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Vuong TNAM, Bartolf-Kopp M, Andelovic K, Jungst T, Farbehi N, Wise SG, Hayward C, Stevens MC, Rnjak-Kovacina J. Integrating Computational and Biological Hemodynamic Approaches to Improve Modeling of Atherosclerotic Arteries. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2307627. [PMID: 38704690 DOI: 10.1002/advs.202307627] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Revised: 03/12/2024] [Indexed: 05/07/2024]
Abstract
Atherosclerosis is the primary cause of cardiovascular disease, resulting in mortality, elevated healthcare costs, diminished productivity, and reduced quality of life for individuals and their communities. This is exacerbated by the limited understanding of its underlying causes and limitations in current therapeutic interventions, highlighting the need for sophisticated models of atherosclerosis. This review critically evaluates the computational and biological models of atherosclerosis, focusing on the study of hemodynamics in atherosclerotic coronary arteries. Computational models account for the geometrical complexities and hemodynamics of the blood vessels and stenoses, but they fail to capture the complex biological processes involved in atherosclerosis. Different in vitro and in vivo biological models can capture aspects of the biological complexity of healthy and stenosed vessels, but rarely mimic the human anatomy and physiological hemodynamics, and require significantly more time, cost, and resources. Therefore, emerging strategies are examined that integrate computational and biological models, and the potential of advances in imaging, biofabrication, and machine learning is explored in developing more effective models of atherosclerosis.
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Affiliation(s)
| | - Michael Bartolf-Kopp
- Department of Functional Materials in Medicine and Dentistry, Institute of Functional Materials and Biofabrication (IFB), KeyLab Polymers for Medicine of the Bavarian Polymer Institute (BPI), University of Würzburg, Pleicherwall 2, 97070, Würzburg, Germany
| | - Kristina Andelovic
- Department of Functional Materials in Medicine and Dentistry, Institute of Functional Materials and Biofabrication (IFB), KeyLab Polymers for Medicine of the Bavarian Polymer Institute (BPI), University of Würzburg, Pleicherwall 2, 97070, Würzburg, Germany
| | - Tomasz Jungst
- Department of Functional Materials in Medicine and Dentistry, Institute of Functional Materials and Biofabrication (IFB), KeyLab Polymers for Medicine of the Bavarian Polymer Institute (BPI), University of Würzburg, Pleicherwall 2, 97070, Würzburg, Germany
- Department of Orthopedics, Regenerative Medicine Center Utrecht, University Medical Center Utrecht, Utrecht, 3584, Netherlands
| | - Nona Farbehi
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, 2052, Australia
- Tyree Institute of Health Engineering, University of New South Wales, Sydney, NSW, 2052, Australia
- Garvan Weizmann Center for Cellular Genomics, Garvan Institute of Medical Research, Sydney, NSW, 2010, Australia
| | - Steven G Wise
- School of Medical Sciences, University of Sydney, Sydney, NSW, 2006, Australia
| | - Christopher Hayward
- St Vincent's Hospital, Sydney, Victor Chang Cardiac Research Institute, Sydney, 2010, Australia
| | - Michael Charles Stevens
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, 2052, Australia
| | - Jelena Rnjak-Kovacina
- Graduate School of Biomedical Engineering, University of New South Wales, Sydney, 2052, Australia
- Tyree Institute of Health Engineering, University of New South Wales, Sydney, NSW, 2052, Australia
- Australian Centre for NanoMedicine (ACN), University of New South Wales, Sydney, NSW, 2052, Australia
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Gazo Hanna E, Younes K, Roufayel R, Khazaal M, Fajloun Z. Engineering innovations in medicine and biology: Revolutionizing patient care through mechanical solutions. Heliyon 2024; 10:e26154. [PMID: 38390063 PMCID: PMC10882044 DOI: 10.1016/j.heliyon.2024.e26154] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2023] [Revised: 01/24/2024] [Accepted: 02/08/2024] [Indexed: 02/24/2024] Open
Abstract
The overlap between mechanical engineering and medicine is expanding more and more over the years. Engineers are now using their expertise to design and create functional biomaterials and are continually collaborating with physicians to improve patient health. In this review, we explore the state of scientific knowledge in the areas of biomaterials, biomechanics, nanomechanics, and computational fluid dynamics (CFD) in relation to the pharmaceutical and medical industry. Focusing on current research and breakthroughs, we provide an overview of how these fields are being used to create new technologies for medical treatments of human patients. Barriers and constraints in these fields, as well as ways to overcome them, are also described in this review. Finally, the potential for future advances in biomaterials to fundamentally change the current approach to medicine and biology is also discussed.
