Automated Localization of Focal Ventricular Tachycardia From Simulated Implanted Device Electrograms: A Combined Physics–AI Approach

Background: Focal ventricular tachycardia (VT) is a life-threating arrhythmia, responsible for high morbidity rates and sudden cardiac death (SCD). Radiofrequency ablation is the only curative therapy against incessant VT; however, its success is dependent on accurate localization of its source, which is highly invasive and time-consuming.Objective: The goal of our study is, as a proof of concept, to demonstrate the possibility of utilizing electrogram (EGM) recordings from cardiac implantable electronic devices (CIEDs). To achieve this, we utilize fast and accurate whole torso electrophysiological (EP) simulations in conjunction with convolutional neural networks (CNNs) to automate the localization of focal VTs using simulated EGMs.Materials and Methods: A highly detailed 3D torso model was used to simulate ∼4000 focal VTs, evenly distributed across the left ventricle (LV), utilizing a rapid reaction-eikonal environment. Solutions were subsequently combined with lead field computations on the torso to derive accurate electrocardiograms (ECGs) and EGM traces, which were used as inputs to CNNs to localize focal sources. We compared the localization performance of a previously developed CNN architecture (Cartesian probability-based) with our novel CNN algorithm utilizing universal ventricular coordinates (UVCs).Results: Implanted device EGMs successfully localized VT sources with localization error (8.74 mm) comparable to ECG-based localization (6.69 mm). Our novel UVC CNN architecture outperformed the existing Cartesian probability-based algorithm (errors = 4.06 mm and 8.07 mm for ECGs and EGMs, respectively). Overall, localization was relatively insensitive to noise and changes in body compositions; however, displacements in ECG electrodes and CIED leads caused performance to decrease (errors 16–25 mm).Conclusion: EGM recordings from implanted devices may be used to successfully, and robustly, localize focal VT sources, and aid ablation planning.

128Non-invasive 3D mapping of earliest activation of premature ventricular complexes originating from intracardiac structures to guide catheter ablation

Funding Acknowledgements Research funding from Catheter Precision, Inc. Introduction Catheter ablation for ventricular arrhythmias such as premature ventricular complexes and ventricular tachycardia is an established management approach. Non-invasive mapping to localise the earliest activation (site of origin) on the myocardium may help guide ablation. Established ECGi methods using the inverse solution to reconstruct epicardial electrograms are unable to accurately locate arrhythmias from the endocardium or from intracardiac structures. VIVO™ (Catheter Precision) is a novel vectorcardiography based 3D mapping system that may be able to localise arrhythmias from any part of the ventricle. Methods We reviewed our initial experience utilising this mapping system to guide catheter ablation of ventricular ectopics from the inter-ventricular septum, coronary cusp or papillary muscle. A patient-specific 3D heart and torso model was created using semi-automated segmentation of MRI or CT scan images. A 3D topographic image of the patient’s torso was taken to accurately position surface ECG electrode locations onto the 3D heart-torso model. An ECG of the PVC was imported from LabSystemPro (Bard) into VIVO™ for analysis prior to ablation. The result was then compared with the site of earliest activation identified using invasive electro-anatomical (EA) mapping. Results VIVO™ was used in 12 cases where the PVC was localised to an intracardiac structure – six papillary muscle, four to the septum and two from the coronary cusp. VIVO™ was able to accurately localise the earliest activation site when compared to the invasive map in 5/6 papillary muscle cases, 3/4 septal cases and 2/2 coronary cusp cases. Ablation was acutely successful in all cases. One additional patient had a PVC localised non-invasively to the postero-medial papillary muscle, however an invasive 3D electro-anatomical map or ablation was not performed. In three cases we were able to merge the 3D geometry of the non-invasive map from VIVO™ into the Carto™ system to guide mapping and ablation in real time (see figure). Conclusion Our experience shows promising results for accurate non-invasive localisation of ventricular arrhythmias originating from intracardiac structures. Non-invasive localisation is of particular value in cases where the arrhythmia is infrequent, difficult to induce or poorly tolerated haemodynamically. The two cases where PVC localisation was inaccurate were performed using an older version of the software. With recent refinements, localisation is anticipated to be improved further. We also present the first experience of combining the VIVO™ geometry with the real-time invasive EA map. This has potential to significantly speed up mapping time and reduce the need for expensive multi-polar catheters by allowing the operator to see their target in real time 3D. Further work is ongoing to validate the accuracy of VIVO™ prospectively and quantitatively. Abstract Figure. VIVO map merged with Carto LV geometry

Modeling radio-frequency energy-induced heating due to the presence of transcranial electric stimulation setup at 3T

