The Future of Durable Mechanical Circulatory Support: Emerging Technological Innovations and Considerations to Enable Evolution of the Field.

The field of durable mechanical circulatory support (MCS) has undergone an incredible evolution over the past few decades, resulting in significant improvements in longevity and quality of life for patients with advanced heart failure. Despite these successes, substantial opportunities for further improvements remain, including in pump design and ancillary technology, perioperative and postoperative management, and the overall patient experience. Ideally, durable MCS devices would be fully implantable, automatically controlled, and minimize the need for anticoagulation. Reliable and long-term total artificial hearts for biventricular support would be available; and surgical, perioperative, and postoperative management would be informed by the individual patient phenotype along with computational simulations. In this review, we summarize emerging technological innovations in these areas, focusing primarily on innovations in late preclinical or early clinical phases of study. We highlight important considerations that the MCS community of clinicians, engineers, industry partners, and venture capital investors should consider to sustain the evolution of the field.

Non-invasive Estimation of Pressure Drop Across Aortic Coarctations: Validation of 0D and 3D Computational Models with In Vivo Measurements.

Blood pressure gradient ( Δ P ) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of Δ P estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N = 17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. Δ P across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. The 0D simulations were extremely efficient ( ∼ 15 s computation time) compared to 3D simulations ( ∼ 30 h computation time on a cluster). However, the 0D Δ P estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as Δ P ≥ 20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Non-invasive estimation of pressure drop across aortic coarctations: validation of 0D and 3D computational models with in vivo measurements.

Purpose: Blood pressure gradient (ΔP) across an aortic coarctation (CoA) is an important measurement to diagnose CoA severity and gauge treatment efficacy. Invasive cardiac catheterization is currently the gold-standard method for measuring blood pressure. The objective of this study was to evaluate the accuracy of ΔP estimates derived non-invasively using patient-specific 0D and 3D deformable wall simulations. Methods: Medical imaging and routine clinical measurements were used to create patient-specific models of patients with CoA (N=17). 0D simulations were performed first and used to tune boundary conditions and initialize 3D simulations. ΔP across the CoA estimated using both 0D and 3D simulations were compared to invasive catheter-based pressure measurements for validation. Results: The 0D simulations were extremely efficient (~15 secs computation time) compared to 3D simulations (~30 hrs computation time on a cluster). However, the 0D ΔP estimates, unsurprisingly, had larger mean errors when compared to catheterization than 3D estimates (12.1 ± 9.9 mmHg vs 5.3 ± 5.4 mmHg). In particular, the 0D model performance degraded in cases where the CoA was adjacent to a bifurcation. The 0D model classified patients with severe CoA requiring intervention (defined as ΔP≥20 mmHg) with 76% accuracy and 3D simulations improved this to 88%. Conclusion: Overall, a combined approach, using 0D models to efficiently tune and launch 3D models, offers the best combination of speed and accuracy for non-invasive classification of CoA severity.

Circulatory Support: Artificial Muscles for the Future of Cardiovascular Assist Devices.

Artificial muscles enable the design of soft implantable devices which are poised to transform the way we mechanically support the heart today. Heart failure is a prevalent and deadly disease, which is treated with the implantation of rotary blood pumps as the only alternative to heart transplantation. The clinically used mechanical devices are associated with severe adverse events, which are reflected here in a comprehensive list of critical requirements for soft active devices of the future: low power, no blood contact, pulsatile support, physiological responsiveness, high cycle life, and less-invasive implantation. In this review, prior art in artificial muscles for their applicability in the short and long term is investigated and critically evaluated. The main challenges regarding the effectiveness, controllability, and implantability of recently proposed actuators are highlighted and the future perspectives for attachment, physiological responsiveness, durability, and biodegradability as well as equitable design considerations are explored.

Decoupling Transmission and Transduction for Improved Durability of Highly Stretchable, Soft Strain Sensing: Applications in Human Health Monitoring.

This work presents a modular approach to the development of strain sensors for large deformations. The proposed method separates the extension and signal transduction mechanisms using a soft, elastomeric transmission and a high-sensitivity microelectromechanical system (MEMS) transducer. By separating the transmission and transduction, they can be optimized independently for application-specific mechanical and electrical performance. This work investigates the potential of this approach for human health monitoring as an implantable cardiac strain sensor for measuring global longitudinal strain (GLS). The durability of the sensor was evaluated by conducting cyclic loading tests over one million cycles, and the results showed negligible drift. To account for hysteresis and frequency-dependent effects, a lumped-parameter model was developed to represent the viscoelastic behavior of the sensor. Multiple model orders were considered and compared using validation and test data sets that mimic physiologically relevant dynamics. Results support the choice of a second-order model, which reduces error by 73% compared to a linear calibration. In addition, we evaluated the suitability of this sensor for the proposed application by demonstrating its ability to operate on compliant, curved surfaces. The effects of friction and boundary conditions are also empirically assessed and discussed.

Framework for patient-specific simulation of hemodynamics in heart failure with counterpulsation support.

