Cardiovascular Engineering and Technology最新文献

Introduction: In vivo estimation of material properties of arterial tissue can provide essential insights into the development and progression of cardiovascular diseases. Furthermore, these properties can be used as an input to finite element simulations of potential medical treatments.

Materials and methods: This study uses non-invasively measured pressure, diameter and wall thickness of human common carotid arteries (CCAs) acquired in 103 healthy subjects. A non-linear optimization was performed to estimate material parameters of two different constitutive models: a phenomenological, isotropic model and a structural, anisotropic model. The effect of age, sex, body mass index and blood pressure on the parameters was investigated.

Results and conclusion: Although both material models were able to model in vivo arterial behaviour, the structural model provided more realistic results in the supra-physiological domain. The phenomenological model predicted very high deformations for pressures above the systolic level. However, the phenomenological model has fewer parameters that were shown to be more robust. This is an advantage when only the physiological domain is of interest. The effect of stiffening with age, BMI and blood pressure was present for women, but not always for men. In general, sex had the biggest effect on the mechanical properties of CCAs. Stiffening trends with age, BMI and blood pressure were present but not very strong. The intersubject variability was high. Therefore, it can be concluded that finding a representative set of parameters for a certain age or BMI group would be very challenging. Instead, for purposes of patient-specific modelling of surgical procedures, we currently advise the use of patient-specific parameters.

Purpose: Pulmonary valve (PV) monocusp reconstruction in transannular patch (TAP) right ventricular outflow tract (RVOT) repair for Tetralogy of Fallot has variable clinical outcomes across different surgical approaches. The study purpose was to systematically evaluate how monocusp leaflet design parameters affect valve function in-vitro.

Methods: A 3D-printed, disease-specific RVOT model was tested under three infant physiological conditions. Monocusps were sewn into models with the native main pulmonary artery (MPA) forming backwalls that constituted 40% and 50% of the reconstructed circumference for z-score zero PV annulus and MPA diameters (native PV z-score - 3.52 and - 2.99 for BSA 0.32m²). Various leaflet free edge lengths (FEL) (relative to backwall), positions (relative to PV STJ), and scallop depths were investigated across both models. Pressure gradient, regurgitation, and coaptation were analyzed with descriptive statistics and regression models.

Results: Increasing FEL beyond 100% of the MPA backwall decreased gradient but mildly increased regurgitation to a peak of 25%. Positioning the free edge 2 mm past the STJ mildly increased gradient for each FEL without significantly changing regurgitation compared to STJ placement. Scalloping leaflets trivially affected performance. Pre-folding leaflets improved mobility and slightly reduced gradient.

Conclusions: Balancing gradient, regurgitation, and oversizing for growth, a set of leaflet designs have been selected for pre-clinical evaluation. Designs with leaflet widths 140-160% in the 40% backwall model (110-120% in the 50% backwall), positioned at or 2 mm past the STJ, demonstrated the best results. The next stage of ex-vivo testing will additionally consider native RVOT distensibility, native leaflet interactions, and TAP characteristics.

Purpose: Bio-impedance analysis (BIA) has been widely investigated for hemodynamic monitoring. However, previous works rarely modelled two synchronously pulsatile arteries (representing the radial and ulnar arteries) in the wrist/forearm model. This work aims to clarify and quantify the influences of two pulsatile arteries on BIA.

Methods: First, two blood-filled arteries were structured in a 3D wrist segment using the finite element method (FEM). Afterwards, an easy-to-produce two-arteries artificial wrist was fabricated with two components: gelatine-based surrounding tissue phantom and saline blood phantom. A syringe driver was utilised to constrict the arteries, and the impedance signals were measured using a Multi-frequency Impedance Analyser (MFIA).

Results: Both simulation and experimental results demonstrated the non-negligible influences of the ulnar artery on the overall BIA, inducing unwanted resistance changes to the acquired signals from the radial artery. The phantom experiments revealed the summation of the individual resistance changes caused by a single pulsatile artery was approximately equal to the measured resistance change caused by two synchronously pulsatile arteries, confirming the measured impedance signal at the wrist contains the pulsatile information from both arteries.

