Improved pressure contour analysis for estimating cardiac stroke volume using pulse wave velocity measurement.

peer reviewedBACKGROUND: Pressure contour analysis is commonly used to estimate cardiac performance for patients suffering from cardiovascular dysfunction in the intensive care unit. However, the existing techniques for continuous estimation of stroke volume (SV) from pressure measurement can be unreliable during hemodynamic instability, which is inevitable for patients requiring significant treatment. For this reason, pressure contour methods must be improved to capture changes in vascular properties and thus provide accurate conversion from pressure to flow. METHODS: This paper presents a novel pressure contour method utilizing pulse wave velocity (PWV) measurement to capture vascular properties. A three-element Windkessel model combined with the reservoir-wave concept are used to decompose the pressure contour into components related to storage and flow. The model parameters are identified beat-to-beat from the water-hammer equation using measured PWV, wave component of the pressure, and an estimate of subject-specific aortic dimension. SV is then calculated by converting pressure to flow using identified model parameters. The accuracy of this novel method is investigated using data from porcine experiments (N = 4 Pietrain pigs, 20-24.5 kg), where hemodynamic properties were significantly altered using dobutamine, fluid administration, and mechanical ventilation. In the experiment, left ventricular volume was measured using admittance catheter, and aortic pressure waveforms were measured at two locations, the aortic arch and abdominal aorta. RESULTS: Bland-Altman analysis comparing gold-standard SV measured by the admittance catheter and estimated SV from the novel method showed average limits of agreement of +/-26% across significant hemodynamic alterations. This result shows the method is capable of estimating clinically acceptable absolute SV values according to Critchely and Critchely. CONCLUSION: The novel pressure contour method presented can accurately estimate and track SV even when hemodynamic properties are significantly altered. Integrating PWV measurements into pressure contour analysis improves identification of beat-to-beat changes in Windkessel model parameters, and thus, provides accurate estimate of blood flow from measured pressure contour. The method has great potential for overcoming weaknesses associated with current pressure contour methods for estimating SV

Minimally invasive, patient specific, beat-by-beat estimation of left ventricular time varying elastance.

peer reviewedBACKGROUND: The aim of this paper was to establish a minimally invasive method for deriving the left ventricular time varying elastance (TVE) curve beat-by-beat, the monitoring of which's inter-beat evolution could add significant new data and insight to improve diagnosis and treatment. The method developed uses the clinically available inputs of aortic pressure, heart rate and baseline end-systolic volume (via echocardiography) to determine the outputs of left ventricular pressure, volume and dead space volume, and thus the TVE curve. This approach avoids directly assuming the shape of the TVE curve, allowing more effective capture of intra- and inter-patient variability. RESULTS: The resulting TVE curve was experimentally validated against the TVE curve as derived from experimentally measured left ventricular pressure and volume in animal models, a data set encompassing 46,318 heartbeats across 5 Pietrain pigs. This simulated TVE curve was able to effectively approximate the measured TVE curve, with an overall median absolute error of 11.4% and overall median signed error of -2.5%. CONCLUSIONS: The use of clinically available inputs means there is potential for real-time implementation of the method at the patient bedside. Thus the method could be used to provide additional, patient specific information on intra- and inter-beat variation in heart function

Model-based hemodynamic monitoring in critical care for improved diagnosis and treatment.

Cardiac and circulatory dysfunction are leading causes of admission, cost, and mortality in the intensive care unit (ICU). However, choosing a suitable treatment is extremely difficult, as a wide range of complex and patient-specific dysfunction types are found. Furthermore, due to the limits and constraints on the currently obtainable data, a full, clear picture of patient state cannot be precisely delineated, which can result in misdiagnosis and incorrect treatment choices. To overcome this problem, cardiovascular parameters essential for correct diagnosis and treatment must be accurately estimated from clinically available measured data. Specifically, the volume of blood ejected from the heart per beat, known as stroke volume (SV), needs to be estimated from easily accessible measurements, such as blood pressure, as it is an important hemodynamic parameter for assessment of cardiovascular performance. This goal can be accomplished by “adding value” to existing clinical data using physiological models of the cardiovascular system. This research develops a novel aortic model and patient-specific hemodynamic parameter identification method for continuous and accurate estimation of SV using measurements commonly available in the ICU. Thus, SV can be acquired in a non-additionally invasive fashion. In addition, use of this SV measurement can enhance the diagnosis, treatment and therapeutic decision support of bedside clinicians. The aortic model developed in this thesis uses continuous aortic pressure waveform and pulse wave velocity (PWV) as inputs to estimate SV. The parameters within the aortic model are aortic characteristic impedance, aortic compliance, and systemic resistance, and are identified beat-to-beat. These parameters are used to compute blood flow and thus to estimate SV for every heartbeat. The SV estimation method is validated with two series of pig experiments involving administration of dobutamine and inducing septic shock, where direct and invasive measurement of SV is obtained for a gold standard comparator. In addition, SV is significantly changed throughout the experiment by modifying preload using various levels of positive end expiratory pressure, as well as fluid administration. The method developed is also compared against the PiCCO system from PULSION, a commercially available pressure-based SV estimation device that is currently considered the most accurate in the critical care. The Bland-Altman results from the porcine study showed clinically acceptable accuracy within approximately ± 30% by the developed model. The PiCCO system also showed similar accuracy compared with the direct SV measurement. However, the PiCCO system required multiple calibrations during the pig study, while the developed method only required one. This result suggests that the developed model and methods are more accurate and clinically useful, particularly when hemodynamic instability is present. Overall, the model developed in this research shows great potential for improving patient care in the ICU. The model offers key hemodynamic parameters for optimizing cardiovascular treatment. In particular, accurate titration of fluid, inotropes, and vasoactive drugs to patient specific responses are now possible. The overall methods and model can be generalized to outpatient management. The overall outcome provide new opportunities to reduce the cost of care, while improving quality. Adding value to existing measurements has not previously been proven in circulartory management. Hence, this research provides a template for further advances, particularly in the highly monitored critical environment

