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Liao SF, Li YJ, Cao S, Xue CD, Tian S, Wu GF, Chen XM, Chen D, Qin KR. Hemodynamics of ventricular-arterial coupling under enhanced external counterpulsation: An optimized dual-source lumped parameter model. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 250:108191. [PMID: 38677079 DOI: 10.1016/j.cmpb.2024.108191] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/14/2024] [Revised: 04/16/2024] [Accepted: 04/20/2024] [Indexed: 04/29/2024]
Abstract
BACKGROUND AND OBJECTIVE Enhanced external counterpulsation (EECP) is a mechanically assisted circulation technique widely used in the rehabilitation and management of ischemic cardiovascular diseases. It contributes to cardiovascular functions by regulating the afterload of ventricle to improve hemodynamic effects, including increased diastolic blood pressure at aortic root, increased cardiac output and enhanced blood perfusion to multiple organs including coronary circulation. However, the effects of EECP on the coupling of the ventricle and the arterial system, termed ventricular-arterial coupling (VAC), remain elusive. We aimed to investigate the acute effect of EECP on the dynamic interaction between the left ventricle and its afterload of the arterial system from the perspective of ventricular output work. METHODS A neural network assisted optimization algorithm was proposed to identify the ordinary differential equation (ODE) relation between aortic root blood pressure and flow rate. Based on the optimized order of ODE, a lumped parameter model (LPM) under EECP was developed taking into consideration of the simultaneous action of cardiac and EECP pressure sources. The ventricular output work, in terms of aortic pressure and flow rate cooperated with the LPM, was used to characterize the VAC of ventricle and its afterload. The VAC subjected to the principle of minimal ventricular output work was validated by solving the Euler-Poisson equation of cost function, ultimately determining the waveforms of aortic pressure and flow rate. RESULTS A third-order ODE can precisely describe the hemodynamic relationship between aortic pressure and flow rate. An optimized dual-source LPM with three energy-storage elements has been constructed, showing the potential in probing VAC under EECP. The LPM simulation results demonstrated that the VAC in terms of aortic pressure and flow rate yielded to the minimal ventricular output work under different EECP pressures. CONCLUSIONS The ventricular-arterial coupling under EECP is subjected to the minimal ventricular output work, which can serve as a criterion for determining aortic pressure and flow rate. This study provides insight for the understanding of VAC and has the potential in characterizing the performance of the ventricular and arterial system under EECP.
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Affiliation(s)
- Sheng-Fu Liao
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Yong-Jiang Li
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Sen Cao
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Chun-Dong Xue
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Shuai Tian
- Department of Cardiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong 518033, China
| | - Gui-Fu Wu
- Department of Cardiology, The Eighth Affiliated Hospital of Sun Yat-Sen University, Shenzhen, Guangdong 518033, China
| | - Xiao-Ming Chen
- School of Optoelectronic Engineering and Instrumentation Science, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Dong Chen
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning 116024, China
| | - Kai-Rong Qin
- Institute of Cardio-Cerebrovascular Medicine, Central Hospital of Dalian University of Technology, Dalian, Liaoning 116033, China; School of Biomedical Engineering, Faculty of Medicine, Dalian University of Technology, Dalian, Liaoning 116024, China.
