심폐소생술에 대한 수학적 모델링 기반의 접근

학위논문(박사) -- 서울대학교대학원 : 공과대학 협동과정 바이오엔지니어링전공, 2021.8. 이정찬.심폐소생술의 생리학적 현상에 대한 이해를 위해 심폐소생술의 메커니즘과 이를 기반으로 한 수학적 모델링에 대한 연구들이 많이 진행되어왔다. 하지만, 기존의 수학적 모델이 아직까지 심폐소생술 중의 혈역학적 현상을 제대로 반영하지 못하고 있는 부분이 있다. 또한, 최근 심폐소생술 연구의 방향성은 환자 맞춤형으로 나아가고 있다. 하지만, 환자 맞춤형 심폐소생술은 환자 개인의 요소 및 주변 환경 요소들의 영향을 받기 때문에 임상환경에서 접근하는 것이 쉽지 않다. 따라서, 본 연구는 시뮬레이션 기반의 이론적 연구를 통해 심폐소생술 중의 혈역학에 대한 이해와 통찰력을 제공하고자 3가지 목표를 기반으로 연구를 수행하였다. 첫번째는 현재 심폐소생술의 혈역학적 현상을 반영할 수 있는 개선된 일반화된 심폐소생모델을 개발하는 것을 목표로 하였다. 본 연구에서 제안하는 개선된 심폐소생모델은 기존 모델에 상대정맥과 하대정맥 구획을 추가하였고, “하이브리드 펌프” 메커니즘을 적용하였다. 기존 모델과 개선된 모델의 혈역학적인 현상을 비교하기 위해 다양한 기법에 대한 시뮬레이션 및 동물 모델로부터 얻은 데이터를 비교하였다. 동물 모델과 기존 모델, 개선한 모델의 압력 곡선 및 관상동맥관류압 등을 비교한 결과, 본 연구에서 개선한 모델이 현재의 심폐소생술 메커니즘을 더 잘 반영하는 심폐소생모델임을 검증하였다. 두 번째 목표는 개선한 모델을 기반으로 현재의 심폐소생술 방법으로부터 발생하는 이슈인 흉강의 탄성력 감소에 의한 부정적인 영향과 최적의 압박 위치에 대해 시뮬레이션을 통해 혈역학적인 해석을 제공하고자 하였다. 결과에서 흉강의 탄성력이 감소함에 따라 압박 중 최대 압력이 감소하며, 정맥 복귀 및 혈류 역시 감소하는 결과를 보였다. 압박 위치 변화는 심실과 심방의 압박 비율을 조절하여 시뮬레이션을 수행하였다. 이 결과에서 심실보다 심방이 더 많이 압박될 경우 1회 박출량 및 관상동맥 관류 압이 감소하면서 혈역학이 제한되는 결과를 보여주었다. 따라서, 압박 중 최대 압력 변화와 관상동맥관류압의 변화는 흉강의 탄성력 변화 추정 및 압박 위치 가이드를 해줄 수 있는 잠재력을 가질 수 있음을 입증하였다. 마지막으로 환자 맞춤형 심폐소생술모델의 가능성을 제시하고자 하였다. 본 연구에서는 유전자 알고리즘을 통해 환자 개별에 대한 심혈관계 파라미터를 추정하였고, 환자마다 다른 심혈관계 파라미터 세트를 가짐으로써 맞춤형 심혈관계 모델을 구성할 수 있음을 검증하였다. 또한, 맞춤형 심혈관계 모델에 심폐소생모델을 적용하여 심혈관계 파라미터 구성에 따라 흉부 압박 시 혈역학적 영향이 달라짐을 검증하였다. 추가적으로 돼지 모델에서 다양한 압박 조건 변화에 대한 혈역학적 변화를 비교하였고, 이를 통해 맞춤형 모델을 통해 최적의 혈역학적 효과를 갖는 압박 조건을 제시할 수 있음을 보였다. 결론적으로 본 연구를 통해 제안하는 심폐소생 모델이 현재 심폐소생술에 의한 메커니즘을 더 잘 반영하는 일반화된 모델임을 보여주었고, 이를 통해 현재 심폐소생술 방법에 의한 이슈에 대해서 혈역학적인 해석이 가능함을 입증하였다. 또한, 이를 기반으로 환자 맞춤형 심폐소생 모델의 가능성 제시함으로써 맞춤형 심폐소생 모델링에 대한 연구의 기반이 될 수 있음을 보여주었다.For a long time, many studies based on mathematical modeling have been conducted to understand cardiopulmonary resuscitation (CPR) physiology. However, some aspects of the existing CPR model do not reflect the current CPR physiology appropriately. If the generalized CPR model does not suitably reflect the hemodynamic phenomena of current CPR, errors may exist in the hemodynamic interpretation. In addition, it is suggested that the one-size-fits-all CPR specified in the guidelines is not suitable, and the direction of recent CPR research is shifting toward personalized CPR. However, in personalized CPR, it is difficult to use preclinical or clinical trial approaches because various factors associated with the patient and environment interact and affect the patient. Therefore, this study was conducted with three goals to provide insight into the hemodynamics during CPR through a simulation-based approach. The first objective was to develop an improved generalized CPR model that can reflect the current CPR physiology. The modified CPR model proposed herein added superior and inferior vena cava compartments in the thoracic cavity of the existing model, as well as a “hybrid pump” mechanism. To compare the hemodynamic effects of the existing and modified models, various maneuvers such as the active compression-decompression CPR combined with the impedance threshold device, head-up tilt, and head-down tilt were simulated. Additionally, the modified model was compared with an animal model to confirm that it reflects the current CPR physiology more than the existing model does. The comparison showed that the pressure waveform and coronary perfusion pressure (CPP) were more appropriately reflected than in the existing model. Therefore, it was verified that the improved model developed in this study is a generalized CPR model that reflects the current CPR physiology more accurately. The second goal was to verify the hemodynamic effects on the reduced thoracic elasticity and compression position—which are the current issues of the existing CPR technique—through simulation based on the improved model. The reduced elasticity of the thorax was simulated to decrease linearly for 1 min immediately after the start of CPR. The results show that as the elasticity of the thorax decreased, the pressure amplitude of the aorta and vena cava decreased during compression, along with the venous return and blood flow. Furthermore, a