Left Ventricular Assist Device Flow Pattern Analysis Using a Novel Model Incorporating Left Ventricular Pulsatility

Our current understanding of flow through the circuit of left ventricular assist device (LVAD), left ventricle and ascending aorta remains incompletely understood. Computational fluid dynamics, which allow for analysis of flow in the cardiovascular system, have been used for this purpose, although current simulation models have failed to fully incorporate the interplay between the pulsatile left ventricle and continuous-flow generated by the LVAD. Flow-through the LVAD is dependent on the interaction between device and patient-specific factors with suboptimal flow patterns evoking increased risk of LVAD-related complications. Computational fluid dynamics can be used to analyze how different pump and patient factors affect flow patterns in the left ventricle and the aorta. Computational fluid dynamics simulations were carried out on a patient with a HeartMate II. Simulations were also conducted for theoretical scenarios substituting HeartWare HVAD, HeartMate 3 (HM3) in continuous mode and HM3 with Artificial Pulse. An anatomical model of the patient was reconstructed from computed tomography (CT) images, and the LVAD outflow was used as the inflow boundary condition. The LVAD outflow was calculated separately using a lumped-parameter-model of the systemic circulation, which was calibrated to the patient based on the patient-specific ventricular volume change reconstructed from 4 dimensional computed tomography and pulmonary capillary wedge pressure tracings. The LVADs were implemented in the lumped-parameter-model via published pressure head versus flow (H-Q) curves. To quantify the flushing effect, virtual contrast agent was released in the ascending aorta and its flushing over the cycles was quantified. Shear stress acting on the aortic endothelium and shear rate in the bloodstream were also quantified as indicators of normal/abnormal blood flow, especially the latter being a biomarker of platelet activation and hemolysis. LVAD speeds for the HVAD and HM3 were selected to match flow rates for the patient’s HMII (9,000 RPM for HMII, 5,500 RPM for HM3, and 2,200 RPM for HVAD), the cardiac outputs were 5.81 L/min, 5.83 L/min, and 5.92 L/min, respectively. The velocity of blood flow in the outflow cannula was higher in the HVAD than in the two HeartMate pumps with a cycle average (range) of 0.92 m/s (0.78–1.19 m/s), 0.91 m/s (0.86–1.00 m/s), and 1.74 m/s (1.40–2.24 m/s) for HMII, HM3, and HVAD, respectively. Artificial pulse increased the peak flow rate to 9.84 L/min for the HM3 but the overall cardiac output was 5.96 L/min, which was similar to the continuous mode. Artificial pulse markedly decreased blood stagnation in the ascending aorta; after six cardiac cycles, 48% of the blood was flushed out from the ascending aorta under the continuous operation mode while 60% was flushed under artificial pulse. Shear stress and shear rate in the aortic arch were higher with the HVAD compared to the HMII and HM3, respectively (shear stress: 1.76 vs. 1.33 vs. 1.33 Pa, shear rate: 136 vs. 91.5 vs. 89.4 s–1). Pump-specific factors such as LVAD type and programmed flow algorithms lead to unique flow patterns which influence blood stagnation, shear stress, and platelet activation. The pump-patient interaction can be studied using a novel computational fluid dynamics model to better understand and potentially mitigate the risk of downstream LVAD complications

OCT for the Identification of Vulnerable Plaque in Acute Coronary Syndrome

AbstractAfter 2 decades of development and use in interventional cardiology research, optical coherence tomography (OCT) has now become a core intravascular imaging modality in clinical practice. Its unprecedented spatial resolution allows visualization of the key components of the atherosclerotic plaque that appear to confer “vulnerability” to rupture—namely the thickness of the fibrous cap, size of the necrotic core, and the presence of macrophages. The utility of OCT in the evaluation of plaque composition can provide insights into the pathophysiology of acute coronary syndrome and the healing that occurs thereafter. A brief summary of the principles of OCT technology and a comparison with other intravascular imaging modalities is presented. The review focuses on the current evidence for the use of OCT in identifying vulnerable plaques in acute coronary syndrome and its limitations

