A viscoelastic fluid-structure interaction model for carotid arteries under pulsatile flow

Effects of vessel wall mechanics on non-invasive evaluation of cardiovascular intrinsic frequencies

Intrinsic Frequency (IF) is a systems-based approach that provides valuable information for hemodynamic monitoring of the left ventricle (LV), the arterial system, and their coupling. Recent clinical studies have demonstrated the clinical significance of this method for prognosis and diagnosis of cardiovascular diseases. In IF analysis, two dominant instantaneous frequencies (ω₁ and ω₂) are extracted from arterial pressure waveforms. The value of ω₁ is related to the dynamics of the LV and the value of ω₂ is related to the dynamics of vascular function. This work investigates the effects of vessel wall mechanics on the accuracy and applicability of IFs extracted from vessel wall displacement waveforms compared to IFs extracted from pressure waveforms. In this study, we used a computational approach employing a fluid-structure interaction finite element method for various wall mechanics governed by linearly elastic, hyperelastic, and viscoelastic models. Results show that for vessels with elastic wall behavior, the error between displacement-based and pressure-based IFs is negligible. In the presence of stenosis or aneurysm in elastic arteries, the maximum errors associated with displacement-based IFs is less than 2%. For non-linear elastic and viscoelastic arteries, errors are more pronounced (where the former reaches up to 11% and the latter up to 27%). Our results ultimately suggest that displacement-based computations of ω₁ and ω₂ are accurate in vessels that exhibit elastic behavior (such as carotid arteries) and are suitable surrogates for pressure-based IFs. This is clinically significant because displacement-based IFs can be measured non-invasively.

Wall stress analyses in patients with ≥5 cm versus <5 cm ascending thoracic aortic aneurysm

OBJECTIVE

Current guidelines for elective surgery of ascending thoracic aortic aneurysms (aTAAs) use aneurysm size as primary determinant for risk stratification of adverse events. Biomechanically, dissection may occur when wall stress exceeds wall strength. Determining patient-specific aTAA wall stresses by finite element analysis can potentially predict patient-specific risk of dissection. This study compared peak wall stresses in patients with ≥5.0 cm versus <5.0 cm aTAAs to determine correlation between diameter and wall stress.

METHODS

Patients with aTAA ≥5.0 cm (n = 47) and <5.0 cm (n = 53) were studied. Patient-specific aneurysm geometries obtained from echocardiogram-gated computed tomography were meshed and prestress geometries determined. Peak wall stresses and stress distributions were determined using LS-DYNA finite element analysis software (LSTC Inc, Livermore, Calif), with user-defined fiber-embedded material models under systolic pressure.

RESULTS

Peak circumferential stresses at systolic pressure were 530 ± 83 kPa for aTAA ≥5.0 cm versus 486 ± 87 kPa for aTAA <5.0 cm (P = .07), whereas peak longitudinal stresses were 331 ± 57 kPa versus 310 ± 54 kPa (P = .08), respectively. For aTAA ≥5.0 cm, correlation between peak circumferential stresses and size was 0.41, whereas correlation between peak longitudinal wall stresses and size was 0.33. However, for aTAA <5.0 cm, correlation between peak circumferential stresses and size was 0.23, whereas correlation between peak longitudinal stresses and size was 0.14.

CONCLUSIONS

Peak patient-specific aTAA wall stresses overall were larger for ≥5.0 cm than aTAA <5.0 cm. Although some correlation between size and peak wall stresses was found in aTAA ≥5.0 cm, poor correlation existed between size and peak wall stresses in aTAA <5.0 cm. Patient-specific wall stresses are particularly important in determining patient-specific risk of dissection for aTAA <5.0 cm.

Deep learning based fully automatic segmentation of the left ventricular endocardium and epicardium from cardiac cine MRI

Background

The segmentation of cardiac medical images is a crucial step for calculating clinical indices such as wall thickness, ventricular volume, and ejection fraction.

Methods

In this study, we introduce a method named LsUnet that combines multi-channel, fully convolutional neural network, and annular shape level-set methods for efficiently segmenting cardiac cine magnetic resonance (MR) images. In this method, the multi-channel deep learning algorithm is applied to train the segmentation task to extract the left ventricle (LV) endocardial and epicardial contours. Next, the segmentation contours from the multi-channel deep learning method are incorporated into a level-set formulation, which is dedicated explicitly to detecting annular shapes to assure the segmentation's accuracy and robustness.

Results

The proposed automatic approach was evaluated on 95 volumes (total 1,076 slices, ~80% as for training datasets, ~20% 2D as for testing datasets). This combined multi-channel deep learning and annular shape level-set segmentation method achieved high accuracy with average Dice values reaching 92.15% and 95.42% for LV endocardium and epicardium delineation, respectively, in comparison to the reference standard (the manual segmentation).

Conclusions

A novel method for fully automatic segmentation of the LV endocardium and epicardium from different MRI datasets is presented. The proposed workflow is accurate and robust compared to the reference and other state-of-the-art methods.

Towards optimal flow diverter porosity for the treatment of intracranial aneurysm

PURPOSE

Low-porosity endovascular stents, known as flow diverters (FDs), have been proposed as an effective and minimally invasive treatment for sidewall intracranial aneurysms (IAs). Although it has been reported that the efficacy of a FD is substantially influenced by its porosity, clinical doctors would clearly prefer to do their interventions optimally based on refined quantitative data. This study focuses on the association between the porosity configurations and the FD efficacy, in order to provide practical data to help the clinical doctors optimize the interventions.