Conclusion: This work is the first simulation and phantom investigation into two synchronously pulsatile arteries under BIA in the distal forearm, providing a better insight and understanding in the morphology of measured impedance signals. Future research can accordingly select either a small spacing 4-spot electrode configuration for a single artery sensing or a band electrode configuration for overall pulsatile arteries sensing. A more accurate estimation of blood volume change and pulse wave analysis (PWA) could help to develop cuffless blood pressure measurement (BPM).

Purpose: Bioprosthetic Heart Valves (BHVs) are widely used in clinical practice, showing promising outcomes. Computational modeling offers a valuable tool for quantitatively characterizing BHVs. To ensure the accuracy of computational models, it is crucial to consider precise leaflet properties, including mechanical properties and density. Bovine pericardium (BP) serves as a common material for BHV leaflets. Previous computational studies often assume BP density to approximate that of water or blood. Given that BP leaflets undergo various treatments, such as tissue fixation and anti-calcification, this study aims to measure the density of BP used in BHVs and assess its impact on leaflet stress distribution.

Methods: Eight square BP samples were laser cut from Edwards BP patches and their density was determined. Specimen weight was measured using an A&D Analytical Balance, while volume was assessed through high-resolution imaging. Additionally, finite element models resembling a BHV, like the Carpentier-Edwards PERIMOUNT Magna, were constructed in ABAQUS.

Results: The average density of the BP samples was found to be 1,410 kg/m³. During the acceleration phase of a cardiac cycle, the maximum stress reached 1.89 MPa for a density of 1,410 kg/m³ and 2.47 MPa for a density of 1,000 kg/m³ (a 30.7% difference). In the deceleration phase, the maximum stress reached 713 kPa and 669 kPa, respectively.

Conclusion: Leaflet stress distribution and motion in BHVs are influenced by density variations. Establishing an accurate density value for BHV leaflets is imperative for enhancing the computational models, which can ultimately contribute to improved BHV design and outcomes.

Purpose: Activation of the calf (gastrocnemius and soleus) and tibialis anterior muscles play an important role in blood pressure regulation (via muscle-pump mechanism) and postural control. Parkinson's disease is associated with calf (and tibialis anterior muscles weakness and stiffness, which contribute to postural instability and associated falls. In this work, we studied the role of the medial and lateral gastrocnemius, tibialis anterior, and soleus muscle contractions in maintaining blood pressure and postural stability in Parkinson's patients and healthy controls during standing. In addition, we investigated whether the activation of the calf and tibialis anterior muscles is baroreflex dependent or postural-mediated.

Methods: We recorded electrocardiogram, blood pressure, center of pressure as a measure of postural sway, and muscle activity from the medial and lateral gastrocnemius, tibialis anterior, and soleus muscles from twenty-six Parkinson's patients and eighteen sex and age-matched healthy controls during standing and with eyes open. The interaction and bidirectional causalities between the cardiovascular, musculoskeletal, and postural variables were studied using wavelet transform coherence and convergent cross-mapping techniques, respectively.

Results: Parkinson's patients experienced a higher postural sway and demonstrated mechanical muscle-pump dysfunction of all individual leg muscles, all of which contribute to postural instability. Moreover, our results showed that coupling between the cardiovascular, musculoskeletal, and postural variables is affected by Parkinson's disease while the contribution of the calf and tibialis anterior muscles is greater for blood pressure regulation than postural sway.

Conclusion: The outcomes of this study could assist in the development of appropriate physical exercise programs that target lower limb muscles to improve the muscle-pump function and reduce postural instability in Parkinson's disease.

Purpose: When performing a brain arteriovenous malformation (bAVMs) intervention, computer-assisted analysis of bAVMs can aid clinicians in planning precise therapeutic alternatives. Therefore, we aim to assess currently available methods for bAVMs nidus extent identification over 3DRA. To this end, we establish a unified framework to contrast them over the same dataset, fully automatising the workflows.

