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Biomedicines
Special Issues
Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine
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Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine

A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Biomedical Engineering and Materials".

Deadline for manuscript submissions: closed (31 December 2023) | Viewed by 5812

Special Issue Editors

Dr. Dimitrios A. Vrachatis

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Guest Editor
2nd Department of Cardiology, “Attikon” University Hospital, National and Kapodistrian University of Athens, Athens, Greece
Interests: clinical cardiology; interventional cardiology; heart; imaging; electrophysiology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Spyridon G. Deftereos

E-Mail Website
Guest Editor
2nd Department of Cardiology, “Attikon” University Hospital, National and Kapodistrian University of Athens, Athens, Greece
Interests: interventional cardiology; atrial fibrillation; catheter ablation; pacemakers; clinical cardiology
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Theodore G. Papaioannou

E-Mail Website
Guest Editor
1st Department of Cardiology, Hippokration Hospital. Medical School, National and Kapodistrian University of Athens, Athens, Greece
Interests: biomedical engineering; cardiovascular disease

Special Issue Information

Dear Colleagues,

Cardiovascular disease represents the most frequent cause of death in the Western world due to non-communicable entities. Nevertheless, it also represents a main cause of preventable morbidity, and thankfully, cardiovascular medicine is evolving rapidly today.

During the previous century, technological innovations led to advances both in the pharmaceutical armamentarium and interventional cardiology and electrophysiology which transformed clinical practice as we knew it. Intense clinical research since then has led to the evolution of new therapeutic molecules. Further, biomedical engineers in close collaboration with the industry and the academia have brought into practice irreplaceable tools. Structural interventional procedures including—but not restricted to—transcatheter heart valve interventions are a prominent example of this evolving transformation. The situation is similar in the field of interventional electrophysiology, with three-dimensional electro-anatomical mapping leading a true paradigm shift in the treatment of arrhythmias.

As in almost all socioeconomic fields, the 4th industrial revolution has also had a significant effect on healthcare. Applications of artificial intelligence utilizing machine and deep learning algorithms are already present in the field of medical research, covering a wide range of targets from disease diagnosis, staging and treatment to healthcare logistics.

The present Special Issue aims to explore pathophysiological, diagnostic, and treatment aspects of biomedical engineering and digital health in the field of cardiovascular medicine. We would be honored to have robust contributions from eminent experts on the field so as to update the scientific literature both with original research and review articles on this fascinating topic.

Dr. Dimitrios A. Vrachatis
Prof. Dr. Spyridon G. Deftereos
Prof. Dr. Theodore G. Papaioannou
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. Biomedicines 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 2600 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

  • biomedical engineering
  • artificial intelligence
  • cardiovascular
  • medical devices

Published Papers (4 papers)

