Cardiac power integral: a new method for monitoring cardiovascular performance

The importance of incorporating ventricular-ventricular interaction (VVI) in the study of pulmonary hypertension

Ventricular ventricular interaction (VVI) affects blood volume and pressure in the right and left ventricles of the heart due to the location and balance of forces on the septal wall separating the ventricles. In healthy patients, the pressure of the left ventricle is considerably higher than the right, resulting in a septal wall that bows into the right ventricle. However, in patients with pulmonary hypertension, the pressure in the right ventricle increases significantly to a point where the pressure is similar to or surpasses that of the left ventricle during portions of the cardiac cycle. For these patients, the septal wall deviates towards the left ventricle, impacting its function. It is possible to study this effect using mathematical modeling, but existing models are nonlinear, leading to a system of algebraic differential equations that can be challenging to solve in patient-specific optimizations of clinical data. This study demonstrates that a simplified linearized model is sufficient to account for the effect of VVI and that, as expected, the impact is significantly more pronounced in patients with pulmonary hypertension.

Parameter inference in a computational model of haemodynamics in pulmonary hypertension

Pulmonary hypertension (PH), defined by a mean pulmonary arterial pressure (mPAP) greater than 20 mmHg, is characterized by increased pulmonary vascular resistance and decreased pulmonary arterial compliance. There are few measurable biomarkers of PH progression, but a conclusive diagnosis of the disease requires invasive right heart catheterization (RHC). Patient-specific cardiovascular systems-level computational models provide a potential non-invasive tool for determining additional indicators of disease severity. Using computational modelling, this study quantifies physiological parameters indicative of disease severity in nine PH patients. The model includes all four heart chambers, the pulmonary and systemic circulations. We consider two sets of calibration data: static (systolic and diastolic values) RHC data and a combination of static and continuous, time-series waveform data. We determine a subset of identifiable parameters for model calibration using sensitivity analyses and multi-start inference and perform posterior uncertainty quantification. Results show that additional waveform data enables accurate calibration of the right atrial reservoir and pump function across the PH cohort. Model outcomes, including stroke work and pulmonary resistance-compliance relations, reflect typical right heart dynamics in PH phenotypes. Lastly, we show that estimated parameters agree with previous, non-modelling studies, supporting this type of analysis in translational PH research.

Fluid structure computational model of simulating mitral valve motion in a contracting left ventricle

BACKGROUND

Fluid structure interaction simulations h hold promise in studying normal and abnormal cardiac function, including the effect of fluid dynamics on mitral valve (MV) leaflet motion. The goal of this study was to develop a 3D fluid structure interaction computational model to simulate bileaflet MV when interacting with blood motion in left ventricle (LV).

METHODS

The model consists of ideal geometric-shaped MV leaflets and the LV, with MV dimensions based on human anatomical measurements. An experimentally-based hyperelastic isotropic material was used to model the mechanical behaviour of the MV leaflets, with chordae tendineae and papillary muscle tips also incorporated. LV myocardial tissue was prescribed using a transverse isotropic hyperelastic formulation. Incompressible Navier-Stokes fluid formulations were used to govern the blood motion, and the Arbitrary Lagrangian Eulerian (ALE) method was employed to determine the mesh deformation of the fluid and solid domains due to trans-valvular pressure on MV boundaries and the resulting leaflet movement.

RESULTS

The LV-MV generic model was able to reproduce physiological MV leaflet opening and closing profiles resulting from the time-varying atrial and ventricular pressures, as well as simulating normal and prolapsed MV states. Additionally, the model was able to simulate blood flow patterns after insertion of a prosthetic MV with and without left ventricular outflow tract flow obstruction. In the MV-LV normal model, the regurgitant blood flow fraction was 10.1 %, with no abnormality in cardiac function according to the mitral regurgitation severity grades reported by the American Society of Echocardiography.

CONCLUSION

Our simulation approach provides insights into intraventricular fluid dynamics in a contracting LV with normal and prolapsed MV function, as well as aiding in the understanding of possible complications after transcatheter MV implantation prior to clinical trials.

Model-based aortic power transfer: A potential measure for quantifying aortic stenosis severity based on measured data

Current aortic stenosis severity grading is based mainly on the local properties of the stenotic valve, such as pressure gradient or jet velocity. Success rates of valve replacement therapy are still suboptimal, so alternative grading of AS should be investigated. We suggest the efficiency of power transfer from the left ventricle to the aorta, as it takes into account heart, valve and circulatory system. Left ventricular and circulatory power were estimated using a 0D model, which was optimised to patient data: left ventricular and aortic pressure, aortic flow and diastolic left ventricular volume. Optimisation was performed using a data assimilation method. These data were available in rest as well as chemically induced exercise for twelve patients. Using this limited data set, we showed that aortic valve efficiency is highly heterogeneous between patients, but also often dependent on the haemodynamic load. This indicates that power transfer efficiency is a highly interesting metric for further research in aortic stenosis.

