An inverse transmission line model of the lower limb arterial system

Includes bibliography. Includes disk in pocket at back of book

Model-based hemodynamic management of critically ill patients.

Hemodynamic monitoring and therapy aims to ensure adequate circulatory function, and thus organ perfusion. However, achieving this goal is challenging due to the inability to directly monitor organ perfusion, difficulty and ambiguity in ascertaining the most appropriate treatment strategy, and highly variable and complex patient response to therapy. Hence, effective measurements and protocols to clarify hemodynamic management and optimise outcomes are urgently needed to meet growing demand for intensive care arising from aging populations and rising rates of chronic disease. This thesis explores model-based solutions to provide real-time, non-additionally-invasive hemodynamic assessment for critical care. These models have the advantage of directly accounting for intra- and inter- patient variability by identifying patient-specific parameters from time-varying data, and monitoring their evolution over time and care. Model validation is performed using data from experimental pig trials, which provide high-fidelity / invasive monitoring not feasible in humans. Further validation is from two clinical databases: VitalDB, from surgical patients; and BedMasterDB, from Christchurch Hospital Intensive Care Unit. This personalised model-based approach is used to provide insight and objective assessments not possible from current measurements. Several clinically-applicable, non-additionally-invasive hemodynamic models are developed and validated in this thesis. Two beat-to-beat cardiac stroke volume estimation methods, the constant-Z windkessel and tube-load models, are shown to outperform existing methods for pig trial and clinical validation. Next, a model is presented to estimate preload changes, Frank-Starling curves, and contractility. The model performed well for the pig trial and for the VitalDB data had reasonable contractility estimation, but poor preload estimation accuracy, providing proof-of-concept. Finally, a model is developed for predicting stroke volume changes in response to fluid therapy. This model had good performance for the pig trial, and a proposed clinical trial design for further validation is presented. All these models together address key elements and insight required to simplify, personalise, and optimise hemodynamic management. This thesis also delivers the design and validation of a low-cost, open-source data acquisition system enabling direct recording of patient arterial pressure waveforms at the same time as a clinical monitor, and measurement of fluid infusion rate. The system is a useful tool for hemodynamic monitoring research, and reduces the high cost barrier of acquiring waveform data from medical monitoring systems, which stifles innovation. Overall, clinically-applicable model-based methods are developed in this thesis to deliver non-additionally-invasive stroke volume monitoring, assessment of cardiac preload responsiveness / contractility, and fluid responsiveness prediction in real-time at the patient bedside. Together, these outputs can provide patient-specific assessment of hemodynamic state and response to therapy. These outputs greatly enrich the information available to clinicians and potentially enable a smarter, more personalised approach to hemodynamic management to improve patient outcomes

Physiological and clinical insights from reservoir-excess pressure analysis

There is a growing body of evidence indicating that reservoir-excess pressure model parameters provide physiological and clinical insights above and beyond standard blood pressure (BP) and pulse waveform analysis. This information has never been collectively examined and was the aim of this review. Cardiovascular disease is the leading cause of mortality worldwide, with BP as the greatest cardiovascular disease risk factor. However, brachial systolic and diastolic BP provide limited information on the underlying BP waveform, missing important BP-related cardiovascular risk. A comprehensive analysis of the BP waveform is provided by parameters derived via the reservoir-excess pressure model, which include reservoir pressure, excess pressure, and systolic and diastolic rate constants and Pinfinity. These parameters, derived from the arterial BP waveform, provide information on the underlying arterial physiology and ventricular–arterial interactions otherwise missed by conventional BP and waveform indices. Application of the reservoir-excess pressure model in the clinical setting may facilitate a better understanding and earlier identification of cardiovascular dysfunction associated with disease. Indeed, reservoir-excess pressure parameters have been associated with sub-clinical markers of end-organ damage, cardiac and vascular dysfunction, and future cardiovascular events and mortality beyond conventional risk factors. In the future, greater understanding is needed on how the underlying physiology of the reservoir-excess pressure parameters informs cardiovascular disease risk prediction over conventional BP and waveform indices. Additional consideration should be given to the application of the reservoir-excess pressure model in clinical practice using new technologies embedded into conventional BP assessment methods

