandez, A ; Bonizzi, P ; Karel, J ; Peeters, R. / Myocardial Ischemia Diagnosis Using a Reduced Lead System. IEEE Engineering in Medicine and Biology Society. 2018. 2018. pp. 5302-5305
@inproceedings{6da466c17ee242c1b799f67f0bd68342,
title = "Myocardial Ischemia Diagnosis Using a Reduced Lead System",
abstract = "This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6{\%} and specificity 82.7{\%}). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis.",
author = "{Aranda Hernandez}, A and P Bonizzi and J Karel and R Peeters",
year = "2018",
month = "7",
doi = "10.1109/EMBC.2018.8513511",
language = "English",
pages = "5302--5305",
booktitle = "IEEE Engineering in Medicine and Biology Society. 2018",

}

Myocardial Ischemia Diagnosis Using a Reduced Lead System. / Aranda Hernandez, A; Bonizzi, P; Karel, J; Peeters, R.

IEEE Engineering in Medicine and Biology Society. 2018. 2018. p. 5302-5305.

Research output: Chapter in Book/Report/Conference proceedingConference article in proceedingAcademicpeer-review

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T1 - Myocardial Ischemia Diagnosis Using a Reduced Lead System

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AU - Peeters, R

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N2 - This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6% and specificity 82.7%). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis.

AB - This research presents a novel statistical model for diagnosing acute myocardial infarction (AMI). The model is based on features extracted from a reduced lead system consisting of a subset of three leads from the standard 12-lead ECG. We selected a set of relevant parameters commonly used in the clinical practice for ECG-based AMI diagnosis, namely ST elevation and T-wave maximum. We also selectedfeatures, not used in clinical practice, that were derived from vectorcardiography and computed on the reduced three-lead system (pseudo-VCG parameters). To validate the model, we used 104 patients coming from the Physionet STAFF III database which contains 12-lead ECG recordings at baseline and in coronary artery occlusion condition during angioplasty (PTCA). Results show that pseudo-VCG features are able to diagnose AMI slightly better than ST elevation and T-wave maximum features together (area under the ROC curve (AUC) 0.87 vs AUC 0.85). When combining pseudo-VCG features together with ST elevation, and T-wave maximum, the performance improved significantly (AUC 0.95, sensitivity 89.6% and specificity 82.7%). Results indicate a potential for diagnosing AMI using the proposed reduced lead system and the selected set of features. We suggest its possible use for diagnosing AMI in long-term, ambulatory and home monitoring situations, allowing an earlier and faster diagnosis.

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