Modeling a healthy and a person with heart failure conditions using the object-oriented modeling environment Dymola

A mathematical model to assess the effects of COVID-19 on the cardiocirculatory system

Impaired cardiac function has been described as a frequent complication of COVID-19-related pneumonia. To investigate possible underlying mechanisms, we represented the cardiovascular system by means of a lumped-parameter 0D mathematical model. The model was calibrated using clinical data, recorded in 58 patients hospitalized for COVID-19-related pneumonia, to make it patient-specific and to compute model outputs of clinical interest related to the cardiocirculatory system. We assessed, for each patient with a successful calibration, the statistical reliability of model outputs estimating the uncertainty intervals. Then, we performed a statistical analysis to compare healthy ranges and mean values (over patients) of reliable model outputs to determine which were significantly altered in COVID-19-related pneumonia. Our results showed significant increases in right ventricular systolic pressure, diastolic and mean pulmonary arterial pressure, and capillary wedge pressure. Instead, physical quantities related to the systemic circulation were not significantly altered. Remarkably, statistical analyses made on raw clinical data, without the support of a mathematical model, were unable to detect the effects of COVID-19-related pneumonia in pulmonary circulation, thus suggesting that the use of a calibrated 0D mathematical model to describe the cardiocirculatory system is an effective tool to investigate the impairments of the cardiocirculatory system associated with COVID-19.

Modeling the cardiac response to hemodynamic changes associated with COVID-19: a computational study

Emerging studies address how COVID-19 infection can impact the human cardiovascular system. This relates particularly to the development of myocardial injury, acute coronary syndrome, myocarditis, arrhythmia, and heart failure. Prospective treatment approach is advised for these patients. To study the interplay between local changes (reduced contractility), global variables (peripheral resistances, heart rate) and the cardiac function, we considered a lumped parameters computational model of the cardiovascular system and a three-dimensional multiphysics model of cardiac electromechanics. Our mathematical model allows to simulate the systemic and pulmonary circulations, the four cardiac valves and the four heart chambers, through equations describing the underlying physical processes. By the assessment of conventionally relevant parameters of cardiac function obtained through our numerical simulations, we propose a computational model to effectively reveal the interactions between the cardiac and pulmonary functions in virtual subjects with normal and impaired cardiac function at baseline affected by mild or severe COVID-19.

Advances in Hemodynamic Analysis in Cardiovascular Diseases Investigation of Energetic Characteristics of Adult and Pediatric Sputnik Left Ventricular Assist Devices during Mock Circulation Support

The need to simulate the operating conditions of the human body is a key factor in every study and engineering process of a bioengineering device developed for implantation. In the present paper, we describe in detail the interaction between the left ventricle (LV) and our Sputnik left ventricular assist devices (LVADs). This research aims to evaluate the influence of different rotary blood pumps (RBPs) on the LV depending on the degree of heart failure (HF), in order to investigate energetic characteristics of the LV-LVAD interaction and to estimate main parameters of left ventricular unloading. We investigate energetic characteristics of adult Sputnik 1 and Sputnik 2 LVADs connected to a hybrid adult mock circulation (HAMC) and also for the Sputnik pediatric rotary blood pump (PRBP) connected to a pediatric mock circulation (PMC). A major improvement of the LV unloading is observed during all simulations for each particular heart failure state when connected to the LVAD, with sequential pump speed increased within 5000–10000 rpm for adult LVADs and 6000–13000 rpm for PRBP with 200 rpm step. Additionally, it was found that depending on the degree of heart failure, LVADs influence the LV in different ways and a significant support level cannot be achieved without the aortic valve closure. Furthermore, this study expands the information on LV-LVAD interaction, which leads to the optimization of the RBP speed rate control in clinics for adult and pediatric patients suffering from heart failure. Finally, we show that the implementation of control algorithms using the modulation of the RBP speed in order to open the aortic valve and unload the LV more efficiently is necessary and will be content of further research.

Object-oriented modeling of thoracic fluid balance to study cardiogenic pulmonary congestion in humans

BACKGROUND AND OBJECTIVE

We hypothesized that a biophysical computational model implemented in an object-oriented modeling language (OOML) would provide physiological information and simulative data to study the development and treatment of cardiogenic pulmonary congestion.

METHODS

This work is based on the object-oriented cardiopulmonary interaction introduced in [1]. This paper describes the novel model components required to study cardiogenic pulmonary congestion: i) interstitial fluid exchange related to the Starling equation, ii) the lymphatic pump, and iii) the interconnection of these elements with the original cardiopulmonary model. The presented model succeeds in i) describing lymphatic flow at the capillary artery and venous end, ii) activation of the lymphatic pump at elevated pulmonary pressures, and iii) the simulation of the different safety factors related to lung tissue, osmotic gradient, and the lymphatic system during the development of lung congestion.