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Affiliation(s)
- Eddie Gazo Hanna
- College of Engineering and Technology, American University of the Middle East, Egaila, 54200, Kuwait
| | - Khaled Younes
- College of Engineering and Technology, American University of the Middle East, Egaila, 54200, Kuwait
| | - Rabih Roufayel
- College of Engineering and Technology, American University of the Middle East, Egaila, 54200, Kuwait
| | - Mickael Khazaal
- École Supérieure des Techniques Aéronautiques et de Construction Automobile, ISAE-ESTACA, France
| | - Ziad Fajloun
- Faculty of Sciences 3, Department of Biology, Lebanese University, Campus Michel Slayman Ras Maska, 1352, Tripoli, Lebanon
- Laboratory of Applied Biotechnology (LBA3B), Azm Center for Research in Biotechnology and Its Applications, EDST, Lebanese University, 1300, Tripoli, Lebanon
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Chiastra C, Zuin M, Rigatelli G, D’Ascenzo F, De Ferrari GM, Collet C, Chatzizisis YS, Gallo D, Morbiducci U. Computational fluid dynamics as supporting technology for coronary artery disease diagnosis and treatment: an international survey. Front Cardiovasc Med 2023; 10:1216796. [PMID: 37719972 PMCID: PMC10501454 DOI: 10.3389/fcvm.2023.1216796] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/04/2023] [Accepted: 08/14/2023] [Indexed: 09/19/2023] Open
Abstract
Background Computational fluid dynamics (CFD) is emerging as an effective technology able to improve procedural outcomes and enhance clinical decision-making in patients with coronary artery disease (CAD). The present study aims to assess the state of knowledge, use and clinical acceptability of CFD in the diagnosis and treatment of CAD. Methods We realized a 20-questions international, anonymous, cross-sectional survey to cardiologists to test their knowledge and confidence on CFD as a technology applied to patients suffering from CAD. Responses were recorded between May 18, 2022, and June 12, 2022. Results A total of 466 interventional cardiologists (mean age 48.4 ± 8.3 years, males 362), from 42 different countries completed the survey, for a response rate of 45.9%. Of these, 66.6% declared to be familiar with the term CFD, especially for optimization of existing interventional techniques (16.1%) and assessment of hemodynamic quantities related with CAD (13.7%). About 30% of respondents correctly answered to the questions exploring their knowledge on the pathophysiological role of some CFD-derived quantities such as wall shear stress and helical flow in coronary arteries. Among respondents, 85.9% would consider patient-specific CFD-based analysis in daily interventional practice while 94.2% declared to be interested in receiving a brief foundation course on the basic CFD principles. Finally, 87.7% of respondents declared to be interested in a cath-lab software able to conduct affordable CFD-based analyses at the point-of-care. Conclusions Interventional cardiologists reported to be profoundly interested in adopting CFD simulations as a technology supporting decision making in the treatment of CAD in daily practice.
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Affiliation(s)
- Claudio Chiastra
- PoliToMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Marco Zuin
- Department of Translational Medicine, University of Ferrara, Ferrara, Italy
| | - Gianluca Rigatelli
- Interventional Cardiology Unit, Department of Cardiology, Madre Teresa Hospital, Padova, Italy
| | - Fabrizio D’Ascenzo
- Division of Cardiology, Department of Medical Sciences, Città Della Salute e Della Scienza Hospital, Turin, Italy
| | - Gaetano Maria De Ferrari
- Division of Cardiology, Department of Medical Sciences, Città Della Salute e Della Scienza Hospital, Turin, Italy
| | | | - Yiannis S. Chatzizisis
- Division of Cardiovascular Medicine, Miller School of Medicine, University of Miami, Miami, FL, United States
| | - Diego Gallo
- PoliToMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
| | - Umberto Morbiducci
- PoliToMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
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Siogkas PK, Pleouras DS, Tsakanikas VD, Mantzaris MD, Potsika VT, Sakellarios A, Charalampopoulos G, Galyfos G, Sigala F, Fotiadis DI. Enhancing risk prediction capabilities in patients with carotid artery disease using a 2-level computational approach. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38082959 DOI: 10.1109/embc40787.2023.10340085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
One of the main causes of death worldwide is carotid artery disease, which causes increasing arterial stenosis and may induce a stroke. To address this problem, the scientific community aims to improve our understanding of the underlying atherosclerotic mechanisms, as well as to make it possible to forecast the progression of atherosclerosis. Additionally, over the past several years, developments in the field of cardiovascular modeling have made it possible to create precise three-dimensional models of patient-specific main carotid arteries. The aforementioned 3D models are then implemented by computational models to forecast either the progression of atherosclerotic plaque or several flow-related metrics which are correlated to risk evaluation. A precise representation of both the blood flow and the fundamental atherosclerotic process within the arterial wall is made possible by computational models, therefore, allowing for the prediction of future lumen stenoses, plaque areas and risk prediction. This work presents an attempt to integrate the outcomes of a novel plaque growth model with advanced blood flow dynamics where the deformed luminal shape derived from the plaque growth model is compared to the actual patient-specific luminal model in terms of several hemodynamic metrics, to identify the prediction accuracy of the aforementioned model. Pressure drop ratios had a mean difference of <3%, whereas OSI-derived metrics were identical in 2/3 cases.Clinical Relevance-This establishes the accuracy of our plaque growth model in predicting the arterial geometry after the desired timeline.
