Cardiovascular Engineering and Technology最新文献

Purpose: Fluid-structure interaction (FSI) models are more commonly applied in medical research as computational power is increasing. However, understanding the accuracy of FSI models is crucial, especially in the context of heart valve disease in patient-specific models. Therefore, this study aimed to create a multi-modal benchmarking data set for cardiac-inspired FSI models, based on clinically important parameters, such as the pressure, velocity, and valve opening, with an in vitro phantom setup.

Method: An in vitro setup was developed with a 3D-printed phantom mimicking the left heart, including a deforming mitral valve. A range of pulsatile flows were created with a computer-controlled motor-and-pump setup. Catheter pressure measurements, magnetic resonance imaging (MRI), and echocardiography (Echo) imaging were used to measure pressure and velocity in the domain. Furthermore, the valve opening was quantified based on cine MRI and Echo images.

Result: The experimental setup, with 0.5% cycle-to-cycle variation, was successfully built and six different flow cases were investigated. Higher velocity through the mitral valve was observed for increased cardiac output. The pressure difference across the valve also followed this trend. The flow in the phantom was qualitatively assessed by the velocity profile in the ventricle and by streamlines obtained from 4D phase-contrast MRI.

Conclusion: A multi-modal set of data for validation of FSI models has been created, based on parameters relevant for diagnosis of heart valve disease. All data is publicly available for future development of computational heart valve models.

Introduction: The precise mechanism of rupture in abdominal aortic aneurysms (AAAs) has not yet been uncovered. The phenomenological failure criterion of the coefficient of proportionality between von Mises stress and tissue strength does not account for any mechanistic foundation of tissue fracture. Experimental studies have shown that arterial failure is a stepwise process of fibrous delamination (mode II) and kinking (mode I) between layers. Such a mechanism has not previously been considered for AAA rupture.

Methods: In the current study we consider both von Mises stress in the wall, in addition to interlayer tractions and delamination using cohesive zone models. Firstly, we present a parametric investigation of the influence of a range of AAA anatomical features on the likelihood of elevated interlayer traction and delamination.

Results: We observe in several cases that the location of peak von Mises stress and tangential traction coincide. Our simulations also reveal however, that peak von Mises and intramural tractions are not coincident for aneurysms with Length/Radius less than 2 (short high-curvature aneurysms) and for aneurysms with symmetric intraluminal thrombus (ILT). For an aneurysm with (L/R = 2.0), the peak ${\sigma }_{\mathrm{vm}}$ moves slightly towards the origin while the peak $T_t$ is near the peak bulge with a separation distance of ~ 17 mm. Additionally, we present three patient-specific AAA models derived directly from CT scans, which also illustrate that the location of von Mises stress does not correlate with the point of interlayer delamination.

Conclusion: This study suggests that incorporating cohesive zone models into clinical based FE analyses may capture a greater proportion of ruptures in-silico.

Background and objective: Advanced material models and material characterization of soft biological tissues play an essential role in pre-surgical planning for vascular surgeries and transcatheter interventions. Recent advances in heart valve engineering, medical device and patch design are built upon these models. Furthermore, understanding vascular growth and remodeling in native and tissue-engineered vascular biomaterials, as well as designing and testing drugs on soft tissue, are crucial aspects of predictive regenerative medicine. Traditional nonlinear optimization methods and finite element (FE) simulations have served as biomaterial characterization tools combined with soft tissue mechanics and tensile testing for decades. However, results obtained through nonlinear optimization methods are reliable only to a certain extent due to mathematical limitations, and FE simulations may require substantial computing time and resources, which might not be justified for patient-specific simulations. To a significant extent, machine learning (ML) techniques have gained increasing prominence in the field of soft tissue mechanics in recent years, offering notable advantages over conventional methods. This review article presents an in-depth examination of emerging ML algorithms utilized for estimating the mechanical characteristics of soft biological tissues and biomaterials. These algorithms are employed to analyze crucial properties such as stress-strain curves and pressure-volume loops. The focus of the review is on applications in cardiovascular engineering, and the fundamental mathematical basis of each approach is also discussed.

