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Bioengineering
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Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to...
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Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to the Diagnosis and Treatment of Cardiac Arrhythmias

A special issue of Bioengineering (ISSN 2306-5354).

Deadline for manuscript submissions: closed (30 September 2023) | Viewed by 5112

Special Issue Editors

Prof. Dr. Enrique Berjano

E-Mail Website
Guest Editor
BioMIT, Department of Electronic Engineering, Polytechnic University of Valencia, 46022 Valencia, Spain
Interests: Bioimpedance; cardiac ablation; computer modeling; cardiac electrophysiology; medical instrumentation; minimally invasive technology; surgical technology; thermal therapy; tumor ablation
Prof. Dr. José J. Rieta

E-Mail Website
Guest Editor
BioMIT, Department of Electronic Engineering, Polytechnic University of Valencia, 46022 Valencia, Spain
Interests: biomedical signal processing; nonlinear signal processing; cardiovascular signals; atrial arrythmias; wearables
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Current research on the diagnosis and treatment of cardiac arrhythmias, both basic and clinically oriented, revolves in most cases around computing. The significant advances achieved in the field of signal analysis and processing in recent years have allowed a much better characterization of arrhythmias, both from surface and invasive recordings, and the application of artificial intelligence (machine learning and deep learning) to multimodal signals from cardiovascular recordings is currently an effervescent field in constant advance. Furthermore, mathematical modeling and its physical implementation in silico allow an increasingly deep and reliable description of electrophysiological behavior at the cellular and tissue levels, which provides a cost-effective tool in the investigation of new drugs for the treatment of arrhythmias. Finally, computer modeling is also broadly used to study the performance of ablative techniques intended to remove cardiac arrhythmias in a minimally invasive way (radiofrequency, laser, electroporation, etc.)

Today, the computer-based approach is no longer just reserved for engineers and physicists but is a tool used daily by cardiologists and electrophysiologists, from medical instrumentation intended for cardiac diagnosis to ablative medical devices. The short-term future must also consider extensive and intelligent use of big data to propose therapies tailored to each patient (combining electrical activity mapping and medical imaging).

This Special Issue will focus on current research and advances based on bioengineering applied to diagnosis and treatment of cardiac arrhythmias.

The journal will be accepting contributions (both original articles and reviews) mainly centered on the following topics:

  • Signal processing of cardiac recordings to characterize arrythmias;
  • Artificial intelligence applied to patient-specific diagnosis or treatment;
  • Applications of big data to cardiac arrythmias;
  • Medical imaging for diagnosis and treatment of cardiac arrhythmias;
  • Energy-based cardiac ablation;
  • Electrophysiological mapping;
  • Drug development for treatment of cardiac arrhythmias;
  • Cardiac electrophysiology.

Prof. Dr. Enrique Berjano
Prof. Dr. José J. Rieta
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Bioengineering is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2700 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • signal processing
  • machine learning
  • deep learning
  • artificial intelligence
  • medical imaging
  • in silico modeling
  • big data
  • cardiac ablation
  • bioelectric modeling
  • electrophysiology

Published Papers (4 papers)

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Research

19 pages, 6327 KiB  
Article
Epicardial Pulsed Field Ablation of Ganglionated Plexi: Computational and Pre-Clinical Evaluation of a Bipolar Sub-Xiphoid Catheter for the Treatment of Atrial Fibrillation
by Barry O’Brien, John Reilly, Ken Coffey, Ana González-Suárez, Piotr Buchta, Piotr P. Buszman, Karolina Lukasik, Jason Tri, Martin van Zyl and Samuel Asirvatham
Bioengineering 2024, 11(1), 18; https://doi.org/10.3390/bioengineering11010018 - 24 Dec 2023
Cited by 1 | Viewed by 1014
Abstract
Epicardial pulsed field ablation (PFA) of ganglionated plexi (GPs) is being explored as a potential treatment for atrial fibrillation. Initial work using open-chest access with a monopolar ablation device has been completed. This study describes the early development work for a device that [...] Read more.
Epicardial pulsed field ablation (PFA) of ganglionated plexi (GPs) is being explored as a potential treatment for atrial fibrillation. Initial work using open-chest access with a monopolar ablation device has been completed. This study describes the early development work for a device that can be used with subxiphoid access and deliver bipolar ablation pulses. Electric field computational models have been used for the initial guidance on pulse parameters. An in vivo assessment of these ablation parameters has been performed in an open-chest canine study, while subxiphoid access and navigation of the device has been demonstrated in a porcine model. Results from this acute study have demonstrated the promising potential of this approach. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to the Diagnosis and Treatment of Cardiac Arrhythmias)
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22 pages, 1702 KiB  
Article
Machine-Learning-Based Prediction of 1-Year Arrhythmia Recurrence after Ventricular Tachycardia Ablation in Patients with Structural Heart Disease
by Ferenc Komlósi, Patrik Tóth, Gyula Bohus, Péter Vámosi, Márton Tokodi, Nándor Szegedi, Zoltán Salló, Katalin Piros, Péter Perge, István Osztheimer, Pál Ábrahám, Gábor Széplaki, Béla Merkely, László Gellér and Klaudia Vivien Nagy
Bioengineering 2023, 10(12), 1386; https://doi.org/10.3390/bioengineering10121386 - 01 Dec 2023
Viewed by 803
Abstract
Background: Ventricular tachycardia (VT) recurrence after catheter ablation remains a concern, emphasizing the need for precise risk assessment. We aimed to use machine learning (ML) to predict 1-month and 1-year VT recurrence following VT ablation. Methods: For 337 patients undergoing VT ablation, we [...] Read more.
Background: Ventricular tachycardia (VT) recurrence after catheter ablation remains a concern, emphasizing the need for precise risk assessment. We aimed to use machine learning (ML) to predict 1-month and 1-year VT recurrence following VT ablation. Methods: For 337 patients undergoing VT ablation, we collected 31 parameters including medical history, echocardiography, and procedural data. 17 relevant features were included in the ML-based feature selection, which yielded six and five optimal features for 1-month and 1-year recurrence, respectively. We trained several supervised machine learning models using 10-fold cross-validation for each endpoint. Results: We observed 1-month VT recurrence was observed in 60 (18%) cases and accurately predicted using our model with an area under the receiver operating curve (AUC) of 0.73. Input features used were hemodynamic instability, incessant VT, ICD shock, left ventricular ejection fraction, TAPSE, and non-inducibility of the clinical VT at the end of the procedure. A separate model was trained for 1-year VT recurrence (observed in 117 (35%) cases) with a mean AUC of 0.71. Selected features were hemodynamic instability, the number of inducible VT morphologies, left ventricular systolic diameter, mitral regurgitation, and ICD shock. For both endpoints, a random forest model displayed the highest performance. Conclusions: Our ML models effectively predict VT recurrence post-ablation, aiding in identifying high-risk patients and tailoring follow-up strategies. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to the Diagnosis and Treatment of Cardiac Arrhythmias)
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Graphical abstract

