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The Effect of Segmentation Variability in Forward ECG Simulation

hal.structure.identifierInstitute of Measurement Science [IMS]
dc.contributor.authorONDRUSOVA, Beata
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorBOONSTRA, Machteld
hal.structure.identifierSlovak University of Technology in Bratislava [STU]
dc.contributor.authorSVEHLIKOVA, Jana
hal.structure.identifierNortheastern University [Boston]
dc.contributor.authorBROOKS, Dana
hal.structure.identifierUniversity Medical Center [Utrecht] [UMCU]
dc.contributor.authorVAN DAM, Peter
hal.structure.identifierJordanian Royal Medical Services
dc.contributor.authorRABABAH, Ali
hal.structure.identifierScientific Computing and Imaging Institute [SCI Institute]
dc.contributor.authorNARAYAN, Akil
hal.structure.identifierScientific Computing and Imaging Institute [SCI Institute]
dc.contributor.authorMACLEOD, Rob
hal.structure.identifierModélisation et calculs pour l'électrophysiologie cardiaque [CARMEN]
dc.contributor.authorZEMZEMI, Nejib
hal.structure.identifierScientific Computing and Imaging Institute [SCI Institute]
dc.contributor.authorTATE, Jess
dc.date.accessioned2024-04-04T02:36:14Z
dc.date.available2024-04-04T02:36:14Z
dc.date.conference2022-09-04
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/190708
dc.description.abstractEnSegmentation of patient-specific anatomical models is one of the first steps in Electrocardiographic imaging (ECGI). However, the effect of segmentation variability on ECGI remains unexplored. In this study, we assess the effect of heart segmentation variability on ECG simulation. We generated a statistical shape model from segmentations of the same patient and generated 262 cardiac geometries to run in an ECG forward computation of body surface potentials (BSPs) using an equivalent dipole layer cardiac source model and 5 ventricular stimulation protocols. Variability between simulated BSPs for all models and protocols was assessed using Pearson's correlation coefficient (CC). Compared to the BSPs of the mean cardiac shape model, the lowest variability (average CC = 0.98 ± 0.03) was found for apical pacing whereas the highest variability (average CC = 0.90 ± 0.23) was found for right ventricular free wall pacing. Furthermore, low amplitude BSPs show a larger variation in QRS morphology compared to high amplitude signals. The results indicate that the uncertainty in cardiac shape has a significant impact on ECGI.
dc.language.isoen
dc.title.enThe Effect of Segmentation Variability in Forward ECG Simulation
dc.typeCommunication dans un congrès
dc.subject.halSciences du Vivant [q-bio]/Ingénierie biomédicale/Imagerie
bordeaux.hal.laboratoriesInstitut de Mathématiques de Bordeaux (IMB) - UMR 5251*
bordeaux.institutionUniversité de Bordeaux
bordeaux.institutionBordeaux INP
bordeaux.institutionCNRS
bordeaux.conference.titleComputing in Cardiology 2022
bordeaux.countryFI
bordeaux.conference.cityTampere
bordeaux.peerReviewedoui
hal.identifierhal-03936097
hal.version1
hal.invitednon
hal.proceedingsoui
hal.conference.end2022-09-07
hal.popularnon
hal.audienceInternationale
hal.origin.linkhttps://hal.archives-ouvertes.fr//hal-03936097v1
bordeaux.COinSctx_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:journal&rft.au=ONDRUSOVA,%20Beata&BOONSTRA,%20Machteld&SVEHLIKOVA,%20Jana&BROOKS,%20Dana&VAN%20DAM,%20Peter&rft.genre=unknown


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