Methods: The review effort employed two strategies. First, the recent studies of major research groups actively engaged in cardiovascular soft tissue mechanics are compiled, and research papers utilizing ML and deep learning (DL) techniques were included in our review. The second strategy involved a standard keyword search across major databases. This approach provided 11 relevant ML articles, meticulously selected from reputable sources including ScienceDirect, Springer, PubMed, and Google Scholar. The selection process involved using specific keywords such as "machine learning" or "deep learning" in conjunction with "soft biological tissues", "cardiovascular", "patient-specific," "strain energy", "vascular" or "biomaterials". Initially, a total of 25 articles were selected. However, 14 of these articles were excluded as they did not align with the criteria of focusing on biomaterials specifically employed for soft tissue repair and regeneration. As a result, the remaining 11 articles were categorized based on the ML techniques employed and the training data utilized.

Results: ML techniques utilized for assessing the mechanical characteristics of soft biological tissues and biomaterials are broadly classified into two categories: standard ML algorithms an

Purpose: Myocardial strain, as a crucial quantitative indicator of myocardial deformation, can detect the changes of cardiac function earlier than parameters such as ejection fraction (EF). It has reported that cardiac magnetic resonance(CMR) and post-processing software possess the ability to obtain the stability and repeatability strain values. Recently, the normal strain values range of people are debatable, especially in the Chinese population. Therefore, we aim to explore the ventricular characteristics and the myocardial strain values of the Chinese people by using the cardiac magnetic resonance feature tracking (CMR-FT). Additionally, we attempted to use the myocardial and chordae tendineae contours to calculate the ventricular volumes by the CMR-FT. This study may provide valuable insights into the application of CMR-FT in tracking the ventricular characteristics and myocardial strain for Chinese population, especially in suggesting an referable myocardial strain parameters of the Chinese.

Methods: A total of 109 healthy Chinese individuals (age range: 18 to 58 years; 52 males and 57 females) underwent 3.0T CMR to acquire the cardiac images. The commercial post-processing software was employed to analyse the image sequence by semi-automatic processing, then the biventricular morphology (End-Diastolic Volume, EDV; EDV/Body Surface Area, EDV/BSA), function(EF; Cardiac Output, CO; Cardiac Index, CI) and strain(Radial Strain, RS; Circumferential Strain, CS; Longitudinal Strain, LS) values were obtained.The biventricular myocardial strain values were stratified according to the age and gender. The Left Ventricular( LV base, mid, apex) and myocardial strain values of three coronary artery areas were calculated based on the the strain value of LV American Heart Association(AHA) 16 segments.

Results: It was shown that the females had larger LV globe strain values compared with the males (LVGPRS: 42.0 ± 8.5 versus 33.6 ± 6.2%, P < 0.001; LVGPCS: -21.2 ± 2.1 versus - 19.7 ± 2.3%, P < 0.001; LVGPLS: -16.4 ± 2.6 versus - 14.6 ± 2.2%, P < 0.001;). Moreover, the differences in RS, CS, and LS among the LV myocardium 16 segments were obvious. However, the right ventricle (RV) strain values showed non-normal distribution in the volunteers of this research.

Conclusions: Here, we successfully tracked the characteristics of bilateral ventricles in healthy Chinese populations through using the 3.0T CMR. We confirmed that there was a gender difference in LV Globe Strain values. In addition, we obtained strain values for each myocardial segment of the LV and different coronary artery regions based on the AHA 16 segments method, Our results also showed that the RV strain values with a non-normal distribution, and RV global strain values were not related to the gender and age. Furthermore, LVGPRS, LVGPLS, and RVGPRS were significantly correlated with BMI, CO, CI, and EDV in t

Purpose: Variations in the anatomy of pulmonary veins can influence selection of approaches of atrial fibrillation catheter ablation. Therefore, preprocedural evaluation and knowledge of pulmonary veins anatomy is crucial for proper mapping and the successful ablation of atrial fibrillation. The aim of this observational study was to assess CT angiography scans and perform detailed analysis of pulmonary veins morphology in patients scheduled for catheter ablation of atrial fibrillation.

Methods: CT angiography was performed in 771 individuals (223 females, 548 males, mean age 58.4 ± 10.7 years). Pulmonary veins anatomy was evaluated using 3D models. The patterns used for evaluation included typical anatomy with four separate pulmonary veins, a common left ostium, and various types of accessory veins either alone or in combination with common left ostia.