Purpose The purpose of the present study was to develop a numerical workflow for simulating temperature increase in a high-resolution human head and torso model positioned in a whole-body magnetic resonance imaging (MRI) radio-frequency (RF) coil in the presence of a transcranial electric stimulation (tES) setup. Methods A customized human head and torso model was developed from medical image data. Power deposition and temperature rise (ΔT) were evaluated with the model positioned in a whole-body birdcage RF coil in the presence of a tES setup. Multiphysics modeling at 3T (123.2 MHz) on unstructured meshes was based on RF circuit, 3D electromagnetic, and thermal co-simulations. ΔT was obtained for (1) a set of electrical and thermal properties assigned to the scalp region, (2) a set of electrical properties of the gel used to ensure proper electrical contact between the tES electrodes and the scalp, (3) a set of electrical conductivity values of skin tissue, (4) four gel patch shapes, and (5) three electrode shapes. Results Significant dependence of power deposition and ΔT on the skin’s electrical properties and electrode and gel patch geometries was observed. Differences in maximum ΔT (> 100%) and its location were observed when comparing the results from a model using realistic human tissue properties and one with an external container made of acrylic material. The electrical and thermal properties of the phantom container material also significantly (> 250%) impacted the ΔT results. Conclusion Simulation results predicted that the electrode and gel geometries, skin electrical conductivity, and position of the temperature sensors have a significant impact on the estimated temperature rise. Therefore, these factors must be considered for reliable assessment of ΔT in subjects undergoing an MRI examination in the presence of a tES setup.

Effect of Torso Non-Homogeneities in the quasi-static inverse problems arising in electrocardiology

In the present paper, an homogeneous and non-homogeneous inverse problem constrained by the stationary problem in electrocardiology representing the heart, lungs surfaces, and torso model is investigated. Our goal is to reconstruct the electrical potentials on the surface of the heart from the information obtained non invasively on the torso surface. The existence and uniqueness of solution for the heart-torso problem and the related inverse problem is assessed, and the primal and dual problems are discretized using a finite element method. We present some preliminary numerical experiments using an efficient implementation of the proposed scheme in homogeneous and non-homogeneous cases. Finally, we demonstrate the effect of the non-homogeneity on the reconstructed epicardial potential and show that the inverse ECG problem cannot be solved by the classical BEM (boundary element method).

PENGGUNAAN MEDIA TORSO MODEL GIGI UNTUK MENINGKATKAN KEMAMPUAN MERAWAT GIGI DAN MULUT ANAK

Penelitian ini dilatarbelakangi oleh masih rendahnya kemampuan anak dalam merawat kesehatan gigi dan mulut. Terihat dari beberapa anak yang mengalami penyakit gigi, belum biasa merawat gigi dengan baik dan belum memeriksakan gigi secara rutin. Tujuan penelitian ini adalah untuk mengetahui penggunaan media torso model gigi dalam meningkatkan kemampuan merawat gigi anak kelompok B di TK. Dalam penelitian ini metode yang digunakan adalah penelitian tindakan kelas dengan pendekatan kualitatif. Subjek penelitian anak kelompok B berjumlah 20 anak yang terdiri atas 6 anak laki – laki dan 14 anak perempuan. Analisis data diperoleh melalui hasil observasi, wawancara dan dokumentasi. Hasil penelitian menunjukan bahwa terdapat peningkatan kemampuan menggosok gigi / merawat kesehatan gigi dan mulut setelah menggunakan media Torso Gigi pada anak kelompok B. Pada penelitian siklus I akhir menunjukan peningkatan yang optimal yaitu pada umumnya anak dalam kategori B (Baik) sebanyak 30% dan pada sikus II akhir mengalami peningkatan yang sangat baik dengan dengan ketercapaian kategori B sebanyak 70%. Adapun rekomendasi bagi guru yaitu para guru perlu mengembangankan dan menciptakan media – media pembelajaran anak yang menarik, salah satunya media torso. Media torso gigi dapat menjadi bahan pertimbangan bagi sekolah sebagai salah satu media pembelajaran yang dapat dikembangkan, sehingga dapat mengembangkan dan mengoptimalkan kemampuan anak dalam kemampuannya menggosok gigi.

Computational Human Torso Model Validation for Frontal Blunt Trauma

Recent research on behind-armor blunt trauma (BABT) has focused on the personal protection offered by lightweight armor. A finite element analysis was performed to improve the biofidelity of the US Army Research Laboratory (ARL) human torso model to prepare for simulating blunt chest impacts and BABT. The overly stiff linear elastic material models for the torso were replaced with material characterizations drawn from current literature. FE torso biofidelity was determined by comparing peak force, force-compression, peak compression, and energy absorption data with cadaver responses to a 23.5 kg pendulum impacting at the sternum at 6.7 m/s. Nonlinear foam, viscous foam, soft rubbers, fibrous hyperelastic rubbers, and low moduli elastic material were considered as material models for the flesh, organs, and bones. Simulations modifying one tissue type revealed that the flesh characterization was most crucial for predicting compression and force, followed closely by the organs characterizations. Combining multiple tissue modifications allowed the FE torso to mimic the cadaveric torsos by reducing peak force and increasing chest compression and energy absorption. Limitations imposed by the Lagrangian finite element approach are discussed with potential workarounds described. Proposed future work is split between considering additional impact scenarios accounting for position and biomaterial variability.