METHOD

Numerical simulations in fluid dynamics were performed using four patient-specific IA geometries, pulsatile velocity profiles and braided fully resolved FDs. The variation of velocity and wall shear stress within the IAs, were investigated in this study. Lattice Boltzmann method (LBM) was used to solve the main challenge centered on the diversity of spatial scales since the typical diameter of struts of FDs is only 25μm while the artery normally can be larger by a hundred times.

RESULTS

Numerical simulations revealed that the blood flow within IA sac was substantially reduced when the porosity is less than 86%. In particular, the flow condition within each IA sac is favorite to initialize thrombus formation when porosity is less than 70%.

CONCLUSION

Our study suggests the existence of a porosity threshold below which the efficacy of a FD will be sufficient for the patients to initialize the thrombus formation. Therefore, by estimating the porosity of FD on patient-specific information, it may be potentially to predict whether or the blood flow condition will successfully become prothrombotic after the FD intervention.

Wall stress on ascending thoracic aortic aneurysms with bicuspid compared with tricuspid aortic valve

OBJECTIVE

Guidelines for repair of bicuspid aortic valve-associated ascending thoracic aortic aneurysms have been changing, most recently to the same criteria as tricuspid aortic valve-ascending thoracic aortic aneurysms. Rupture/dissection occurs when wall stress exceeds wall strength. Recent studies suggest similar strength of bicuspid aortic valve versus tricuspid aortic valve-ascending thoracic aortic aneurysms; thus, comparative wall stress may better predict dissection in bicuspid aortic valve versus tricuspid aortic valve-ascending thoracic aortic aneurysms. Our aim was to determine whether bicuspid aortic valve-ascending thoracic aortic aneurysms had higher wall stresses than their tricuspid aortic valve counterparts.

METHODS

Patients with bicuspid aortic valve- and tricuspid aortic valve-ascending thoracic aortic aneurysms (bicuspid aortic valve = 17, tricuspid aortic valve = 19) greater than 4.5 cm underwent electrocardiogram-gated computed tomography angiography. Patient-specific 3-dimensional geometry was reconstructed and loaded to systemic pressure after accounting for prestress geometry. Finite element analyses were performed using the LS-DYNA solver (LSTC Inc, Livermore, Calif) with user-defined fiber-embedded material model to determine ascending thoracic aortic aneurysm wall stress.

RESULTS

Bicuspid aortic valve-ascending thoracic aortic aneurysms 99th-percentile longitudinal stresses were 280 kPa versus 242 kPa (P = .028) for tricuspid aortic valve-ascending thoracic aortic aneurysms in systole. These stresses did not correlate to diameter for bicuspid aortic valve-ascending thoracic aortic aneurysms (r = -0.004) but had better correlation to tricuspid aortic valve-ascending thoracic aortic aneurysms diameter (r = 0.677). Longitudinal stresses on sinotubular junction were significantly higher in bicuspid aortic valve-ascending thoracic aortic aneurysms than in tricuspid aortic valve-ascending thoracic aortic aneurysms (405 vs 329 kPa, P = .023). Bicuspid aortic valve-ascending thoracic aortic aneurysm 99th-percentile circumferential stresses were 548 kPa versus 462 kPa (P = .033) for tricuspid aortic valve-ascending thoracic aortic aneurysms, which also did not correlate to bicuspid aortic valve-ascending thoracic aortic aneurysm diameter (r = 0.007).

CONCLUSIONS

Circumferential and longitudinal stresses were greater in bicuspid aortic valve- than tricuspid aortic valve-ascending thoracic aortic aneurysms and were more pronounced in the sinotubular junction. Peak wall stress did not correlate with bicuspid aortic valve-ascending thoracic aortic aneurysm diameter, suggesting diameter alone in this population may be a poor predictor of dissection risk. Our results highlight the need for patient-specific aneurysm wall stress analysis for accurate dissection risk prediction.

Investigating the impact of non-Newtonian blood models within a heart pump

A detailed computational fluid dynamics (CFD) study of transient, turbulent blood flow through a positive displacement left ventricular assist device is performed. Two common models for non-Newtonian blood flow are compared to the Newtonian model to investigate their impact on predicted levels of shear rate and wall shear stress. Given that both parameters are directly relevant to the evaluation of risk from thrombus and haemolysis, there is a need to assess the sensitivity to modelling non-Newtonian flow effects within a pulsatile turbulent flow, in order to identify levels of uncertainly in CFD. To capture the effects of turbulence, the elliptic blending Reynolds stress model is used in the present study, on account of superior performance of second moment closure schemes previously identified by the present authors. The CFD configuration includes two cyclically rotating valves and a moving pusher plate to periodically vary the chamber volume. An overset mesh algorithm is used for each instance of mesh motion, and a zero gap technique was employed to ensure full valve closure. The left ventricular assist device was operated at a pumping rate of 86 BPM (beats per minute) and a systolic duration of 40% of the pumping cycle, in line with existing experimental data to which comparisons are made. The sensitivity of the variable viscosity models is investigated in terms of mean flow field, levels of turbulence and global shear rate, and a non-dimensional index is used to directly evaluate the impact of non-Newtonian effects. The clinical relevance of the results is reported along with a discussion of modelling uncertainties, observing that the turbulent kinetic energy is generally predicted to be higher in non-Newtonian flow than that observed in Newtonian flow. Copyright © 2016 John Wiley & Sons, Ltd.