Results: An anatomical variant with common left ostium was observed as the most prevalent anatomy (44%). The typical variant was observed in 34.8% of patients. Accessory pulmonary veins were observed predominantly on the right side. The prevalence of anatomical variants did not differ between sexes with the exception of the unclassifiable category U (4.4% vs. 9%, p < 0.05).

Conclusions: Our study shows that a considerable number of atypical anatomies is present in patients undergoing AF catheter ablation. This knowledge may influence the choice of instrumentation. The data could be possibly helpful also in development of new ablation techniques.

Purpose: Biomaterial and stem cell delivery are promising approaches to treating myocardial infarction. However, the mechanical and biochemical mechanisms underlying the therapeutic benefits require further clarification. This study aimed to assess the deformation of stem cells injected with the biomaterial into the infarcted heart.

Methods: A microstructural finite element model of a mid-wall infarcted myocardial region was developed from ex vivo microcomputed tomography data of a rat heart with left ventricular infarct and intramyocardial biomaterial injectate. Nine cells were numerically seeded in the injectate of the microstructural model. The microstructural and a previously developed biventricular finite element model of the same rat heart were used to quantify the deformation of the cells during a cardiac cycle for a biomaterial elastic modulus (E_inj) ranging between 4.1 and 405,900 kPa.

Results: The transplanted cells' deformation was largest for E_inj = 7.4 kPa, matching that of the cells, and decreased for an increase and decrease in E_inj. The cell deformation was more sensitive to E_inj changes for softer (E_inj ≤ 738 kPa) than stiffer biomaterials.

Conclusions: Combining the microstructural and biventricular finite element models enables quantifying micromechanics of transplanted cells in the heart. The approach offers a broader scope for in silico investigations of biomaterial and cell therapies for myocardial infarction and other cardiac pathologies.

Purpose: One in four deaths worldwide is due to thromboembolic disease; that is, one in four people die from blood clots first forming and then breaking off or embolizing. Once broken off, clots travel downstream, where they occlude vital blood vessels such as those of the brain, heart, or lungs, leading to strokes, heart attacks, or pulmonary embolisms, respectively. Despite clots' obvious importance, much remains to be understood about clotting and clot embolization. In our work, we take a first step toward untangling the mystery behind clot embolization and try to answer the simple question: "What makes blood clots break off?"

Methods: To this end, we conducted experimentally-informed, back-of-the-envelope computations combining fracture mechanics and phase-field modeling. We also focused on deep venous clots as our model problem.

Results: Here, we show that of the three general forces that act on venous blood clots-shear stress, blood pressure, and wall stretch-induced interfacial forces-the latter may be a critical embolization force in occlusive and non-occlusive clots, while blood pressure appears to play a determinant role only for occlusive clots. Contrary to intuition and prior reports, shear stress, even when severely elevated, appears unlikely to cause embolization.

Conclusion: This first approach to understanding the source of blood clot bulk fracture may be a critical starting point for understanding blood clot embolization. We hope to inspire future work that will build on ours and overcome the limitations of these back-of-the-envelope computations.

Purpose

The development of new endovascular technologies for transarterial embolization has relied on animal studies to validate efficacy before clinical trials are undertaken. Because embolizations in animals and patients are primarily conducted with fluoroscopy alone, local hemodynamic changes are not assessed during testing. However, such hemodynamic metrics could be important indicators of procedure efficacy that could support improved patient outcomes, such as via the determination of procedural endpoints. The purpose of this study is to create a high-fidelity benchtop system for multiparametric (i.e., hemodynamic and imaging) assessment of transarterial embolization procedures.

Methods

The benchtop system consists of a 3D printed, anatomically accurate vascular phantom; a flow loop with a cardiac output simulator; a high-speed video camera; and pressure transducers and flow meters. This system enabled us to vary the heart rate and blood pressure and to simulate clinically relevant hemodynamic states, such as healthy adult, aortic regurgitation, and hypovolemic shock.