14 pages, 2827 KiB  
Article
Effects of Pulsed Radiofrequency Source on Cardiac Ablation
by Marcello Iasiello, Assunta Andreozzi, Nicola Bianco and Kambiz Vafai
Bioengineering 2023, 10(2), 227; https://doi.org/10.3390/bioengineering10020227 - 08 Feb 2023
Cited by 4 | Viewed by 1331
Abstract
Heart arrhythmia is caused by abnormal electrical conduction through the myocardium, which in some cases, can be treated with heat. One of the challenges is to reduce temperature peaks—by still guaranteeing an efficient treatment where desired—to avoid any healthy tissue damage or any [...] Read more.
Heart arrhythmia is caused by abnormal electrical conduction through the myocardium, which in some cases, can be treated with heat. One of the challenges is to reduce temperature peaks—by still guaranteeing an efficient treatment where desired—to avoid any healthy tissue damage or any electrical issues within the device employed. A solution might be employing pulsed heat, in which thermal dose is given to the tissue with a variation in time. In this work, pulsed heat is used to modulate induced temperature fields during radiofrequency cardiac ablation. A three-dimensional model of the myocardium, catheter and blood flow is developed. Porous media, heat conduction and Navier–Stokes equations are, respectively, employed for each of the investigated domains. For the electric field, solved via Laplace equation, it is assumed that the electrode is at a fixed voltage. Pulsed heating effects are considered with a cosine time-variable pulsed function for the fixed voltage by constraining the product between this variable and time. Different dimensionless frequencies are considered and applied for different blood flow velocity and sustained voltages. Results are presented for different pulsed conditions to establish if a reasonable ablation zone, known from the obtained temperature profiles, can be obtained without any undesired temperature peaks. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to the Diagnosis and Treatment of Cardiac Arrhythmias)
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9 pages, 3041 KiB  
Article
Pulsed Electric Field Ablation of Epicardial Autonomic Ganglia: Computer Analysis of Monopolar Electric Field across the Tissues Involved
by Ana González-Suárez, Barry O’Brien, Martin O’Halloran and Adnan Elahi
Bioengineering 2022, 9(12), 731; https://doi.org/10.3390/bioengineering9120731 - 27 Nov 2022
Cited by 5 | Viewed by 1357
Abstract
Background and objectives: Pulsed Electric Field (PEF) ablation has been proposed as a non-thermal energy to treat atrial fibrillation (AF) by epicardial ablation of ganglionated plexi (GP), which are embedded within epicardial fat. Our objective was to study the distribution of the electric [...] Read more.
Background and objectives: Pulsed Electric Field (PEF) ablation has been proposed as a non-thermal energy to treat atrial fibrillation (AF) by epicardial ablation of ganglionated plexi (GP), which are embedded within epicardial fat. Our objective was to study the distribution of the electric field through the involved tissues (fat, GPs, myocardium and blood) during epicardial PEF ablation. Methods: A two-dimensional model was built considering different tissue layers below the ablation device which consists of an irrigated electrode. The 1000 V/cm threshold was used to estimate the ‘PEF-zone’. Results: The PEF-zone was almost 100% circumscribed in the epicardial fat layer, with very little incidence in the myocardium. The presence of the saline on the epicardial fat causes the PEF-zone to spread laterally around the electrode from ~5 mm to ~15 mm, relatively independently of how embedded the electrode is in the saline layer. For a saline layer well spread over the tissue surface and an electrode fully embedded in the saline layer, the PEF-zone width decreases as the fat layer thickens: from ~15 mm for fat thickness of 1 and 2 mm, down to ~10 mm for fat thickness of 5 mm. The presence of a GP in the center of the fat layer hardly affects the size of the PEF-zone, but significantly alters the distribution of the electric field around the GP, resulting in progressively lower values than in the surrounding adipose tissue as the fat layer thickness increased. Conclusions: Our results suggest how some procedural (irrigation) and anatomical parameters (fat thicknesses and presence of GPs) could be relevant in terms of the size of the tissue area affected by pulsed field ablation. Full article
(This article belongs to the Special Issue Editorial Board Members’ Collection Series: Biomedical Engineering Research Applied to the Diagnosis and Treatment of Cardiac Arrhythmias)
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