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Pleouras DS, Siogkas PK, Tsakanikas VD, Mantzaris MD, Potsika VT, Sakellarios A, Sigala F, Fotiadis DI. Accurate adventitia reconstruction; significant or not in atherosclerotic plaque growth simulationsƒ A comparative study. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083292 DOI: 10.1109/embc40787.2023.10340557] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
A reform in the diagnosis and treatment process is urgently required as carotid artery disease remains a leading cause of death in the world. To this purpose, all computational techniques are now being applied to enhancing the most cutting-edge diagnosis techniques. Computational modeling of plaque generation and evolution is being refined over the past years to forecast the atherosclerotic progression and the corresponding risk in patient-specific carotid arteries. A prerequisite to their implementation is the reconstruction of the precise three-dimensional models of patient-specific main carotid arteries. Even with the most sophisticated algorithms, accurate reconstruction of the arterial vessel is frequently difficult. Furthermore, there are several works of plaque growth modeling that ignore the reconstruction of the artery's outer layer in favor of a virtual one. In this paper, we investigate the importance of an accurate adventitia layer in plaque growth modeling. This is done as a comparative study by implementing a novel plaque growth model in two reconstructed carotid arterial segments using either their realistic or virtual adventitia layer as input. The results indicate that accurate adventitia reconstruction is of minor importance regarding species distributions and plaque growth in carotid segments, which initially did not contain any plaque regions.Clinical Relevance- The findings of this comparative study emphasize the importance of precise adventitia geometry in plaque growth modeling. As a result, this work sets a higher standard for publishing new plaque growth models.
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6
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Siogkas PK, Pleouras DS, Tsakanikas VD, Potsika VT, Tsiouris KM, Sakellarios A, Karamouzi E, Lagiou F, Charalampopoulos G, Galyfos G, Sigala F, Koncar I, Fotiadis DI. A Machine Learning Model for the prediction of the progression of carotid arterial stenoses. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2023; 2023:1-4. [PMID: 38083544 DOI: 10.1109/embc40787.2023.10340383] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/18/2023]
Abstract
Atherosclerotic carotid plaque development results in a steady narrowing of the artery lumen, which may eventually trigger catastrophic plaque rupture leading to thromboembolism and stroke. The primary cause of ischemic stroke in the EU is carotid artery disease, which increases the demand for tools for risk stratification and patient management in carotid artery disease. Additionally, advancements in cardiovascular modeling over the past few years have made it possible to build accurate three-dimensional models of patient-specific primary carotid arteries. Computational models then incorporate the aforementioned 3D models to estimate either the development of atherosclerotic plaque or a number of flow-related parameters that are linked to risk assessment. This work presents an attempt to provide a carotid artery stenosis prognostic model, utilizing non-imaging and imaging data, as well as simulated hemodynamic data. The overall methodology was trained and tested on a dataset of 41 cases with 23 carotid arteries with stable stenosis and 18 carotids with increasing stenosis degree. The highest accuracy of 71% was achieved using a neural network classifier. The novel aspect of our work is the definition of the problem that is solved, as well as the amount of simulated data that are used as input for the prognostic model.Clinical Relevance-A prognostic model for the prediction of the trajectory of carotid artery atherosclerosis is proposed, which can support physicians in critical treatment decisions.