simple simulation was performed by adjusting the compression ratio between the ventricle and atrium with the thoracic pump factor to compare the hemodynamic difference according to the compression position. Consequently, when the atrium was compressed more than the ventricle, the stroke volume and CPP decreased, indicating that hemodynamics was limited. Therefore, it was demonstrated that a change in the pressure amplitude and CPP during compression could potentially enable estimation of the change in the elasticity of the thorax and assist in determining the position of compression. Finally, this study attempted to present the possibility of a personalized CPR model. Cardiovascular parameters were estimated for different patients using a genetic algorithm. Additionally, it was confirmed that patient-specific cardiovascular models could be constructed with different sets of parameters for each patient. Furthermore, incorporating the CPR model into the patient-specific cardiovascular model revealed that the hemodynamic effect of chest compression varies according to the cardiovascular parameter configuration. The hemodynamic changes for different compression conditions were compared in a pig model. From the results, it was shown that various hemodynamics occurred depending on the compression condition when using the personalized CPR model. Thus, it is possible to determine the optimal compression condition for the patient-specific from this. In conclusion, this study showed that the modified CPR model is a generalized model that reflects the current CPR physiology more accurately. It also proved that hemodynamic interpretation can address the limitations of the current CPR technique through the modified model. Additionally, by presenting the possibility of a patient-specific CPR model based on this, this study can serve as the basis for research on personalized CPR modeling.Chapter 1. Introduction 1 1.1 Basic understanding of cardiovascular system 2 1.1.1 Cardiac output 2 1.1.2 Venous return and Frank-Starling law 5 1.1.3 Blood circulatory system 7 1.2 Cardiopulmonary resuscitation (CPR) 10 1.2.1 Basic concept for CPR 10 1.2.2 Theories for CPR mechanism 13 1.3 Mathematical modeling for CPR 15 1.3.1 Basic concept of lumped parameter model for cardiovascular system 15 1.3.2 Previous studies on CPR modeling 20 1.4 Motivation and objectives 22 Chapter 2. Materials and Methods 29 2.1 Modified CPR model for general CPR model 30 2.1.1 Modified hybrid CPR model 30 2.1.2 Simulations of various maneuvers for CPR model 35 2.1.2.1 Active compression-decompression CPR with an impedance threshold valve (ACD-CPR+ITV) 35 2.1.2.2 Head-up tilt (HUT) and head-down tilt (HDT) 37 2.1.3 Animal experiments for hemodynamic data acquisition 39 2.1.3.1 Experimental protocol 40 2.1.3.2 Data acquisition 41 2.2 Simulation-based approach to current issues in CPR using modified hybrid CPR model 42 2.2.1 Reduced elasticity of thorax 42 2.2.1 Ventricle-atrium compression ratio (VAR) for compression position 43 2.3 Parameter estimation of simple cardiovascular model for patient-specific CPR model 45 2.3.1 Simple cardiovascular model 45 2.3.2 Genetic algorithm for parameter estimation 47 2.3.3 Application of CPR model to patient-specific cardiovascular model 49 Chapter 3. Results and Discussion 51 3.1 Modified CPR model based on general CPR model 52 3.1.1 Comparison results of animal experiments and simulations 54 3.1.2 Hemodynamic effects on the various maneuvers 58 3.1.2.1 Comparison of CPR techniques 58 3.1.2.2 HUT and HDT 60 3.2 Simulation-based approach to current issues in CPR using modified CPR model 64 3.2.1 Hemodynamic effects on reduced elasticity of thorax 64 3.2.2 Coronary perfusion pressure for various VAR 68 3.3 Parameter estimation of simple cardiovascular model for patient-specific CPR model 72 3.3.1 Verification of parameter estimation using open dataset 74 3.3.2 Application to patient-specific CPR model 88 3.4 Limitations 100 Chapter 4. Conclusion 102 4.1 Dissertation summary 103 4.2 Future works 105 References 107 Abstract in Korean 117 Acknowledgement 119 감사의 글 120박