RESULTS

Simulations show a qualitative correlation between model behavior and physiological data from literature. The model also demonstrates the beneficial effect of continuous positive airway pressure therapy on fluid clearance and respiratory mechanics.

CONCLUSION

This study demonstrates the successful use of OOML to describe the development of cardiogenic congestion by introducing a model of the lymphatic system and the thoracic fluid balance system, as well as connecting them to the existing cardiopulmonary model.

Modeling photoplethysmographic signals in camera-based perfusion measurements: optoelectronic skin phantom

The remote acquisition of photoplethysmographic (PPG) signals via a video camera, also known as photoplethysmography imaging (PPGI), is not yet standardized. In general, PPGI is investigated with test persons in a laboratory setting. While these in-vivo tests have the advantage of generating real-life data, they suffer from the lack of repeatability and are comparatively effort-intensive because human subjects are required. Consequently, studying changes in signal morphology, for example, due to aging or pathological effects, is practically impossible. As a tool to study these effects, a hardware PPG simulator has been developed: this is a phantom which simulates and generates both 1D and locally resolved 2D optical PPG signals. Here, we demonstrate that it is possible to generate PPG-like signals with various signal morphologies by means of a purely optoelectronic setup, namely an LED array, and to analyze them by means of PPGI. Signals extracted via a camera show good agreement with simulated generated signals. In fact, the first phantom design is suitable to demonstrate this qualitatively.

Online cardiac output estimation during transvalvular left ventricular assistance

BACKGROUND AND OBJECTIVES

Sufficient cardiac output is one of the main goals of ventricular assist device therapy. To date, there is no adequate method to estimate the combined amount of blood the native heart and a continuous-flow assist device pump through the circulatory system. This paper presents an approach to estimate total cardiac output based on the signals provided by optical pressure sensors mounted on the inlet and outlet of an Abiomed Impella CP pump.

METHODS

Two Kalman filters were used in parallel for joint estimation of the aortic flow rate and the hydraulic resistance of the aortic valve. The filters utilized a third order nonlinear state-space representation of the cardiovascular system with two nominal parameter sets, one for ovine and another for human subjects. The accuracy of the estimated cardiac output has been investigated in a hybrid mock circulatory loop and an animal study involving two sheep with experimentally induced acute ischaemic heart disease supported by a transvalvular left ventricular assist device.

RESULTS

The in vitro accuracy of the cardiac output estimation is ±3.64%. In an ovine model, the comparison of the estimated cardiac output with an ultrasonic flow measurement in the pulmonary artery showed 95% limits of agreement of -0.004 ± 0.897 L min^-1. The estimation errors were comparable to the accuracy of the measurement (±10%), which is the gold standard in research for invasive blood flow diagnostics.

CONCLUSIONS

The online estimation of total cardiac output may give the treating physician a direct and physiologically meaningful feedback on the pump speed setting. One promising possible application of our method is physiological control, where the cardiac output can be used as the control variable for closed-loop ventricular assist device therapy.

An object-oriented computational model to study cardiopulmonary hemodynamic interactions in humans

BACKGROUND AND OBJECTIVE

This work introduces an object-oriented computational model to study cardiopulmonary interactions in humans.

METHODS

Modeling was performed in object-oriented programing language Matlab Simscape, where model components are connected with each other through physical connections. Constitutive and phenomenological equations of model elements are implemented based on their non-linear pressure-volume or pressure-flow relationship. The model includes more than 30 physiological compartments, which belong either to the cardiovascular or respiratory system. The model considers non-linear behaviors of veins, pulmonary capillaries, collapsible airways, alveoli, and the chest wall. Model parameters were derisved based on literature values. Model validation was performed by comparing simulation results with clinical and animal data reported in literature.

RESULTS

The model is able to provide quantitative values of alveolar, pleural, interstitial, aortic and ventricular pressures, as well as heart and lung volumes during spontaneous breathing and mechanical ventilation. Results of baseline simulation demonstrate the consistency of the assigned parameters. Simulation results during mechanical ventilation with PEEP trials can be directly compared with animal and clinical data given in literature.

CONCLUSIONS

Object-oriented programming languages can be used to model interconnected systems including model non-linearities. The model provides a useful tool to investigate cardiopulmonary activity during spontaneous breathing and mechanical ventilation.