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An All-in-One Tool for 2D Atherosclerotic Disease Assessment and 3D Coronary Artery Reconstruction. J Cardiovasc Dev Dis 2023; 10:jcdd10030130. [PMID: 36975894 PMCID: PMC10056488 DOI: 10.3390/jcdd10030130] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/24/2023] [Revised: 03/10/2023] [Accepted: 03/17/2023] [Indexed: 03/22/2023] Open
Abstract
Diagnosis of coronary artery disease is mainly based on invasive imaging modalities such as X-ray angiography, intravascular ultrasound (IVUS) and optical coherence tomography (OCT). Computed tomography coronary angiography (CTCA) is also used as a non-invasive imaging alternative. In this work, we present a novel and unique tool for 3D coronary artery reconstruction and plaque characterization using the abovementioned imaging modalities or their combination. In particular, image processing and deep learning algorithms were employed and validated for the lumen and adventitia borders and plaque characterization at the IVUS and OCT frames. Strut detection is also achieved from the OCT images. Quantitative analysis of the X-ray angiography enables the 3D reconstruction of the lumen geometry and arterial centerline extraction. The fusion of the generated centerline with the results of the OCT or IVUS analysis enables hybrid coronary artery 3D reconstruction, including the plaques and the stent geometry. CTCA image processing using a 3D level set approach allows the reconstruction of the coronary arterial tree, the calcified and non-calcified plaques as well as the detection of the stent location. The modules of the tool were evaluated for efficiency with over 90% agreement of the 3D models with the manual annotations, while a usability assessment using external evaluators demonstrated high usability resulting in a mean System Usability Scale (SUS) score equal to 0.89, classifying the tool as “excellent”.
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Mazumder O, Gupta S, Roy D, Khandelwal S, Sinha A. Numerical Analysis on Effect of Coronary Supply-Demand Equilibrium on Varying Coronary Blockage and Stress Conditions. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:3972-3976. [PMID: 36086122 DOI: 10.1109/embc48229.2022.9871116] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
In this paper, we present a computational fluid dynamic (CFD) analysis to capture the effect of physical stress and stenosis severity in coronary arteries leading to changes in coronary supply demand oxygen equilibrium. We propose a coupled Od-3d coronary vessel model to predict the variation in flow dynamics of coronary as well as arterial system, modeled using an in-silico model replicating cardiovascular hemodynamics. CFD simulation were solved using subject specific CT scan for coronary and arterial flow and pressure along with metrics related to arterial wall shear stress. Simulations were performed for three heart rates (75, 90 and 120 bpm) and four stenosis states representing different stages of Coronary artery disease (CAD) namely healthy, 50%, 75%, 90% blockage in left anterior descending artery (LAD). Myocardial oxygen supply demand equilibrium were calculated for each cases using hemodynamic surrogate markers naming Diastolic pressure time index for supply and Tension time index for demand. The proposed 0d-3d coupled hemodynamic model of the coronary vessel bed along with supply-demand equilibrium estimated for different stress level and stenosis severity may provide useful insights on the dynamics of CAD manifestation and predict vulnerable regions in coronary bed for early screening and interventions.
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Pleouras DS, Mantzaris MD, Siogkas PK, Tsakanikas VD, Potsika VT, Sakellarios A, Tsompou P, Sigala F, Fotiadis DI. Prediction of the atherosclerotic plaque development in carotid arteries; the effect of T-cells. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2022; 2022:1590-1593. [PMID: 36085734 DOI: 10.1109/embc48229.2022.9871632] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/15/2023]
Abstract
The carotid artery disease is one of the leading causes of mortality worldwide, as it leads to the progressive arterial stenosis that may result to stroke. To address this issue, the scientific community is attempting not only to enrich our knowledge on the underlying atherosclerotic mechanisms, but also to enable the prediction of the atherosclerotic progression. This study investigates the role of T-cells in the atherosclerotic plaque growth process through the implementation of a computational model in realistic geometries of carotid arteries. T-cells mediate in the inflammatory process by secreting interferon-y that enhances the activation of macrophages. In this analysis, we used 5 realistic human carotid arterial segments as input to the model. In particular, magnetic resonance imaging data, as well as, clinical data were collected from the patients at two time points. Using the baseline data, plaque growth was predicted and correlated to the follow-up arterial geometries. The results exhibited a very good agreement between them, presenting a high coefficient of determination R2=0.64.
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Sakellarios AI, Siogkas P, Kigka V, Tsompou P, Pleouras D, Kyriakidis S, Karanasiou G, Pelosi G, Nikopoulos S, Naka KK, Rocchiccioli S, Michalis LK, Fotiadis DI. Error Propagation in the Simulation of Atherosclerotic Plaque Growth and the Prediction of Atherosclerotic Disease Progression. Diagnostics (Basel) 2021; 11:diagnostics11122306. [PMID: 34943545 PMCID: PMC8699876 DOI: 10.3390/diagnostics11122306] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2021] [Revised: 11/23/2021] [Accepted: 12/06/2021] [Indexed: 11/16/2022] Open
Abstract
Assessments of coronary artery disease can be achieved using non-invasive computed tomography coronary angiography (CTCA). CTCA can be further used for the 3D reconstruction of the coronary arteries and the development of computational models. However, image acquisition and arterial reconstruction introduce an error which can be propagated, affecting the computational results and the accuracy of diagnostic and prognostic models. In this work, we investigate the effect of an imaging error, propagated to a diagnostic index calculated using computational modelling of blood flow and then to prognostic models based on plaque growth modelling or binary logistic predictive modelling. The analysis was performed utilizing data from 20 patients collected at two time points with interscan period of six years. The collected data includes clinical and risk factors, biological and biohumoral data, and CTCA imaging. The results demonstrated that the error propagated and may have significantly affected some of the final outcomes. The calculated propagated error seemed to be minor for shear stress, but was major for some variables of the plaque growth model. In parallel, in the current analysis SmartFFR was not considerably affected, with the limitation of only one case located into the gray zone.