Tube-load model: A clinically applicable pulse contour analysis method for estimation of cardiac stroke volume

peer reviewedBackground and Objectives: Accurate, reproducible, and reliable real-time clinical measurement of stroke volume (SV) is challenging. To accurately estimate arterial mechanics and SV by pulse contour analysis, accounting for wave reflection, such as by a tube-load model, is potentially important. This study tests for the first time whether a dynamically identified tube-load model, given a single peripheral arterial input signal and pulse transit time (PTT), provides accurate SV estimates during hemodynamic instability. Methods: The model is tested for 5 pigs during hemodynamic interventions, using either an aortic flow probe or admittance catheter for a validation SV measure. Performance is assessed using Bland-Altman and polar plot analysis for a series of long-term state-change and short-term dynamic events. Results:The overall median bias and limits of agreement (2.5th, 97.5th percentile) from Bland-Altman analysis were -10% [-49, 36], and -1% [-28,20] for state-change and dynamic events, respectively. The angular limit of agreement (maximum of 2.5th, 97.5th percentile) from polar-plot analysis for state-change and dynamic interventions was 35.6∘, and 35.2∘, respectively. Conclusion: SV estimation agreement and trending performance was reasonable given the severity of the interventions. This simple yet robust method has potential to track SV within acceptable limits during hemodynamic instability in critically ill patients, provided a sufficiently accurate PTT measure. © 2021 Elsevier B.V

TURBULENCE ACCUMULATION AND AVERAGE IN THE SYMMETRICALLY AND ASYMMETRICALLY STENOSED CAROTID BIFURCATION

Ischemic stroke due to atherosclerotic disease has been studied widely in the recent past. Most studies focus on either the correlation between stroke risk and stenosis severity (narrowing of the plaque in the vessel) or mechanisms affecting platelet activation and aggregation. Shear stress has been identified as a strong indicator for platelet activation/aggregation, resulting in both thrombus formation and plaque growth. This has subsequently been correlated with regions of elevated turbulence. Doppler ultrasound offers a method of characterizing these flow disturbances using a well-established parameter—turbulence intensity (Tl), which is the root mean squared deviation in the spectral mean velocity. Using an in-house in vitro flow system, Doppler spectra are obtained at each of over 1000, 1-mm3 isotropically spaced sites in the central plane of seven Teflon phantoms simulating varying degrees of arterial disease. An average of Tl over a 25 mm2 region of interest, as well as the volume of Tl and the cumulative Tl over the internal carotid artery showed that downstream turbulence increased significantly with both stenosis severity (30% - 650% increase) and plaque asymmetry (10% - 30% increase)

Clinically feasible model-based methods to guide cardiovascular fluid therapy in the ICU

Fluid therapy is one of the most commonly used clinical procedures employed in the ICU to treat circulatory shock. Approximately 30% of ICU patients receive a fluid therapy at some stage during their stay, with 20% of patients reviving it on the day of admission. By increasing the total volume in the circulation, clinicians aim to stimulate an increase in cardiac output, helping restore or maintain adequate organ and tissue perfusion. However, only ≈50% of patients receiving a fluid therapy will have also have the desired increase in cardiac output. Furthermore, excessive fluids have been strongly associated with worsened patient outcome and can negate the effects of earlier successful treatment. Therefore, knowledge of a patient’s fluid responsiveness, prior to administering of treatment is essential for safe treatment. Current, clinically used, indices of fluid responsiveness have a number of inherent limitations restricting their applicability or invalidating their use altogether. A recently developed model of the cardiovascular system showed a new index, model based stressed blood volume, to be a potential improvement over currently available indices, but required measurements from inside the cardiac chambers and central arteries for identification, which are not available in standard ICU care. This thesis develops a series of novel methods for estimating the required cardiovascular waveforms required for model identification from currently available clinical measurements. Thus, developing a clinically feasible model-based method to guide fluid therapy in the ICU. The first part of this work introduces the relevant physiology of the cardiovascular system is introduced along with the principles of the circulation driving flow to and from the heart. Next, a brief overview of current indices of fluid responsiveness is given, highlighting their advantages and limitations. Stressed blood volume, in the context of fluid responsiveness, is also introduced. The three-chamber lumped parameter model of the cardiovascular system is then introduced. Each component of the model and all model equations, including the equations governing model dynamics and equations for initial parameter estimation, are detailed. An initial study showing the implementation of the three chambered model is performed to highlight the clinical utility of identified parameters in assessing changes in patient condition. This study was performed on several porcine endotoxin experiments and provided the reference model parameters used to compare the final, clinically feasible method. A subsequent study is performed using the first method introduced to achieve clinical feasibility by removing the requirement of direct cardiac measurements by estimating left ventricle pressure and volume from aortic pressure. Because aortic pressure is also not available in standard ICU environments, the next section of work aimed to develop a method of estimating central pressure. A tube-load model of the arterial system was used to develop and test a novel method of estimating central pressure from commonly available peripheral pressure measurements, via an arterial transfer function, and nothing else. The transfer corresponding flow waveforms were then used, with an initial calibration measurement, to estimate stroke volume in the porcine endotoxin experiments. The final part of his thesis begins by consolidating all developed methods to identify the three-chambered model parameters from an anticipated clinically available subset of measurements from the porcine experiments. Finally, the model, and associated methods for estimating the required inputs, are used to assess fluid responsiveness in patient data obtained from the Christchurch hospital ICU in New Zealand. Overall, this thesis provides a method of identifying the parameters of model of the cardiovascular system model from a minimal, currently available, set of clinical measurements. Model-based stressed blood volume, identified using the three-chambered model, has the physiological basis, animal study validation, and now clinical feasibility, to be considered a potential diagnostic tool in the ICU. The intrinsic relation between stressed blood volume, perfusion pressure and fluid responsiveness means the methods proposed in this thesis may significantly improve a clinicians ability to safely and effective guide fluid therapy