Materials and methods: We retrospectively collected contrast-enhanced 3DRA scans of patients with bAVMs. A segmentation network was used to automatically acquire the brain vessels segmentation for each case. We applied the nidus extent identification algorithms over each of the segmentations, computing overlap measurements against manual nidus delineations.

Results: We evaluated the methods over a private dataset with 22 3DRA scans of individuals with bAVMs. The best-performing alternatives resulted in [Formula: see text] and [Formula: see text] dice coefficient values.

Conclusions: The mathematical morphology-based approach showed higher robustness through inter-case variability. The skeleton-based approach leverages the skeleton topomorphology characteristics, while being highly sensitive to anatomical variations and the skeletonisation method employed. Overall, nidus extent identification algorithms are also limited by the quality of the raw volume, as the consequent imprecise vessel segmentation will hinder their results. Performance of the available alternatives remains subpar. This analysis allows for a better understanding of the current limitations.

Propose: An electrocardiogram (ECG) has been extensively used to detect rhythm disturbances. We sought to determine the accuracy of different machine learning in distinguishing abnormal ECGs from normal ones in children who were examined using a resting 12-Lead ECG machine, and we also compared the manual and automated measurement using the modular ECG Analysis System (MEANS) algorithm of ECG features.

Methods: Altogether, 10745 ECGs were recorded for students aged 6 to 18. Manual and automatic ECG features were extracted for each participant. Features were normalized using Z-score normalization and went through the student's t-test and chi-squared test to measure their relevance. We applied the Boruta algorithm for feature selection and then implemented eight classifier algorithms. The dataset was split into training (80%) and test (20%) partitions. The performance of the classifiers was evaluated on the test data (unseen data) by 1000 bootstrap, and sensitivity (SEN), specificity (SPE), AUC, and accuracy (ACC) were reported.

Results: In univariate analysis, the highest performance was heart rate and RR interval in the manual dataset and heart rate in an automated dataset with AUC of 0.72 and 0.71, respectively. The best classifiers in the manual dataset were random forest (RF) and quadratic-discriminant-analysis (QDA) with AUC, ACC, SEN, and SPE equal to 0.93, 0.98, 0.69, 0.99, and 0.90, 0.95, 0.75, 0.96, respectively. In the automated dataset, QDA (AUC: 0.89, ACC:0.92, SEN:0.71, SPE:0.93) and stack learning (SL) (AUC:0.89, ACC:0.96, SEN:0.61, SPE:0.99) reached best performances.

Conclusion: This study demonstrated that the manual measurement of 12-Lead ECG features had better performance than the automated measurement (MEANS algorithm), but some classifiers had promising results in discriminating between normal and abnormal cases. Further studies can help us evaluate the applicability and efficacy of machine-learning approaches for distinguishing abnormal ECGs in community-based investigations in both adults and children.

Background: In object-oriented or acausal modelling, components of the model can be connected topologically, following the inherent structure of the physical system, and system equations can be formulated automatically. This technique allows individuals without a mathematics background to develop knowledge-based models and facilitates collaboration in multidisciplinary fields like biomedical engineering. This study conducts a preclinical evaluation of a ventricular assist device (VAD) in assisting advanced-stage heart failure patients in an acausal modelling environment.

Methods: A comprehensive object-oriented model of the cardiovascular system with a VAD is developed in MATLAB/SIMSCAPE, and its hemodynamic behaviour is studied. An analytically derived pump model is calibrated for the experimental prototype of the Istanbul Heart VAD. Hemodynamics are produced under healthy, diseased, and assisted conditions. The study features a comprehensive collection of advanced-stage heart failure patients' data from the literature to identify parameters for disease modelling and to validate the resulting hemodynamics.

Results: Regurgitation, suction, and optimal speeds are identified, and trends in different hemodynamic parameters are observed for the simulated pathophysiological conditions. Using pertinent parameters in disease modelling allows for more accurate results compared to the traditional approach of arbitrary reduction in left ventricular contractility to model dilated cardiomyopathy.