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Affiliation(s)
- Antonis I. Sakellarios
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
- Correspondence: ; Tel.: +30-265-100-7837
| | - Panagiotis Siogkas
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Vassiliki Kigka
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Panagiota Tsompou
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Dimitrios Pleouras
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Savvas Kyriakidis
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
| | - Georgia Karanasiou
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
| | - Gualtiero Pelosi
- Institute of Clinical Physiology, National Research Council, 56124 Pisa, Italy; (G.P.); (S.R.)
| | - Sotirios Nikopoulos
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (S.N.); (K.K.N.); (L.K.M.)
| | - Katerina K. Naka
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (S.N.); (K.K.N.); (L.K.M.)
| | - Silvia Rocchiccioli
- Institute of Clinical Physiology, National Research Council, 56124 Pisa, Italy; (G.P.); (S.R.)
| | - Lampros K. Michalis
- Department of Cardiology, Medical School, University of Ioannina, 45110 Ioannina, Greece; (S.N.); (K.K.N.); (L.K.M.)
| | - Dimitrios I. Fotiadis
- Department of Biomedical Research, Institute of Molecular Biology and Biotechnology—FORTH, University Campus of Ioannina, 45110 Ioannina, Greece; (P.S.); (V.K.); (P.T.); (S.K.); (G.K.); (D.I.F.)
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and Engineering, University of Ioannina, 45110 Ioannina, Greece;
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Corti A, Colombo M, Migliavacca F, Rodriguez Matas JF, Casarin S, Chiastra C. Multiscale Computational Modeling of Vascular Adaptation: A Systems Biology Approach Using Agent-Based Models. Front Bioeng Biotechnol 2021; 9:744560. [PMID: 34796166 PMCID: PMC8593007 DOI: 10.3389/fbioe.2021.744560] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/20/2021] [Accepted: 10/04/2021] [Indexed: 12/20/2022] Open
Abstract
The widespread incidence of cardiovascular diseases and associated mortality and morbidity, along with the advent of powerful computational resources, have fostered an extensive research in computational modeling of vascular pathophysiology field and promoted in-silico models as a support for biomedical research. Given the multiscale nature of biological systems, the integration of phenomena at different spatial and temporal scales has emerged to be essential in capturing mechanobiological mechanisms underlying vascular adaptation processes. In this regard, agent-based models have demonstrated to successfully embed the systems biology principles and capture the emergent behavior of cellular systems under different pathophysiological conditions. Furthermore, through their modular structure, agent-based models are suitable to be integrated with continuum-based models within a multiscale framework that can link the molecular pathways to the cell and tissue levels. This can allow improving existing therapies and/or developing new therapeutic strategies. The present review examines the multiscale computational frameworks of vascular adaptation with an emphasis on the integration of agent-based approaches with continuum models to describe vascular pathophysiology in a systems biology perspective. The state-of-the-art highlights the current gaps and limitations in the field, thus shedding light on new areas to be explored that may become the future research focus. The inclusion of molecular intracellular pathways (e.g., genomics or proteomics) within the multiscale agent-based modeling frameworks will certainly provide a great contribution to the promising personalized medicine. Efforts will be also needed to address the challenges encountered for the verification, uncertainty quantification, calibration and validation of these multiscale frameworks.