Results

With our radiation-free angiography-mimetic imaging system, we could simultaneously assess gauge pressure and flow values during transarterial embolization. We demonstrated the feasibility of recapitulating the digital subtraction angiography workflow. Finally, we highlighted the utility of this system by characterizing the relationship between an imaging-based metric of procedural endpoint and intravascular flow. We also characterized hemodynamic changes associated with particle embolization within a branch of the hepatic artery and found them to be within reported patient data.

Conclusion

Our benchtop vascular system was low-cost and reproduced transarterial embolization-related hemodynamic phenomena with high fidelity. We believe that this novel platform enables the characterization of patient physiology, novel catheterization devices, and techniques.

Purpose

Neo-sinus flow stasis has ben correlated with transcatheter heart valve (THV) thrombosis severity and occurrence. Standard benchtop flow field quantification techniques require optical access or modified prosthesis models that may not reflect the true nature of the original valve. En face and fluoroscopic videodensitometry enable visualization of washout in regions otherwise unviewable.

Methods

This study compares two in vitro methods of assessing flow stasis in scenarios with insufficient optical access for traditional techniques such as particle image velocimetry (PIV). A series of seven paired experiments were conducted using a previously described laser-enhanced video densitometry (LEVD) and fluoroscopic video densitometry (FVD). Both sets of experiments were analyzed to calculate washout time as a measure of flow stasis. A novel flow stasis measure termed contrast attenuation ratio (CAR) is proposed as a viable single measure of flow stasis obtainable from only a small number of cardiac cycles of in vitro or in vivo fluoroscopic data. Retrospective fluoroscopic datasets (n = 72) were analyzed to assess the feasibility of obtaining this metric from routine clinical practice and its ability to stratify results.

Results

Neo-sinus flow stasis calculated from in vitro fluoroscopy was well correlated with LEVD (r² = 0.77, p = 0.009). The newly proposed CAR metric showed good agreement with the commonly used “washout time” measure of flow stasis (r² = 0.91, p < 0.001) while allowing for assessment with incomplete or truncated data. As a proof of concept, CAR was measured in 72 consecutive retrospective fluoroscopic datasets. CAR averaged 10.6 ± 4.6% with a range of 1.5–20.3% in these patients.

Conclusions

This study demonstrates two in vitro methods that can be used to assess relative flow stasis in otherwise optically inaccessible regions surrounding cardiac or vascular implants. In addition, the fluoroscopic benchtop technique was used to validate a metric that allows for extension to routine clinical fluoroscopy. This contrast attenuation ratio (CAR) metric was found to be both accurate and clinically obtainable, and potentially offers a new method for valve thrombosis risk stratification.

Purposr: This study created 3D CFD models of the Norwood procedure for hypoplastic left heart syndrome (HLHS) using standard angiography and echocardiogram data to investigate the impact of shunt characteristics on pulmonary artery (PA) hemodynamics. Leveraging routine clinical data offers advantages such as availability and cost-effectiveness without subjecting patients to additional invasive procedures.

Methods: Patient-specific geometries of the intrathoracic arteries of two Norwood patients were generated from biplane cineangiograms. "Virtual surgery" was then performed to simulate the hemodynamics of alternative PA shunt configurations, including shunt type (modified Blalock-Thomas-Taussig shunt (mBTTS) vs. right ventricle-to-pulmonary artery shunt (RVPAS)), shunt diameter, and pulmonary artery anastomosis angle. Left-right pulmonary flow differential, Q_p/Q_s, time-averaged wall shear stress (TAWSS), and oscillatory shear index (OSI) were evaluated.

Results: There was strong agreement between clinically measured data and CFD model output throughout the patient-specific models. Geometries with a RVPAS tended toward more balanced left-right pulmonary flow, lower Q_p/Q_s, and greater TAWSS and OSI than models with a mBTTS. For both shunt types, larger shunts resulted in a higher Q_p/Q_s and higher TAWSS, with minimal effect on OSI. Low TAWSS areas correlated with regions of low flow and changing the PA-shunt anastomosis angle to face toward low TAWSS regions increased TAWSS.

Conclusion: Excellent correlation between clinically measured and CFD model data shows that 3D CFD models of HLHS Norwood can be developed using standard angiography and echocardiographic data. The CFD analysis also revealed consistent changes in PA TAWSS, flow differential, and OSI as a function of shunt characteristics.