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Vicente-Martínez J, Bonmatí-Carrión MÁ, Madrid JA, Rol MA. Uncovering personal circadian responses to light through particle swarm optimization. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2024; 243:107933. [PMID: 38006683 DOI: 10.1016/j.cmpb.2023.107933] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/23/2023] [Revised: 10/02/2023] [Accepted: 11/17/2023] [Indexed: 11/27/2023]
Abstract
BACKGROUND AND OBJECTIVES Kronauer's oscillator model of the human central pacemaker is one of the most commonly used approaches to study the human circadian response to light. Two sources of error when applying it to a personal light exposure have been identified: (1) as a populational model, it does not consider inter-individual variability, and (2) the initial conditions needed to integrate the model are usually unknown, and thus subjectively estimated. In this work, we evaluate the ability of particle swarm optimization (PSO) algorithms to simultaneously uncover the optimal initial conditions and individual parameters of a pre-defined Kronauer's oscillator model. METHODS A Canonical PSO, a Dynamic Multi-Swarm PSO and a novel modification of the latter, namely Hierarchical Dynamic Multi-Swarm PSO, are evaluated. Two different target models (under a regular and an irregular schedule) are defined, and the same realistic light profile is fed to them. Based on their output, a fitness function is proposed, which is minimized by the algorithms to find the optimum set of parameters and initial conditions of the model. RESULTS We demonstrate that Dynamic Multi-Swarm and Hierarchical Dynamic Multi-Swarm algorithms can accurately uncover personal circadian parameters under both regular and irregular schedules, but as expected, optimization is easier under a regular schedule. Circadian parameters play the most important role in the optimization process and should be prioritized over initial conditions, although assessment of the impact of misestimating the latter is recommended. The log-log linear relationship between mean absolute error and computational cost shows that the number of particles to use is at the discretion of the user. CONCLUSIONS The robustness and low errors achieved by the algorithms support their further testing, validation and systematic application to empirical data under a regular or irregular schedule. Uncovering personal circadian parameters can improve the assessment of the circadian status of a person and the applicability of personalized light therapies, as well as help to discover other factors that may lie behind the interindividual variability in the circadian response to light.
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Affiliation(s)
- Jesús Vicente-Martínez
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - María Ángeles Bonmatí-Carrión
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain.
| | - Juan Antonio Madrid
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
| | - Maria Angeles Rol
- Chronobiology Laboratory, Department of Physiology, College of Biology, University of Murcia, Mare Nostrum Campus, IUIE, IMIB-Arrixaca, Murcia 30100, Spain; Ciber Fragilidad y Envejecimiento Saludable, Instituto de Salud Carlos III, Madrid 28029, Spain
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Bracamonte JH, Saunders SK, Wilson JS, Truong UT, Soares JS. Patient-Specific Inverse Modeling of In Vivo Cardiovascular Mechanics with Medical Image-Derived Kinematics as Input Data: Concepts, Methods, and Applications. APPLIED SCIENCES-BASEL 2022; 12:3954. [PMID: 36911244 PMCID: PMC10004130 DOI: 10.3390/app12083954] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/16/2022]
Abstract
Inverse modeling approaches in cardiovascular medicine are a collection of methodologies that can provide non-invasive patient-specific estimations of tissue properties, mechanical loads, and other mechanics-based risk factors using medical imaging as inputs. Its incorporation into clinical practice has the potential to improve diagnosis and treatment planning with low associated risks and costs. These methods have become available for medical applications mainly due to the continuing development of image-based kinematic techniques, the maturity of the associated theories describing cardiovascular function, and recent progress in computer science, modeling, and simulation engineering. Inverse method applications are multidisciplinary, requiring tailored solutions to the available clinical data, pathology of interest, and available computational resources. Herein, we review biomechanical modeling and simulation principles, methods of solving inverse problems, and techniques for image-based kinematic analysis. In the final section, the major advances in inverse modeling of human cardiovascular mechanics since its early development in the early 2000s are reviewed with emphasis on method-specific descriptions, results, and conclusions. We draw selected studies on healthy and diseased hearts, aortas, and pulmonary arteries achieved through the incorporation of tissue mechanics, hemodynamics, and fluid-structure interaction methods paired with patient-specific data acquired with medical imaging in inverse modeling approaches.
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Affiliation(s)
- Johane H. Bracamonte
- Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - Sarah K. Saunders
- Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA
| | - John S. Wilson
- Department of Biomedical Engineering and Pauley Heart Center, Virginia Commonwealth University, Richmond, VA 23219, USA
| | - Uyen T. Truong
- Department of Pediatrics, School of Medicine, Children’s Hospital of Richmond at Virginia Commonwealth University, Richmond, VA 23219, USA
| | - Joao S. Soares
- Department of Mechanical and Nuclear Engineering, Virginia Commonwealth University, Richmond, VA 23284, USA
- Correspondence:
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