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Affiliation(s)
- Anna Corti
- Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Monika Colombo
- Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Milan, Italy.,Institute for Chemical and Bioengineering, Department of Chemistry and Applied Biosciences, ETH Zürich, Switzerland
| | - Francesco Migliavacca
- Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Jose Felix Rodriguez Matas
- Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Milan, Italy
| | - Stefano Casarin
- Department of Surgery, Houston Methodist Hospital, Houston, TX, United States.,Center for Computational Surgery, Houston Methodist Research Institute, Houston, TX, United States.,Houston Methodist Academic Institute, Houston, TX, United States
| | - Claudio Chiastra
- Laboratory of Biological Structure Mechanics (LaBS), Department of Chemistry, Materials and Chemical Engineering "Giulio Natta", Politecnico di Milano, Milan, Italy.,PoliToMed Lab, Department of Mechanical and Aerospace Engineering, Politecnico di Torino, Turin, Italy
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12
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Mantzaris MD, Siogkas PK, Tsakanikas VD, Potsika VT, Pleouras DS, Sakellarios AI, Karagiannis G, Galyfos G, Sigala F, Liasis N, Jovanovic M, Koncar IB, Kallmayer M, Fotiadis DI. Computational modeling of atherosclerotic plaque progression in carotid lesions with moderate degree of stenosis . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:4209-4212. [PMID: 34892152 DOI: 10.1109/embc46164.2021.9630376] [Citation(s) in RCA: 4] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
Carotid atherosclerotic plaque growth leads to the progressive luminal stenosis of the vessel, which may erode or rupture causing thromboembolism and cerebral infarction, manifested as stroke. Carotid atherosclerosis is considered the major cause of ischemic stroke in Europe and thus new imaging-based computational tools that can improve risk stratification and management of carotid artery disease patients are needed. In this work, we present a new computational approach for modeling atherosclerotic plaque progression in real patient-carotid lesions, with moderate to severe degree of stenosis (>50%). The model incorporates for the first time, the baseline 3D geometry of the plaque tissue components (e.g. Lipid Core) identified by MR imaging, in which the major biological processes of atherosclerosis are simulated in time. The simulated plaque tissue production results in the inward remodeling of the vessel wall promoting luminal stenosis which in turn predicts the region of the actual stenosis progression observed at the follow-up visit. The model aims to support clinical decision making, by identifying regions prone to plaque formation, predict carotid stenosis and plaque burden progression, and provide advice on the optimal time for patient follow-up screening.
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Sakellarios AI, Tsompou P, Kigka V, Karanasiou G, Tsarapatsani K, Kyriakidis S, Karanasiou G, Siogkas P, Nikopoulos S, Rocchiccioli S, Pelosi G, Michalis LK, Fotiadis DI. A proof-of-concept study for the prediction of the de-novo atherosclerotic plaque development using finite elements . ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:4354-4357. [PMID: 34892184 DOI: 10.1109/embc46164.2021.9629792] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
The type of the atherosclerotic plaque has significant clinical meaning since plaque vulnerability depends on its type. In this work, we present a computational approach which predicts the development of new plaques in coronary arteries. More specifically, we employ a multi-level model which simulates the blood fluid dynamics, the lipoprotein transport and their accumulation in the arterial wall and the triggering of inflammation using convection-diffusion-reaction equations and in the final level, we estimate the plaque volume which causes the arterial wall thickening. The novelty of this work relies on the conceptual approach that using the information from 94 patients with computed tomography coronary angiography (CTCA) imaging at two time points we identify the correlation of the computational results with the real plaque components detected in CTCA. In the next step, we use these correlations to generate two types of de-novo plaques: calcified and non-calcified. Evaluation of the model's performance is achieved using eleven patients, who present de-novo plaques at the follow-up imaging. The results demonstrate that the computationally generated plaques are associated significantly with the real plaques indicating that the proposed approach could be used for the prediction of specific plaque type formation.
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Pleouras DS, Karanasiou GS, Loukas VS, Semertzioglou A, Moulas AN, Fotiadis DI. Investigation of the drug release time from the biodegrading coating of an everolimus eluting stent. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2021; 2021:1698-1701. [PMID: 34891613 DOI: 10.1109/embc46164.2021.9629813] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/14/2023]
Abstract
This case-study examines the release time of the everolimus drug from an experimental biodegrading coating of a Rontis corp. drug eluting stent (DES). The controlled drug release is achieved by the degradation of the coating, which consists of a mixture of polylactic co-glycolic acid (PLGA) and everolimus (55:45). In our analysis, we used the outcome of another study, which contains the geometry of an in-silico deployed Rontis corp. stent in a 3D reconstructed coney arterial segment. Using this geometry as input, the everolimus release was simulated using a computational model that includes: i) modeling of the blood flow dynamics, ii) modeling of PLGA degradation, and iii) modeling of the everolimus advection and diffusion towards both the lumen and the arterial wall. The results show the rapid release of everolimus. This is justified due to the high porosity of the coating, which is caused by the initial high concentration of everolimus in the coating.Clinical Relevance - The methodology presented in this work is an additional step towards predicting accurately drug release from DES. Also, the results of our work prove that high drug concentration in the coating causes its rapid release, which could be used as input in the design of new DES.