Cardiac power output accurately reflects external cardiac work over a wide range of inotropic states in pigs

BACKGROUND

Cardiac power output (CPO), derived from the product of cardiac output and mean aortic pressure, is an important yet underexploited parameter for hemodynamic monitoring of critically ill patients in the intensive-care unit (ICU). The conductance catheter-derived pressure-volume loop area reflects left ventricular stroke work (LV SW). Dividing LV SW by time, a measure of LV SW min^- 1 is obtained sharing the same unit as CPO (W). We aimed to validate CPO as a marker of LV SW min^- 1 under various inotropic states.

METHODS

We retrospectively analysed data obtained from experimental studies of the hemodynamic impact of mild hypothermia and hyperthermia on acute heart failure. Fifty-nine anaesthetized and mechanically ventilated closed-chest Landrace pigs (68 ± 1 kg) were instrumented with Swan-Ganz and LV pressure-volume catheters. Data were obtained at body temperatures of 33.0 °C, 38.0 °C and 40.5 °C; before and after: resuscitation, myocardial infarction, endotoxemia, sevoflurane-induced myocardial depression and beta-adrenergic stimulation. We plotted LVSW min^- 1 against CPO by linear regression analysis, as well as against the following classical indices of LV function and work: LV ejection fraction (LV EF), rate-pressure product (RPP), triple product (TP), LV maximum pressure (LVP_max) and maximal rate of rise of LVP (LV dP/dt_max).

RESULTS

CPO showed the best correlation with LV SW min^- 1 (r² = 0.89; p < 0.05) while LV EF did not correlate at all (r² = 0.01; p = 0.259). Further parameters correlated moderately with LV SW min^- 1 (LVP_max r² = 0.47, RPP r² = 0.67; and TP r² = 0.54). LV dP/dt_max correlated worst with LV SW min^- 1 (r² = 0.28).

CONCLUSION

CPO reflects external cardiac work over a wide range of inotropic states. These data further support the use of CPO to monitor inotropic interventions in the ICU.

Ventriculo-arterial interaction may be assessed by Oscillatory Power Fraction

The rate of energy transfer from the left ventricle to the aorta is viewed in terms of mean power (MP) and total power (TP). The difference between MP and TP is due to the pulsatility of the circulation and is known as oscillatory power (OP). OP is considered the energy spent to accelerate the blood flow. The aim of this study was to investigate the baseline left ventricular oscillatory power fraction (OP/TP) and how this was affected by acute cardiovascular dysfunction and altered preload. Twenty-eight patients undergoing elective coronary artery bypass graft surgery were included. Before administration of anaesthesia, we simultaneously recorded an arterial pressure curve and instantaneous cardiac outflow with pulsed wave Doppler. Postoperatively, prior to extubation, these measurements were repeated in neutral, Trendelenburg and reverse-Trendelenburg position. The final measurements were taken on the awake patient the day after the operation. TP is the mean of the instantaneous product of the flow and pressure curves. MP was calculated by multiplying mean arterial pressure with mean cardiac output. The oscillatory power fraction is therefore calculated as (TP-MP)/TP. The oscillatory power fraction in neutral position decreased from 23% preoperatively to 16% immediately postoperatively (P<0·001) and increased again to 19% the first postoperative day (P = 0·001). The oscillatory power fraction also increased from 16% in neutral to 19% in Trendelenburg (P = 0·001) and decreased comparing to neutral, to 14% in reverse-Trendelenburg (P = 0·04). The oscillatory power fraction is situation-dependent and is influenced by both the operation and the altered preload.

Derivation and measurement consistency of a novel biofluid dynamics measure of deglutitive bolus-driving function-pharyngeal swallowing power

BACKGROUND

The primary function of the pharyngeal swallowing mechanism is to drive ingested materials into the esophagus. Currently, a definitive measure of pharyngeal bolus-driving function that accounts for bolus movement remains lacking. The primary objectives of this study were to describe the derivation of a novel biofluid dynamics measure of deglutition-that is, pharyngeal swallowing power (PSP)-and to demonstrate the consistency of PSP in normal swallowing.

METHODS

The pharyngeal swallowing mechanism was conceptualized as a hydraulic power system with the upper esophageal sphincter (UES) as a conduit. PSP was calculated as the product of bolus pressure and flow across the UES. Thirty-four young healthy subjects swallowed materials consisting of two bolus volumes (10, 20 mL) and four bolus viscosities (thin liquid, nectar-thick liquid, honey-thick liquid, pudding). High-resolution impedance manometry was used for data collection. The consistency of PSP across specific bolus conditions was evaluated using standardized Cronbach's coefficient alpha.

KEY RESULTS

Standardized Cronbach's coefficient alphas in specific bolus conditions ranged between 0.85 and 0.93. Fisher weighted mean Cronbach's coefficient alphas for swallow trials across bolus volumes and across bolus viscosities ranged from 0.86 to 0.90. Fisher weighted mean Cronbach's coefficient alpha for overall consistency of PSP across all swallow trials was 0.88.

