A Novel 3D Camera-Based ECG-Imaging System for Electrode Position Discovery and Heart-Torso Registration

ECG-imaging has been receiving increasing clinical and commercialization interest as a non-invasive technology for computing cardiac electrical activity and facilitating clinical management of heart rhythm disorders. Despite its potential, the standard ECG-imaging pipeline requires thorax imaging for constructing patient-specific heart-thorax geometry - being outside standard-of-care clinical workflow, this component constitutes a major barrier to the clinical adoption of ECG-imaging. The advent of 3D cameras into ECG-imaging workflow to replace thorax imaging has shown promise, although existing works largely neglect the registration between camera-derived thorax models with an individual's heart geometry. In this work, we address this gap with a novel system that generates patient-specific torso geometry using a 3D camera, registers the torso to heart geometry obtained from pre-existing cardiac scans, and optimally deforms the torso to the skin surface of the patient. We evaluated the presented camera-based ECG-imaging system on five patients undergoing ablation of scar-related ventricular tachycardia, where we evaluate both the accuracy of the surface electrode localization and the ECG-imaging solutions in comparison to those obtained from computed tomography based thorax imaging. We further evaluate the use of the presented camera-based patient-specific heart-thorax model versus a generic heart-thorax model, highlighting the importance of the registration between the camera-based thorax models with cardiac scans.

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Publication Details

Journal
IEEE Journal of Biomedical and Health Informatics
Published
2024-12-23
DOI
https://doi.org/10.1109/jbhi.2024.3520486
Citations
1
Primary Topic
Advanced X-ray and CT Imaging
Type
article
Field-Weighted Citation Impact
0.18
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A Novel 3D Camera-Based ECG-Imaging System for Electrode Position Discovery and Heart-Torso Registration

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IEEE Journal of Biomedical and Health Informatics
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article

A Novel 3D Camera-Based ECG-Imaging System for Electrode Position Discovery and Heart-Torso Registration

Omar Gharbia, Vivek Kumar Singh, Mirmilad Khoshknab, Nikhil Shenoy, Maryam Toloubidokhti, Saman Nazarian, John L. Sapp, Linwei Wang, Ankur Kapoor
article en
1 citations

Abstract

ECG-imaging has been receiving increasing clinical and commercialization interest as a non-invasive technology for computing cardiac electrical activity and facilitating clinical management of heart rhythm disorders. Despite its potential, the standard ECG-imaging pipeline requires thorax imaging for constructing patient-specific heart-thorax geometry - being outside standard-of-care clinical workflow, this component constitutes a major barrier to the clinical adoption of ECG-imaging. The advent of 3D cameras into ECG-imaging workflow to replace thorax imaging has shown promise, although existing works largely neglect the registration between camera-derived thorax models with an individual's heart geometry. In this work, we address this gap with a novel system that generates patient-specific torso geometry using a 3D camera, registers the torso to heart geometry obtained from pre-existing cardiac scans, and optimally deforms the torso to the skin surface of the patient. We evaluated the presented camera-based ECG-imaging system on five patients undergoing ablation of scar-related ventricular tachycardia, where we evaluate both the accuracy of the surface electrode localization and the ECG-imaging solutions in comparison to those obtained from computed tomography based thorax imaging. We further evaluate the use of the presented camera-based patient-specific heart-thorax model versus a generic heart-thorax model, highlighting the importance of the registration between the camera-based thorax models with cardiac scans.

IEEE Journal of Biomedical and Health InformaticsVol. 29(5)
Rochester Institute of Technology (US), University of Utah (US), Queen Elizabeth II Health Sciences Centre (CA), Siemens (United States) (US), University of Pennsylvania (US)
Openalex Percentile: Top 49%
Advanced X-ray and CT Imaging
0.18
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