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Cai Y, Li Z. Mathematical modeling of plaque progression and associated microenvironment: How far from predicting the fate of atherosclerosis? COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2021; 211:106435. [PMID: 34619601 DOI: 10.1016/j.cmpb.2021.106435] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/09/2021] [Accepted: 09/16/2021] [Indexed: 06/13/2023]
Abstract
Mathematical modeling contributes to pathophysiological research of atherosclerosis by helping to elucidate mechanisms and by providing quantitative predictions that can be validated. In turn, the complexity of atherosclerosis is well suited to quantitative approaches as it provides challenges and opportunities for new developments of modeling. In this review, we summarize the current 'state of the art' on the mathematical modeling of the effects of biomechanical factors and microenvironmental factors on the plaque progression, and its potential help in prediction of plaque development. We begin with models that describe the biomechanical environment inside and outside the plaque and its influence on its growth and rupture. We then discuss mathematical models that describe the dynamic evolution of plaque microenvironmental factors, such as lipid deposition, inflammation, smooth muscle cells migration and intraplaque hemorrhage, followed by studies on plaque growth and progression using these modelling approaches. Moreover, we present several key questions for future research. Mathematical models can complement experimental and clinical studies, but also challenge current paradigms, redefine our understanding of mechanisms driving plaque vulnerability and propose future potential direction in therapy for cardiovascular disease.
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Affiliation(s)
- Yan Cai
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China.
| | - Zhiyong Li
- School of Biological Sciences and Medical Engineering, Southeast University, Nanjing 210096, China; School of Mechanical, Medical and Process Engineering, Queensland University of Technology, Brisbane, QLD 4001, Australia
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Liu H, Wingert A, Wang X, Zhang J, Sun J, Chen F, Khalid SG, Gong Y, Xia L, Jiang J, Wang J, Zheng D. Consistency in Geometry Among Coronary Atherosclerotic Plaques Extracted From Computed Tomography Angiography. Front Physiol 2021; 12:715265. [PMID: 34712147 PMCID: PMC8546263 DOI: 10.3389/fphys.2021.715265] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2021] [Accepted: 09/03/2021] [Indexed: 11/25/2022] Open
Abstract
Background: The three-dimensional (3D) geometry of coronary atherosclerotic plaques is associated with plaque growth and the occurrence of coronary artery disease. However, there is a lack of studies on the 3D geometric properties of coronary plaques. We aim to investigate if coronary plaques of different sizes are consistent in geometric properties. Methods: Nineteen cases with symptomatic stenosis caused by atherosclerotic plaques in the left coronary artery were included. Based on attenuation values on computed tomography angiography images, coronary atherosclerotic plaques and calcifications were identified, 3D reconstructed, and manually revised. Multidimensional geometric parameters were measured on the 3D models of plaques and calcifications. Linear and non-linear (i.e., power function) fittings were used to investigate the relationship between multidimensional geometric parameters (length, surface area, volume, etc.). Pearson correlation coefficient (r), R-squared, and p-values were used to evaluate the significance of the relationship. The analysis was performed based on cases and plaques, respectively. Significant linear relationship was defined as R-squared > 0.25 and p < 0.05. Results: In total, 49 atherosclerotic plaques and 56 calcifications were extracted. In the case-based analysis, significant linear relationships were found between number of plaques and number of calcifications (r = 0.650, p = 0.003) as well as total volume of plaques (r = 0.538, p = 0.018), between number of calcifications and total volume of plaques (r = 0.703, p = 0.001) as well as total volume of calcification (r = 0.646, p = 0.003), and between the total volumes of plaques and calcifications (r = 0.872, p < 0.001). In plaque-based analysis, the power function showed higher R-squared values than the linear function in fitting the relationships of multidimensional geometric parameters. Two presumptions of plaque geometry in different growth stages were proposed with simplified geometric models developed. In the proposed models, the exponents in the power functions of geometric parameters were in accordance with the fitted values. Conclusion: In patients with coronary artery disease, coronary plaques and calcifications are positively related in number and volume. Different coronary plaques are consistent in the relationship between geometry parameters in different dimensions.