A Hybrid Experimental‐Computational Modeling Framework For Cardiovascular Device Testing

Significant advances in biomedical science often leverage powerful computational and experimental modeling platforms. We present a framework named physiology simulation coupled experiment (“PSCOPE”) that can capitalize on the strengths of both types of platforms in a single hybrid model. PSCOPE uses an iterative method to couple an in vitro mock circuit to a lumped-parameter numerical simulation of physiology, obtaining closed-loop feedback between the two. We first compared the results of Fontan graft obstruction scenarios modeled using both PSCOPE and an established multiscale computational fluid dynamics method; the normalized root-mean-square error values of important physiologic parameters were between 0.1% and 2.1%, confirming the fidelity of the PSCOPE framework. Next, we demonstrate an example application of PSCOPE to model a scenario beyond the current capabilities of multiscale computational methods—the implantation of a Jarvik 2000 blood pump for cavopulmonary support in the single-ventricle circulation; we found that the commercial Jarvik 2000 controller can be modified to produce a suitable rotor speed for augmenting cardiac output by approximately 20% while maintaining blood pressures within safe ranges. The unified modeling framework enables a testing environment which simultaneously operates a medical device and performs computational simulations of the resulting physiology, providing a tool for physically testing medical devices with simulated physiologic feedback

Development, Validation, and Clinical Application of a Numerical Model for Pulse Wave Velocity Propagation in a Cardiovascular System with Application to Noninvasive Blood Pressure Measurements

High blood pressure blood pressure is an important risk factor for cardiovascular disease and affects almost one-third of the U.S. adult population. Historical cuff-less non-invasive techniques used to monitor blood pressure are not accurate and highlight the need for first principal models. The first model is a one-dimensional model for pulse wave velocity (PWV) propagation in compliant arteries that accounts for nonlinear fluids in a linear elastic thin walled vessel. The results indicate an inverse quadratic relationship (R^2=.99) between ejection time and PWV, with ejection time dominating the PWV shifts (12%). The second model predicts the general relationship between PWV and blood pressure with a rigorous account of nonlinearities in the fluid dynamics, blood vessel elasticity, and finite dynamic deformation of a membrane type thin anisotropic wall. The nonlinear model achieves the best match with the experimental data. To retrieve individual vascular information of a patient, the inverse problem of hemodynamics is presented, calculating local orthotropic hyperelastic properties of the arterial wall. The final model examines the impact of the thick arterial wall with different material properties in the radial direction. For a hypertensive subject the thick wall model provides improved accuracy up to 8.4% in PWV prediction over its thin wall counterpart. This translates to nearly 20% improvement in blood pressure prediction based on a PWV measure. The models highlight flow velocity is additive to the classic pressure wave, suggesting flow velocity correction may be important for cuff-less, non-invasive blood pressure measures. Systolic flow correction of the measured PWV improves the R2 correlation to systolic blood pressure from 0.81 to 0.92 for the mongrel dog study, and 0.34 to 0.88 for the human subjects study. The algorithms and insight resulting from this work can enable the development of an integrated microsystem for cuff-less, non-invasive blood pressure monitoring