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Research

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18 pages, 627 KiB  
Article
On the Use of Machine Learning Techniques and Non-Invasive Indicators for Classifying and Predicting Cardiac Disorders
by Raydonal Ospina, Adenice G. O. Ferreira, Hélio M. de Oliveira, Víctor Leiva and Cecilia Castro
Biomedicines 2023, 11(10), 2604; https://doi.org/10.3390/biomedicines11102604 - 22 Sep 2023
Cited by 2 | Viewed by 814
Abstract
This research aims to enhance the classification and prediction of ischemic heart diseases using machine learning techniques, with a focus on resource efficiency and clinical applicability. Specifically, we introduce novel non-invasive indicators known as Campello de Souza features, which require only a tensiometer [...] Read more.
This research aims to enhance the classification and prediction of ischemic heart diseases using machine learning techniques, with a focus on resource efficiency and clinical applicability. Specifically, we introduce novel non-invasive indicators known as Campello de Souza features, which require only a tensiometer and a clock for data collection. These features were evaluated using a comprehensive dataset of heart disease cases from a machine learning data repository. Our findings highlight the ability of machine learning algorithms to not only streamline diagnostic procedures but also reduce diagnostic errors and the dependency on extensive clinical testing. Three key features—mean arterial pressure, pulsatile blood pressure index, and resistance-compliance indicator—were found to significantly improve the accuracy of machine learning algorithms in binary heart disease classification. Logistic regression achieved the highest average accuracy among the examined classifiers when utilizing these features. While such novel indicators contribute substantially to the classification process, they should be integrated into a broader diagnostic framework that includes comprehensive patient evaluations and medical expertise. Therefore, the present study offers valuable insights for leveraging data science techniques in the diagnosis and management of cardiovascular diseases. Full article
(This article belongs to the Special Issue Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine)
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17 pages, 2735 KiB  
Article
Targeted Proteomic Analysis of Patients with Ascending Thoracic Aortic Aneurysm
by Aphrodite Daskalopoulou, Sotiria G. Giotaki, Konstantina Toli, Angeliki Minia, Vaia Pliaka, Leonidas G. Alexopoulos, Gerasimos Deftereos, Konstantinos Iliodromitis, Dimitrios Dimitroulis, Gerasimos Siasos, Christos Verikokos and Dimitrios Iliopoulos
Biomedicines 2023, 11(5), 1273; https://doi.org/10.3390/biomedicines11051273 - 25 Apr 2023
Cited by 1 | Viewed by 1402
Abstract
Background: There is a need for clinical markers to aid in the detection of individuals at risk of harboring an ascending thoracic aneurysm (ATAA) or developing one in the future. Objectives: To our knowledge, ATAA remains without a specific biomarker. This study aims [...] Read more.
Background: There is a need for clinical markers to aid in the detection of individuals at risk of harboring an ascending thoracic aneurysm (ATAA) or developing one in the future. Objectives: To our knowledge, ATAA remains without a specific biomarker. This study aims to identify potential biomarkers for ATAA using targeted proteomic analysis. Methods: In this study, 52 patients were divided into three groups depending on their ascending aorta diameter: 4.0–4.5 cm (N = 23), 4.6–5.0 cm (N = 20), and >5.0 cm (N = 9). A total of 30 controls were in-house populations ethnically matched to cases without known or visible ATAA-related symptoms and with no ATAA familial history. Before the debut of our study, all patients provided medical history and underwent physical examination. Diagnosis was confirmed by echocardiography and angio-computed tomography (CT) scans. Targeted-proteomic analysis was conducted to identify possible biomarkers for the diagnosis of ATAA. Results: A Kruskal–Wallis test revealed that C-C motif chemokine ligand 5 (CCL5), defensin beta 1 (HBD1), intracellular adhesion molecule-1 (ICAM1), interleukin-8 (IL8), tumor necrosis factor alpha (TNFα) and transforming growth factor-beta 1 (TGFB1) expressions are significantly increased in ATAA patients in comparison to control subjects with physiological aorta diameter (p < 0.0001). The receiver-operating characteristic analysis showed that the area under the curve values for CCL5 (0.84), HBD1 (0.83) and ICAM1 (0.83) were superior to that of the other analyzed proteins. Conclusions: CCL5, HBD1 and ICAM1 are very promising biomarkers with satisfying sensitivity and specificity that could be helpful in stratifying risk for the development of ATAA. These biomarkers may assist in the diagnosis and follow-up of patients at risk of developing ATAA. This retrospective study is very encouraging; however, further in-depth studies may be worthwhile to investigate the role of these biomarkers in the pathogenesis of ATAA. Full article
(This article belongs to the Special Issue Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine)
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14 pages, 10425 KiB  
Article
Bioresorbable Magnesium-Based Stent: Real-World Clinical Experience and Feasibility of Follow-Up by Coronary Computed Tomography: A New Window to Look at New Scaffolds
by Chadi Ghafari, Nicolas Brassart, Philippe Delmotte, Philippe Brunner, Sarah Dghoughi and Stéphane Carlier
Biomedicines 2023, 11(4), 1150; https://doi.org/10.3390/biomedicines11041150 - 11 Apr 2023
Cited by 1 | Viewed by 1466
Abstract
(1) Background: The diagnostic accuracy of coronary computed tomography angiography (CCTA) for coronary artery disease (CAD) has greatly improved so CCTA represents a transition in the care of patients suffering from CAD. Magnesium-based bioresorbable stents (Mg-BRS) secure acute percutaneous coronary intervention (PCI) results [...] Read more.
(1) Background: The diagnostic accuracy of coronary computed tomography angiography (CCTA) for coronary artery disease (CAD) has greatly improved so CCTA represents a transition in the care of patients suffering from CAD. Magnesium-based bioresorbable stents (Mg-BRS) secure acute percutaneous coronary intervention (PCI) results without leaving, in the long term, a metallic caging effect. The purpose of this real-world study was to assess clinical and CCTA medium- and long-term follow-up of all our patients with implanted Mg-BRS. (2) Methods: The patency of 52 Mg-BRS implanted in 44 patients with de novo lesions (24 of which had acute coronary syndrome (ACS)) was evaluated by CCTA and compared to quantitative coronary angiography (QCA) post-implantation. (3) Results: ten events including four deaths occurred during a median follow-up of 48 months. CCTA was interpretable and in-stent measurements were successful at follow-up without being hindered by the stent strut’s “blooming effect”. Minimal in-stent diameters on CCTA were found to be 1.03 ± 0.60 mm smaller than the expected diameter after post-dilation on implantation (p < 0.05), a difference not found in comparing CCTA and QCA. (4) Conclusions: CCTA follow-up of implanted Mg-BRS is fully interpretable and we confirm the long-term Mg-BRS safety profile. Full article
(This article belongs to the Special Issue Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine)
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Review