Replacement of animal models of cardiac arrest and resuscitation strategies using a computer simulation

This doctoral thesis explores cardiac arrest (CA) and cardiopulmonary resuscitation (CPR) from a multidisciplinary perspective, with a focus on three main objectives: enhancing the Interdisciplinary Collaboration in Systems Medicine (ICSM) simulation suite, investigating the pathophysiology of CA, and proposing an alternative to animal models in CA and CPR research. The ICSM simulation suite was significantly improved, with additions such as a thoracic model for chest compressions, multiple organ tissue compartments, a vasculature equation accounting for resistance changes, circulatory transport delays, retrograded blood flow during CPR, and respiratory and cardiovascular control mechanisms. Utilizing the enhanced ICSM simulation suite, a series of studies were conducted to examine various aspects of CPR strategies, all with the aim of improving resuscitation outcomes. These studies encompassed investigations into the impact of positive end-expiratory pressure (PEEP) on cardiac output during CPR, the effects of chest compression rate, depth, and duty cycle, the influence of the precipitating aetiology on CPR strategy optimization, and the comparison of personalized CPR strategies to current guidelines. The research also quantitatively identified the effect of CPR parameters on cardiac output, with end compression force and positive end expiratory pressure emerging as significant contributors. The validation of the ICSM simulation suite thoracic model using individual haemodynamic recordings of a patient undergoing CPR demonstrated its capacity to simulate individualized patient data for retrospective identification of optimized CPR protocols. These outcomes collectively emphasize the potential of computational models, particularly the ICSM simulation suite, to revolutionize CA and CPR research by providing humane, informative, and personalized alternatives to traditional animal models. The findings of this research suggest that the ICSM simulation suite offers a valuable alternative to animal models in the study of CA and CPR. This computational model allows for the simulation and investigation of personalized CPR strategies, which can be tailored to individual patients' need

Replacement of animal models of cardiac arrest and resuscitation strategies using a computer simulation

This doctoral thesis explores cardiac arrest (CA) and cardiopulmonary resuscitation (CPR) from a multidisciplinary perspective, with a focus on three main objectives: enhancing the Interdisciplinary Collaboration in Systems Medicine (ICSM) simulation suite, investigating the pathophysiology of CA, and proposing an alternative to animal models in CA and CPR research. The ICSM simulation suite was significantly improved, with additions such as a thoracic model for chest compressions, multiple organ tissue compartments, a vasculature equation accounting for resistance changes, circulatory transport delays, retrograded blood flow during CPR, and respiratory and cardiovascular control mechanisms. Utilizing the enhanced ICSM simulation suite, a series of studies were conducted to examine various aspects of CPR strategies, all with the aim of improving resuscitation outcomes. These studies encompassed investigations into the impact of positive end-expiratory pressure (PEEP) on cardiac output during CPR, the effects of chest compression rate, depth, and duty cycle, the influence of the precipitating aetiology on CPR strategy optimization, and the comparison of personalized CPR strategies to current guidelines. The research also quantitatively identified the effect of CPR parameters on cardiac output, with end compression force and positive end expiratory pressure emerging as significant contributors. The validation of the ICSM simulation suite thoracic model using individual haemodynamic recordings of a patient undergoing CPR demonstrated its capacity to simulate individualized patient data for retrospective identification of optimized CPR protocols. These outcomes collectively emphasize the potential of computational models, particularly the ICSM simulation suite, to revolutionize CA and CPR research by providing humane, informative, and personalized alternatives to traditional animal models. The findings of this research suggest that the ICSM simulation suite offers a valuable alternative to animal models in the study of CA and CPR. This computational model allows for the simulation and investigation of personalized CPR strategies, which can be tailored to individual patients' need