Conclusion: The current research provides a comprehensive and validated framework for the preclinical evaluation of cardiac assist devices. Due to its object-oriented nature, the featured model is readily modifiable for other cardiovascular diseases for studying the effect of pump operating conditions on hemodynamics and vice versa in silico and hybrid mock circulatory loops. The work also provides a potential teaching tool for understanding the pathophysiology of heart failure, diagnosis rationale, and degree of assist requirements.

Introduction: T-wave analysis from standard electrocardiogram (ECG) remains one of the most available clinical and research methods for evaluating myocardial repolarization. T-wave morphology was recently evaluated to aid with diagnosis and characterization of diastolic dysfunction. Unfortunately, PDF stored ECG datasets limit additional numerical post-processing of ECG waveforms. In this study, we apply a simple custom process pipeline to extract and re-digitize T-wave signals and subject them to principal component analysis (PCA) to define primary T-wave shape variations.

Methods: We propose simple pre-processing and digitization algorithms programmable as a MATLAB tool using standard thresholding functions without the need for advanced signal analysis. To validate digitized datasets, we compared clinically standard measurements in 20 different ECGs with the original ECG machine interpreted values as a gold standard. Afterwards, we analyzed 212 individual ECGs for T-wave shape analysis using PCA.

Results: The re-digitized signal was shown to preserve the original information as evidenced by excellent agreement between original - machine interpreted and re-digitized clinical variables including heart rate: bias ~ 1 bpm (95% CI: -1.0 to 3.5), QT interval: bias ~ 0.000 ms (95% CI: -0.012 to 0.012), PR interval: bias = -0.015 ms (95% CI: -0.015 to 0.003), and QRS duration: bias = -0.001 ms (95% CI: -0.007 to 0.006). PCA revealed that the first principal component universally modulates the T-wave height or amount of repolarization voltage regardless of the investigated ECG lead. The second and third principal components described variation in the T-wave peak onset and the T-wave peak morphology, respectively.

Conclusion: This study presents a straightforward method for re-digitizing ECGs stored in the PDF format utilized in many academic electronic medical record systems. This process can yield re-digitized lead specific signals which can be retrospectively analyzed using advanced custom post-processing numerical analysis independent of commercially available platforms.

Purpose: Mitral regurgitation (MR) is a highly prevalent and deadly cardiac disease characterized by improper mitral valve (MV) leaflet coaptation. Among the plethora of available treatment strategies, the MitraClip is an especially safe option, but optimizing its long-term efficacy remains an urgent challenge.

Methods: We applied our noninvasive image-based strain computation pipeline [1] to intraoperative transesophageal echocardiography datasets taken from ten patients undergoing MitraClip repair, spanning a range of MR etiologies and MitraClip configurations. We then analyzed MV leaflet strains before and after MitraClip implementation to develop a better understanding of (1) the pre-operative state of human regurgitant MV, and (2) the MitraClip's impact on the MV leaflet deformations.

Results: The MV pre-operative strain fields were highly variable, underscoring both the heterogeneity of the MR in the patient population and the need for patient-specific treatment approaches. Similarly, there were no consistent overall post-operative strain patterns, although the average A2 segment radial strain difference between pre- and post-operative states was consistently positive. In contrast, the post-operative strain fields were better correlated to their respective pre-operative strain fields than to the inter-patient post-operative strain fields. This quantitative result implies that the patient specific pre-operative state of the MV guides its post-operative deformation, which suggests that the post-operative state can be predicted using pre-operative data-derived modelling alone.

Conclusions: The pre-operative MV leaflet strain patterns varied considerably across the range of MR disease states and after MitraClip repair. Despite large inter-patient heterogeneity, the post-operative deformation appears principally dictated by the pre-operative deformation state. This novel finding suggests that though the variation in MR functional state and MitraClip-induced deformation were substantial, the post-operative state can be predicted from the pre-operative data alone. This study suggests that, with use of larger patient cohort and corresponding long-term outcomes, quantitative predictive factors of MitraClip durability can be identified.