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16 pages, 306 KiB  
Review
Efficacy, Safety and Feasibility of Superior Vena Cava Isolation in Patients Undergoing Atrial Fibrillation Catheter Ablation: An Up-to-Date Review
by Dimitrios A. Vrachatis, Konstantinos A. Papathanasiou, Charalampos Kossyvakis, Sotiria G. Giotaki, Gerasimos Deftereos, Maria S. Kousta, Konstantinos E. Iliodromitis, Harilaos Bogossian, Dimitrios Avramides, George Giannopoulos, Vaia Lambadiari, Gerasimos Siasos, Theodore G. Papaioannou and Spyridon Deftereos
Biomedicines 2023, 11(4), 1022; https://doi.org/10.3390/biomedicines11041022 - 27 Mar 2023
Cited by 2 | Viewed by 1542
Abstract
Pulmonary vein isolation (PVI) is the cornerstone in atrial fibrillation (AF) ablation; yet, the role of arrhythmogenic superior vena cava (SVC) is increasingly recognized and different ablation strategies have been employed in this context. SVC can act as a trigger or perpetuator of [...] Read more.
Pulmonary vein isolation (PVI) is the cornerstone in atrial fibrillation (AF) ablation; yet, the role of arrhythmogenic superior vena cava (SVC) is increasingly recognized and different ablation strategies have been employed in this context. SVC can act as a trigger or perpetuator of AF, and its significance might be more pronounced in patients undergoing repeated ablation. Several cohorts have examined efficacy, safety and feasibility of SVC isolation (SVCI) among AF patients. The majority of these studies explored as-needed SVCI during index PVI, and only a minority of them included repeated ablation subjects and non-radiofrequency energy sources. Studies of heterogeneous design and intent have explored both empiric and as-needed SVCI on top of PVI and reported inconclusive results. These studies have largely failed to demonstrate any clinical benefit in terms of arrhythmia recurrence, although safety and feasibility are undisputable. Mixed population demographics, small number of enrollees and short follow-up are the main limitations. Procedural and safety data are comparable between empiric SVCI and as-needed SVCI, and some studies suggested that empiric SVCI might be associated with reduced AF recurrences in paroxysmal AF patients. Currently, no study has compared different ablation energy sources in the setting of SVCI, and no randomized study has addressed as-needed SVCI on top of PVI. Furthermore, data regarding cryoablation are still in their infancy, and regarding SVCI in patients with cardiac devices more safety and feasibility data are needed. PVI non-responders, patients undergoing repeated ablation and patients with long SVC sleeves could be potential candidates for SVCI, especially via an empiric approach. Although many technical aspects remain unsettled, the major question to answer is which clinical phenotype of AF patients might benefit from SVCI? Full article
(This article belongs to the Special Issue Cardiovascular Care in Transition: From Biomedical Engineering to Digital Medicine)
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