Tracking stressed blood volume during vascular filling experiments

A three-chamber cardiovascular system model is used to compute stressed blood volume from filling experiments. As previously observed, stressed blood volume is a good predictor of the change in cardiac output after fluid infusion

Stroke Volume Estimation using Aortic Pressure Measurements and Aortic Cross Sectional Area

Accurate Stroke Volume (SV) monitoring is essential for patient with cardiovascular dysfunction patients. However, direct SV measurements are not clinically feasible due to the highly invasive nature of measurement devices. Current devices for indirect monitoring of SV are shown to be inaccurate during sudden hemodynamic changes. This paper presents a novel SV estimation using readily available aortic pressure measurements and aortic cross sectional area, using data from a porcine experiment where medical interventions such as fluid replacement, dobutamine infusions, and recruitment maneuvers induced SV changes in a pig with circulatory shock. Measurement of left ventricular volume, proximal aortic pressure, and descending aortic pressure waveforms were made simultaneously during the experiment. From measured data, proximal aortic pressure was separated into reservoir and excess pressures. Beat-to-beat aortic characteristic impedance values were calculated using both aortic pressure measurements and an estimate of the aortic cross sectional area. SV was estimated using the calculated aortic characteristic impedance and excess component of the proximal aorta. The median difference between directly measured SV and estimated SV was -1.4ml with 95% limit of agreement +/- 6.6ml. This method demonstrates that SV can be accurately captured beat-to-beat during sudden changes in hemodynamic state. This novel SV estimation could enable improved cardiac and circulatory treatment in the critical care environment by titrating treatment to the effect on SV

Modelling of the Nonlinear End-Systolic Pressure-Volume Relation and Volume-at-Zero-Pressure in Porcine Experiments

peer reviewedThe End-Systolic Pressure-Volume Relation (ESPVR) is generally modelled as a linear relationship between P and V as cardiac reflexes, such as the baroreflex, are typically suppressed in experiments. However, ESPVR has been observed to behave in a curvilinear fashion when cardiac reflexes are not supressed, suggesting the curvilinear function may be more clinically appropriate. Data was gathered from 41 vena cava occlusion manoeuvres performed experimentally at a variety of PEEPs across 6 porcine specimens, and ESPVR determined for each pig. An exponential model of ESPVR was found to provide a higher correlation coefficient than a linear model in 6 out of 7 cases, and a lower Akaike Information Criterion (AIC) value in all cases. Further, the exponential ESPVR provided positive V0 values in a physiological range in6 out of 7 cases analysed, while the linear ESPVR produced positive V0 values in only 3 out of 7 cases, suggesting linear extrapolation of ESPVR to determine V0 may be flawed

Model-Based Stressed Blood Volume is an Index of Fluid Responsiveness

Fluid therapy is frequently used to manage acute circulatory failure. This therapy aims to restore cardiac output by fluid administration, which increases the quantity of fluid in the circulation. However, it has been shown to be effective only in certain cases, leading to the need for indices of fluid responsiveness. Total stressed blood volume has recently been shown to be such an index of fluid responsiveness. However, the current methods to determine this parameter require specific procedures. In this work, a more straightforward method is developed using data available in the intensive care unit. A simple three-chamber cardiovascular system model is used, of which total stressed blood volume is a parameter. All model parameters (including total stressed blood volume) are adjusted to pig experimental data during fluid administrations. The resulting value of total stressed blood volume is always negatively associated with the relative change in cardiac output after fluid administration. This finding confirms that total stressed blood volume is an index of fluid responsiveness. Another finding of this study is that the response curves are subject-specific. The method developed in this work can be applied to humans, since the data required is typically available in an intensive care unit

Modelling of the nonlinear end-systolic pressure-volume relation and volume-at-zero-pressure in porcine experiments

peer reviewedThe End-Systolic Pressure-Volume Relation (ESPVR) is generally modelled as a linear relationship between P and V as cardiac reflexes, such as the baroreflex, are typically suppressed in experiments. However, ESPVR has been observed to behave in a curvilinear fashion when cardiac reflexes are not supressed, suggesting the curvilinear function may be more clinically appropriate. Data was gathered from 41 vena cava occlusion manoeuvres performed experimentally at a variety of PEEPs across 6 porcine specimens, and ESPVR determined for each pig. An exponential model of ESPVR was found to provide a higher correlation coefficient than a linear model in 6 out of 7 cases, and a lower Akaike Information Criterion (AIC) value in all cases. Further, the exponential ESPVR provided positive V0 values in a physiological range in6 out of 7 cases analysed, while the linear ESPVR produced positive V0 values in only 3 out of 7 cases, suggesting linear extrapolation of ESPVR to determine V0 may be flawed