CONCLUSIONS AND INFERENCES

PSP estimates the output power of the pharyngeal bolus-driving mechanism during deglutition. PSP's high consistency indicates that it can be a useful biofluid dynamics measure of pharyngeal bolus-driving function. Current results also demonstrate that consistency in pharyngeal bolus propulsion is an important physiological target for the pharyngeal swallowing mechanism.

New insights into mitral heart valve prolapse after chordae rupture through fluid-structure interaction computational modeling

Mitral valve (MV) dynamics depends on a force balance across the mitral leaflets, the chordae tendineae, the mitral annulus, the papillary muscles and the adjacent ventricular wall. Chordae rupture disrupts the link between the MV and the left ventricle (LV), causing mitral regurgitation (MR), the most common valvular disease. In this study, a fluid-structure interaction (FSI) modeling framework is implemented to investigate the impact of chordae rupture on the left heart (LH) dynamics and severity of MR. A control and seven chordae rupture LH models were developed to simulate a pathological process in which minimal chordae rupture precedes more extensive chordae rupture. Different non-eccentric and eccentric regurgitant jets were identified during systole. Cardiac efficiency was evaluated by the ratio of external stroke work. MV structural results showed that basal/strut chordae were the major load-bearing chordae. An increased number of ruptured chordae resulted in reduced basal/strut tension, but increased marginal/intermediate load. Chordae rupture in a specific scallop did not necessarily involve an increase in the stress of the entire prolapsed leaflet. This work represents a further step towards patient-specific modeling of pathological LH dynamics, and has the potential to improve our understanding of the biomechanical mechanisms and treatment of primary MR.

Minimally invasive beat-by-beat monitoring of cardiac power in normal hearts and during acute ventricular dysfunction

Cardiac power, the product of aortic flow and blood pressure, appears to be a fundamental cardiovascular parameter. The simplified version named cardiac power output (CPO), calculated as the product of cardiac output (CO) in L/min and mean arterial pressure (MAP) in mmHg divided by 451, has shown great ability to predict outcome in a broad spectrum of cardiac disease. Beat‐by‐beat evaluation of cardiac power (PWR) therefore appears to be a possibly valuable addition when monitoring circulatory unstable patients, providing parameters of overall cardiovascular function. We have developed a minimally invasive system for cardiac power measurement, and aimed in this study to compare this system to an invasive method (ttPWR). Seven male anesthetized farm pigs were included. A laptop with in‐house software gathered audio from Doppler signals of aortic flow and blood pressure from the patient monitor to continuously calculate and display a minimally invasive cardiac power trace (uPWR). The time integral per cardiac cycle (uPWR‐integral) represents cardiac work, and was compared to the invasive counterpart (ttPWR‐integral). Signals were obtained at baseline, during mechanically manipulated preload and afterload, before and after induced global ischemic left ventricular dysfunction. We found that the uPWR‐integral overestimated compared to the ttPWR‐integral by about 10% (P < 0.001) in both normal hearts and during ventricular dysfunction. Bland–Altman limits of agreement were at +0.060 and −0.054 J, without increasing spread over the range. In conclusion we find that the minimally invasive system follows its invasive counterpart, and is ready for clinical research of cardiac power parameters.

Cardiac power parameters during hypovolemia, induced by the lower body negative pressure technique, in healthy volunteers

Background

Changes in cardiac power parameters incorporate changes in both aortic flow and blood pressure. We hypothesized that dynamic and non-dynamic cardiac power parameters would track hypovolemia better than equivalent flow- and pressure parameters, both during spontaneous breathing and non-invasive positive pressure ventilation (NPPV).

Methods

Fourteen healthy volunteers underwent lower body negative pressure (LBNP) of 0, −20, −40, −60 and −80 mmHg to simulate hypovolemia, both during spontaneous breathing and during NPPV. We recorded aortic flow using suprasternal ultrasound Doppler and blood pressure using Finometer, and calculated dynamic and non-dynamic parameters of cardiac power, flow and blood pressure. These were assessed on their association with LBNP-levels.

Results

Respiratory variation in peak aortic flow was the dynamic parameter most affected during spontaneous breathing increasing 103 % (p < 0.001) from baseline to LBNP −80 mmHg. Respiratory variation in pulse pressure was the most affected dynamic parameter during NPPV, increasing 119 % (p < 0.001) from baseline to LBNP −80 mmHg. The cardiac power integral was the most affected non-dynamic parameter falling 59 % (p < 0.001) from baseline to LBNP −80 mmHg during spontaneous breathing, and 68 % (p < 0.001) during NPPV.

Conclusions

Dynamic cardiac power parameters were not better than dynamic flow- and pressure parameters at tracking hypovolemia, seemingly due to previously unknown variation in peripheral vascular resistance matching respiratory changes in hemodynamics. Of non-dynamic parameters, the power parameters track hypovolemia slightly better than equivalent flow parameters, and far better than equivalent pressure parameters.