Despite being responsible for half of heart failure-related hospitalizations, heart failure with preserved ejection fraction (HFpEF) has limited evidence-based treatment options. Currently, a substantial clinical issue is that the disease etiology is very heterogenous with no patient-specific treatment options. Modeling can provide a framework for evaluating alternative treatment strategies. Counterpulsation strategies have the capacity to improve left ventricular diastolic filling by reducing systolic blood pressure and augmenting the diastolic pressure that drives coronary perfusion. Here, we propose a framework for testing the effectiveness of a soft robotic extra-aortic counterpulsation strategy using a patient-specific closed-loop hemodynamic lumped parameter model of a patient with HFpEF. The soft robotic device prototype was characterized experimentally in a physiologically pressurized (50-150 mmHg) soft silicone vessel and modeled as a combination of a pressure source and a capacitance. The patient-specific model was created using open-source software and validated against hemodynamics obtained by imaging of a patient (male, 87 years, HR = 60 bpm) with HFpEF. The impact of actuation timing on the flows and pressures as well as systolic function was analyzed. Good agreement between the patient-specific model and patient data was achieved with relative errors below 5% in all categories except for the diastolic aortic root pressure and the end systolic volume. The most effective reduction in systolic pressure compared to baseline (147 vs. 141 mmHg) was achieved when actuating 350 ms before systole. In this case, flow splits were preserved, and cardiac output was increased (5.17 vs. 5.34 L/min), resulting in increased blood flow to the coronaries (0.15 vs. 0.16 L/min). Both arterial elastance (0.77 vs. 0.74 mmHg/mL) and stroke work (11.8 vs. 10.6 kJ) were decreased compared to baseline, however left atrial pressure increased (11.2 vs. 11.5 mmHg). A higher actuation pressure is associated with higher systolic pressure reduction and slightly higher coronary flow. The soft robotic device prototype achieves reduced systolic pressure, reduced stroke work, slightly increased coronary perfusion, but increased left atrial pressures in HFpEF patients. In future work, the framework could include additional physiological mechanisms, a larger patient cohort with HFpEF, and testing against clinically used devices.

Elucidating tricuspid Doppler signal interpolation and its implication for assessing pulmonary hypertension.

Doppler echocardiography plays a central role in the assessment of pulmonary hypertension (PAH). We aim to improve quality assessment of systolic pulmonary arterial pressure (SPAP) by applying a cubic polynomial interpolation to digitized tricuspid regurgitation (TR) waveforms. Patients with PAH and advanced lung disease were divided into three cohorts: a derivation cohort (n = 44), a validation cohort (n = 71), an outlier cohort (n = 26), and a non-PAH cohort (n = 44). We digitized TR waveforms and analyzed normalized duration, skewness, kurtosis, and first and second derivatives of pressure. Cubic polynomial interpolation was applied to three physiology-driven phases: the isovolumic phase, ejection phase, and "shoulder" point phase. Coefficients of determination and a Bland-Altman analysis was used to assess bias between methods. The cubic polynomial interpolation of the TR waveform correlated strongly with expert read right ventricular systolic pressure (RVSP) with R 2 > 0.910 in the validation cohort. The biases when compared to invasive SPAP measured within 24 h were 6.03 [4.33; 7.73], -2.94 [1.47; 4.41], and -3.11 [-4.52; -1.71] mmHg, for isovolumic, ejection, and shoulder point interpolations, respectively. In the outlier cohort with more than 30% difference between echocardiographic estimates and invasive SPAP, cubic polynomial interpolation significantly reduced underestimation of RVSP. Cubic polynomial interpolation of the TR waveform based on isovolumic or early ejection phase may improve RVSP estimates.

Right Ventricular Function and T1-Mapping in Boys With Duchenne Muscular Dystrophy.

BACKGROUND: Clinical management of boys with Duchenne muscular dystrophy (DMD) relies on in-depth understanding of cardiac involvement, but right ventricular (RV) structural and functional remodeling remains understudied. PURPOSE: To evaluate several analysis methods and identify the most reliable one to measure RV pre- and postcontrast T1 (RV-T1) and to characterize myocardial remodeling in the RV of boys with DMD. STUDY TYPE: Prospective. POPULATION: Boys with DMD (N = 27) and age-/sex-matched healthy controls (N = 17) from two sites. FIELD STRENGTH/SEQUENCE: 3.0 T using balanced steady state free precession, motion-corrected phase sensitive inversion recovery and modified Look-Locker inversion recovery sequences. ASSESSMENT: Biventricular mass (Mi), end-diastolic volume (EDVi) and ejection fraction (EF) assessment, tricuspid annular excursion (TAE), late gadolinium enhancement (LGE), pre- and postcontrast myocardial T1 maps. The RV-T1 reliability was assessed by three observers in four different RV regions of interest (ROI) using intraclass correlation (ICC). STATISTICAL TESTS: The Wilcoxon rank sum test was used to compare RV-T1 differences between DMD boys with negative LGE(-) or positive LGE(+) and healthy controls. Additionally, correlation of precontrast RV-T1 with functional measures was performed. A P-value <0.05 was considered statistically significant. RESULTS: A 1-pixel thick RV circumferential ROI proved most reliable (ICC > 0.91) for assessing RV-T1. Precontrast RV-T1 was significantly higher in boys with DMD compared to controls. Both LGE(-) and LGE(+) boys had significantly elevated precontrast RV-T1 compared to controls (1543 [1489-1597] msec and 1550 [1402-1699] msec vs. 1436 [1399-1473] msec, respectively). Compared to healthy controls, boys with DMD had preserved RVEF (51.8 [9.9]% vs. 54.2 [7.2]%, P = 0.31) and significantly reduced RVMi (29.8 [9.7] g vs. 48.0 [15.7] g), RVEDVi (69.8 [29.7] mL/m2 vs. 89.1 [21.9] mL/m2 ), and TAE (22.0 [3.2] cm vs. 26.0 [4.7] cm). Significant correlations were found between precontrast RV-T1 and RVEF (ß = -0.48%/msec) and between LV-T1 and LVEF (ß = -0.51%/msec). DATA CONCLUSION: Precontrast RV-T1 is elevated in boys with DMD compared to healthy controls and is negatively correlated with RVEF. LEVEL OF EVIDENCE: 1 TECHNICAL EFFICACY: Stage 2.