Random boundaries: quantifying segmentation uncertainty in solutions to boundary-value problems

Engineering simulations using boundary-value partial differential equations often implicitly assume that the uncertainty in the location of the boundary has a negligible impact on the output of the simulation. In this work, we develop a novel method for describing the geometric uncertainty in image-derived models and use a naive method for subsequently quantifying a simulation's sensitivity to that uncertainty. A Gaussian random field is constructed to represent the space of possible geometries, based on image-derived quantities such as pixel size, which can then be used to probe the simulation's output space. The algorithm is demonstrated with examples from biomechanics where patient-specific geometries are often segmented from low-resolution, three-dimensional images. These examples show the method's wide applicability with examples using linear elasticity and fluid dynamics. We show that important biomechanical outputs of these example simulations, namely maximum principal stress and wall shear stress, can be highly sensitive to realistic uncertainties in geometry

Long Term Gait, Mobility, and Daily Living Outcomes after Orthopedic Surgery for Youth with Cerebral Palsy: Influence of Rehabilitation Dose and Setting

Background/Purpose: Cerebral palsy (CP) is a broad diagnostic description of early brain insult causing motor impairment. To help correct gait abnormalities, many children with CP undergo an orthopedic single event multi-level surgery (SEMLS). After surgery and most importantly SEMLS, rehabilitation is important to recovery. The purpose of this study was to examine the effects of post-op therapy setting and dose on functional mobility outcomes for youth with CP. Methods: Outcome measures included gait deviation index (GDI), walking speed, Pediatrics Outcomes Data Collection Instrument (PODCI), Gross Motor Function Mobility-D (GMFM-D). Data on post-op rehab therapy were retrieved from electronic medical records. Multiple Regression, Two-Way ANOVA, and Welch’s t-tests were used. Patient Sample: 74 cases were eligible. Average age at baseline gait analysis was 11.5, at surgery was 12, and at post-op gait analysis was 13.3 years old, with Gross Motor Function Classification System (GMFCS) levels I (9%), II (53%), III (34%), and IV (4%). Results: There was variability in therapy setting, with 33 different therapy centers. Higher burden of surgery was associated with more therapy sessions. Patients with low burden surgeries tended to improve in PODCI scores, but patients with high burden surgeries did not. These trends were not related to therapy dose, however, patients receiving Nemours Outpatient therapy had a positive association with PODCI gains. Similarly, patients who had low burden surgery improved GMFM-D and those with high burden did not. A minimal threshold of therapy dose was identified for cases with low burden surgery. Patients who attended 46 sessions or more saw GMFM-D improvements and patients who attended 25 sessions or fewer did not improve. Conclusion: Clinical practice recommends rehab therapy after SEMLS, but implementation is inconsistent. Post-op therapy varied widely by setting and number of sessions. As expected, youth who had low-burden surgery had less post-op therapy. Those above a minimum threshold and those at Nemours settings tended to show improvement at one-year post-op. At one year post-op, youth with high burden surgery demonstrated less gains, which is likely related to ongoing recovery in year two

3D Coronary Vessel Reconstruction from Bi-Plane Angiography Using Graph Convolutional Networks

X-ray coronary angiography (XCA) is used to assess coronary artery disease and provides valuable information on lesion morphology and severity. However, XCA images are 2D and therefore limit visualisation of the vessel. 3D reconstruction of coronary vessels is possible using multiple views, however lumen border detection in current software is performed manually resulting in limited reproducibility and slow processing time. In this study we propose 3DAngioNet, a novel deep learning (DL) system that enables rapid 3D vessel mesh reconstruction using 2D XCA images from two views. Our approach learns a coarse mesh template using an EfficientB3-UNet segmentation network and projection geometries, and deforms it using a graph convolutional network. 3DAngioNet outperforms similar automated reconstruction methods, offers improved efficiency, and enables modelling of bifurcated vessels. The approach was validated using state-of-the-art software verified by skilled cardiologists