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Affiliation(s)
- Haipeng Liu
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.,Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Aleksandra Wingert
- Faculty of Health, Education, Medicine, and Social Care, Anglia Ruskin University, Chelmsford, United Kingdom
| | - Xinhong Wang
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Jucheng Zhang
- Department of Clinical Engineering, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jianzhong Sun
- Department of Radiology, The Second Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, China
| | - Fei Chen
- Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China
| | - Syed Ghufran Khalid
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom.,Department of Medical Physics, Guy's and St Thomas' NHS Foundation Trust, London, United Kingdom
| | - Yinglan Gong
- Key Laboratory for Biomedical Engineering of Ministry of Education, Institute of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Ling Xia
- Key Laboratory for Biomedical Engineering of Ministry of Education, Institute of Biomedical Engineering, Zhejiang University, Hangzhou, China
| | - Jun Jiang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Jian'an Wang
- Department of Cardiology, School of Medicine, The Second Affiliated Hospital, Zhejiang University, Hangzhou, China
| | - Dingchang Zheng
- Research Centre for Intelligent Healthcare, Coventry University, Coventry, United Kingdom
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Different types of cell death in vascular diseases. Mol Biol Rep 2021; 48:4687-4702. [PMID: 34013393 DOI: 10.1007/s11033-021-06402-0] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Accepted: 05/08/2021] [Indexed: 10/21/2022]
Abstract
In a mature organism, tissue homeostasis is regulated by cell division and cell demise as the two major physiological procedures. There is increasing evidence that deregulation of these processes is important in the pathogenicity of main diseases, including myocardial infarction, stroke, atherosclerosis, and inflammatory diseases. Therefore, there are ongoing efforts to discover modulating factors of the cell cycle and cell demise planners aiming at shaping innovative therapeutically modalities to the therapy of such diseases. Although the life of a cell is terminated by several modes of action, a few cell deaths exist-some of which resemble apoptosis and/or necrosis, and most of them are different from one another-that contribute to a wide range of functions to either support or disrupt the homoeostasis. Even in normal physiological conditions, cell life is severe within the cardiovascular system. Cells are persistently undergoing stretch, contraction, injurious metabolic byproducts, and hemodynamic forces, and a few of cells sustain decade-long lifetimes. The duration of vascular disease causes further exposure of vascular cells to a novel range of offences, most of which induce cell death. There is growing evidence on consequences of direct damage to a cell, as well as on responses of adjacent and infiltrating cells, which also have an effect on the pathology. In this study, by focusing on different pathways of cell death in different vascular diseases, an attempt is made to open a new perspective on the therapeutic goals associated with cell death in these diseases.
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Pleouras D, Sakellarios A, Rigas G, Karanasiou GS, Tsompou P, Karanasiou G, Kigka V, Kyriakidis S, Pezoulas V, Gois G, Tachos N, Ramos A, Pelosi G, Rocchiccioli S, Michalis L, Fotiadis DI. A Novel Approach to Generate a Virtual Population of Human Coronary Arteries for In Silico Clinical Trials of Stent Design. IEEE OPEN JOURNAL OF ENGINEERING IN MEDICINE AND BIOLOGY 2021; 2:201-209. [PMID: 35402969 PMCID: PMC8901009 DOI: 10.1109/ojemb.2021.3082328] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/19/2021] [Revised: 05/06/2021] [Accepted: 05/17/2021] [Indexed: 11/15/2022] Open
Abstract
Goal: To develop a cardiovascular virtual population using statistical modeling and computational biomechanics. Methods: A clinical data augmentation algorithm is implemented to efficiently generate virtual clinical data using a real clinical dataset. An atherosclerotic plaque growth model is employed to 3D reconstructed coronary arterial segments to generate virtual coronary arterial geometries (geometrical data). Last, the combination of the virtual clinical and geometrical data is achieved using a methodology that allows for the generation of a realistic virtual population which can be used in in silico clinical trials. Results: The results show good agreement between real and virtual clinical data presenting a mean gof 0.1 ± 0.08. 400 virtual coronary arteries were generated, while the final virtual population includes 10,000 patients. Conclusions: The virtual arterial geometries are efficiently matched to the generated clinical data, both increasing and complementing the variability of the virtual population.
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Affiliation(s)
| | - Antonis Sakellarios
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
| | - George Rigas
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
| | | | - Panagiota Tsompou
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
| | - Gianna Karanasiou
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
| | - Vassiliki Kigka
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
| | - Savvas Kyriakidis
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
| | - Vasileios Pezoulas
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
| | - George Gois
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
| | - Nikolaos Tachos
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
| | - Aidonis Ramos
- Department of Cardiology, Medical SchoolUniversity of Ioannina Ioannina GR 45110 Greece
| | - Gualtiero Pelosi
- Institute of Clinical PhysiologyNational Research Council 56124 Pisa Italy
| | | | - Lampros Michalis
- Department of Cardiology, Medical SchoolUniversity of Ioannina Ioannina GR 45110 Greece
| | - Dimitrios I Fotiadis
- Department of Biomedical ResearchFORTH-IMBB GR 45110 Ioannina Greece
- Unit of Medical Technology and Intelligent Information Systems, Department of Materials Science and EngineeringUniversity of Ioannina GR 45110 Greece
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