Real-Time Ventricular Volume Measured Using the Intracardiac Electromyogram.

Left ventricular end-diastolic volume (EDV) is an important parameter for monitoring patients with left ventricular assist devices (LVADs) and might be useful for automatic LVAD work adaptation. However, continuous information on the EDV is unavailable to date. The depolarization amplitude (DA) of the noncontact intracardiac electromyogram (iEMG) is physically related to the EDV. Here, we show how a left ventricular (LV) volume sensor based on the iEMG might provide beat-wise EDV estimates. The study was performed in six pigs while undergoing a series of controlled changes in hemodynamic states. The LV volume sensor consisted of four conventional pacemaker electrodes measuring the far-field iEMG inside the LV blood pool, using a novel unipolar amplifier. Simultaneously, noninvasive measurements of EDV and hematocrit were recorded. The proposed EDV predictor was tested for statistical significance using a mixed-effect model and associated confidence intervals. A statistically significant (p = 3e-07) negative correlation was confirmed between the DA of the iEMG and the EDV as measured by electric impedance at a slope of -0.069 (-0.089, -0.049) mV/mL. The DA was slightly decreased by increased hematocrit (p = 0.039) and moderately decreased with the opening of the thorax (p = 0.003). The DA of the iEMG proved to be a significant, independent predictor of EDV. The proposed LV volume sensor is simple to integrate into the inflow cannula of an LVAD and thus has the potential to inform the clinician about the state of LV volume in real time and to automatically control the LVAD.

On the impact of vessel wall stiffness on quantitative flow dynamics in a synthetic model of the thoracic aorta.

Aortic wall stiffening is a predictive marker for morbidity in hypertensive patients. Arterial pulse wave velocity (PWV) correlates with the level of stiffness and can be derived using non-invasive 4D-flow magnetic resonance imaging (MRI). The objectives of this study were twofold: to develop subject-specific thoracic aorta models embedded into an MRI-compatible flow circuit operating under controlled physiological conditions; and to evaluate how a range of aortic wall stiffness impacts 4D-flow-based quantification of hemodynamics, particularly PWV. Three aorta models were 3D-printed using a novel photopolymer material at two compliant and one nearly rigid stiffnesses and characterized via tensile testing. Luminal pressure and 4D-flow MRI data were acquired for each model and cross-sectional net flow, peak velocities, and PWV were measured. In addition, the confounding effect of temporal resolution on all metrics was evaluated. Stiffer models resulted in increased systolic pressures (112, 116, and 133 mmHg), variations in velocity patterns, and increased peak velocities, peak flow rate, and PWV (5.8-7.3 m/s). Lower temporal resolution (20 ms down to 62.5 ms per image frame) impacted estimates of peak velocity and PWV (7.31 down to 4.77 m/s). Using compliant aorta models is essential to produce realistic flow dynamics and conditions that recapitulated in vivo hemodynamics.

Continuous Heart Volume Monitoring by Fully Implantable Soft Strain Sensor.

Cardiothoracic open-heart surgery has revolutionized the treatment of cardiovascular disease, the leading cause of death worldwide. After the surgery, hemodynamic and volume management can be complicated, for example in case of vasoplegia after endocarditis. Timely treatment is crucial for outcomes. Currently, treatment decisions are made based on heart volume, which needs to be measured manually by the clinician each time using ultrasound. Alternatively, implantable sensors offer a real-time window into the dynamic function of our body. Here it is shown that a soft flexible sensor, made with biocompatible materials, implanted on the surface of the heart, can provide continuous information of the heart volume after surgery. The sensor works robustly for a period of two days on a tensile machine. The accuracy of measuring heart volume is improved compared to the clinical gold standard in vivo, with an error of 7.1 mL for the strain sensor versus impedance and 14.0 mL versus ultrasound. Implanting such a sensor would provide essential, continuous information on heart volume in the critical time following the surgery, allowing early identification of complications, facilitating treatment, and hence potentially improving patient outcome.