Corentin Dallet, L. Bear, J. Duchâteau, M. Potse, N. Zemzemi, V. Meillet, Y. Coudière, R. Dubois
{"title":"局部传导速度测绘用于心电图成像","authors":"Corentin Dallet, L. Bear, J. Duchâteau, M. Potse, N. Zemzemi, V. Meillet, Y. Coudière, R. Dubois","doi":"10.1109/CIC.2015.7408627","DOIUrl":null,"url":null,"abstract":"Slow conduction is a well-known pro-arrhythmic feature for tachycardia and fibrillation. Cardiac conduction velocity (CV) mapping can be extremely helpful for investigating unusual activation patterns. Although methods have been developed to estimate velocity vector field, from ex-vivo preparations (e.g. from optical mapping recordings), the estimation from in-vivo electrograms (EGMs) remains challenging. This paper presents a new method specifically designed for EGMs reconstructed non-invasively from body surface potentials using electrocardiographic imaging (ECGi). The algorithm is based on cardiac activation maps and assumes either a linear or quadratic wavefront shape. The proposed methodology was performed on computed and experimental data for epicardial pacing on healthy tissue. The results were compared with reference velocity vector fields and evaluated by analyzing the errors of direction and speed. The outcomes indicate that a linear wavefront is the most suited for cardiac propagation in healthy tissue.","PeriodicalId":414802,"journal":{"name":"2015 Computing in Cardiology Conference (CinC)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2015-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"Local conduction velocity mapping for electrocardiographic imaging\",\"authors\":\"Corentin Dallet, L. Bear, J. Duchâteau, M. Potse, N. Zemzemi, V. Meillet, Y. Coudière, R. Dubois\",\"doi\":\"10.1109/CIC.2015.7408627\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Slow conduction is a well-known pro-arrhythmic feature for tachycardia and fibrillation. Cardiac conduction velocity (CV) mapping can be extremely helpful for investigating unusual activation patterns. Although methods have been developed to estimate velocity vector field, from ex-vivo preparations (e.g. from optical mapping recordings), the estimation from in-vivo electrograms (EGMs) remains challenging. This paper presents a new method specifically designed for EGMs reconstructed non-invasively from body surface potentials using electrocardiographic imaging (ECGi). The algorithm is based on cardiac activation maps and assumes either a linear or quadratic wavefront shape. The proposed methodology was performed on computed and experimental data for epicardial pacing on healthy tissue. The results were compared with reference velocity vector fields and evaluated by analyzing the errors of direction and speed. The outcomes indicate that a linear wavefront is the most suited for cardiac propagation in healthy tissue.\",\"PeriodicalId\":414802,\"journal\":{\"name\":\"2015 Computing in Cardiology Conference (CinC)\",\"volume\":\"10 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2015-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2015 Computing in Cardiology Conference (CinC)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/CIC.2015.7408627\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2015 Computing in Cardiology Conference (CinC)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/CIC.2015.7408627","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Local conduction velocity mapping for electrocardiographic imaging
Slow conduction is a well-known pro-arrhythmic feature for tachycardia and fibrillation. Cardiac conduction velocity (CV) mapping can be extremely helpful for investigating unusual activation patterns. Although methods have been developed to estimate velocity vector field, from ex-vivo preparations (e.g. from optical mapping recordings), the estimation from in-vivo electrograms (EGMs) remains challenging. This paper presents a new method specifically designed for EGMs reconstructed non-invasively from body surface potentials using electrocardiographic imaging (ECGi). The algorithm is based on cardiac activation maps and assumes either a linear or quadratic wavefront shape. The proposed methodology was performed on computed and experimental data for epicardial pacing on healthy tissue. The results were compared with reference velocity vector fields and evaluated by analyzing the errors of direction and speed. The outcomes indicate that a linear wavefront is the most suited for cardiac propagation in healthy tissue.