Real-Time ECG Simulation for Hybrid Mock Circulatory Loops

Classically, mock circulatory loops only simulate mechanical properties of the circulation. To connect the hydraulic world with electrophysiology, we present a real-time electrical activity model of the heart and show how to integrate this model into a real-time mock loop simulation. The model incorporates a predefined conduction pathway and a simplified volume conductor to solve the bidomain equations and the forward problem of electrocardiography, resulting in a physiological simulation of the electrocardiogram (ECG) at arbitrary electrode positions. A complete physiological simulation of the heart's excitation would be too CPU intensive. Thus, in our model, complexity was reduced to allow real-time simulation of ECG-triggered medical systems in vitro; this decreases time and cost in the development process. Conversely, the presented model can still be adapted to various pathologies by locally changing the properties of the heart's conduction pathway. To simulate the ECG, the heart is divided into suitable areas, which are innervated by the hierarchically structured conduction system. To distinguish different cardiac regions, a segmentation of the heart was performed. In these regions, Prim's algorithm was applied to identify the directed minimal spanning trees for conduction orientation. Each node of the tree was assigned to a cardiac action potential generated by its hybrid automaton to represent the heart's conduction system by the spatial distribution of action potentials. To generate the ECG output, the bidomain equations were implemented and a simple model of the volume conductor of the body was used to solve the forward problem of electrocardiography. As a result, the model simulates potentials at arbitrary electrode positions in real-time. To verify the developed real-time ECG model, measurements were made within a hybrid mock circulatory loop, including a simple ECG-triggered ventricular assist device control. The model's potential value is to simulate physiological and pathological behavior for hardware-in-the-loop testing of medical devices in an ECG-triggered scenario.

Large-scale computational models of liver metabolism: How far from the clinics?

Understanding the dynamics of human liver metabolism is fundamental for effective diagnosis and treatment of liver diseases. This knowledge can be obtained with systems biology/medicine approaches that account for the complexity of hepatic responses and their systemic consequences in other organs. Computational modeling can reveal hidden principles of the system by classification of individual components, analyzing their interactions and simulating the effects that are difficult to investigate experimentally. Herein, we review the state-of-the-art computational models that describe liver dynamics from metabolic, gene regulatory, and signal transduction perspectives. We focus especially on large-scale liver models described either by genome scale metabolic networks or an object-oriented approach. We also discuss the benefits and limitations of each modeling approach and their value for clinical applications in diagnosis, therapy, and prevention of liver diseases as well as precision medicine in hepatology. (Hepatology 2017;66:1323-1334).

Diagnosis of coronary artery disease using an efficient hash table based closed frequent itemsets mining

This paper proposes an efficient hash table based closed frequent itemsets (HCFI) mining algorithm to envisage coronary artery disease early. HCFI algorithm generates closed frequent itemsets efficiently by performing intersection operation on transaction id's of itemset without considering the name of item/itemset. The employed hash table reduces search efficiency to O(1) or constant time. HCFI algorithm is applied on the UCI (University of California, Irvine) Cleveland dataset, a biological database of cardiovascular disease to generate closed frequent itemsets on the dataset. The findings of HCFI algorithm are (1) it determines a set of distinguished features to differentiate a 'healthy' and a 'sick' class. The features such as heart status being normal, oldpeak being less than or equal to 1.2, slope being up, number of vessels colored being zero, absence of exercise-induced angina, maximum heart rate achieved between 151 and 180 are referred as 'healthy' class. The features like chest pain are being asymptomatic, heart-status being reversible defect, slope being flat, and presence of exercise-induced-angina and serum cholesterol being greater than 240 indicate a presumption of heart disease to both genders. (2) It predicts that females have less chance of coronary heart disease than males. This algorithm is also compared with two other state-of-the-art-algorithms 'NAFCP' (N-list based algorithm for mining frequent closed patterns) and 'PredictiveApriori' to show the effectiveness of the proposed algorithm.

Benefits of object-oriented models and ModeliChart: modern tools and methods for the interdisciplinary research on smart biomedical technology

Computational models of biophysical systems generally constitute an essential component in the realization of smart biomedical technological applications. Typically, the development process of such models is characterized by a great extent of collaboration between different interdisciplinary parties. Furthermore, due to the fact that many underlying mechanisms and the necessary degree of abstraction of biophysical system models are unknown beforehand, the steps of the development process of the application are iteratively repeated when the model is refined. This paper presents some methods and tools to facilitate the development process. First, the principle of object-oriented (OO) modeling is presented and the advantages over classical signal-oriented modeling are emphasized. Second, our self-developed simulation tool ModeliChart is presented. ModeliChart was designed specifically for clinical users and allows independently performing