Cardiovascular Engineering and Technology最新文献

Purpose: Inefficient energy delivery to blood remains a primary challenge in cardiac radiofrequency ablation (RFA), limiting procedural efficacy. This paper introduces and computationally validates a novel multi-surface microelectrode catheter (MSMC) designed to enhance targeted energy delivery and improve overall procedural efficiency.

Methods: A 3D multiphysics computational model coupling electrical, thermal, fluid-dynamic, and mechanical fields was developed to simulate RFA. The performance of the MSMC was systematically compared against a traditional catheter by analyzing its energy distribution and thermal lesion characteristics under both standard (10-18 W vs. 30 W) and high-power short-duration (25 W vs. 60 W) protocols, assessing the impact of varying catheter angles (vertical, 45°, and parallel), and exploring its potential for real-time lesion monitoring via impedance analysis.

Results: The MSMC directed over 75% of its energy to the myocardium, a threefold improvement over the traditional catheter (~22%), allowing the creation of comparable lesions with 40% less power. The design demonstrated high stability across different orientations. Furthermore, analysis of its impedance characteristics via Cole-Cole plots revealed a greater sensitivity for real-time lesion monitoring compared to the traditional catheter.

Conclusions: The MSMC's design, which synergizes a multi-surface electrode structure with a contact-based discharge strategy, enables more efficient and predictable lesion formation. This computational proof-of-concept study confirms its potential to improve the safety, efficacy, and real-time control of RFA procedures, offering a promising pathway for the development of next-generation therapeutic devices.

Purpose: Tricuspid valve chordae tendineae rupture is a valvular lesion that is often overlooked, though is postulated to be more prevalent than currently known. We examined the hemodynamics and biomechanical response of the tricuspid valve leaflets following chordae rupture to understand how acute changes in the post-rupture mechanical environment may contribute to long-term remodeling responses.

Methods: Porcine valve leaflet deformation was studied in an intact heart in an ex vivo setup using sonomicrometry techniques before and after chordae rupture, which was induced by severing a chordae bundle connected to the septal leaflet.

Results: Following chordae rupture, pulmonary artery pressure dropped approximately 5 mmHg ( $p=0.048$ ), indicating that valvular regurgitation occurred immediately after rupture. Mean maximum principal stretch of the septal leaflet increased 12% after rupture ( $p=0.006$ ).

Conclusion: The immediate changes in post-rupture septal leaflet stretches show that chordae tendineae rupture acutely alters the biomechanical environment of the tricuspid valve, which may result in chronic tissue remodeling responses. The tricuspid valve is one of the four valves in the heart. Rupture of supporting structures of the tricuspid valve leaflet, known as chordae tendineae, may be more common than previously thought. In this study, we used excised pig hearts to examine how chordae rupture affects valvular function. With our experimental beating heart system, we pumped fluid through the hearts under realistic conditions and measured changes in pressure and leaflet motion before and after chordae rupture. After rupture, we observed a change in pressures and leaflet motion, causing the valve to leak and become less efficient. These changes may influence how the valve functions over time.

Objective: Electrocardiogram (ECG) signals are well-known non-stationary heart signals of lower strength. Due to their small amplitude, it attracts other biomedical artefacts from the surrounding. This research mainly focuses on removing artefacts from the electrocardiogram signals.

Method: The work presented uses the recent metaheuristic techniques to design a nonlinear adaptive Hammerstein filter-based structure efficiently. Many powerful metaheuristic optimisation algorithms, such as particle swarm optimisation algorithm with constriction factor, flower pollination algorithm, marine predators' algorithm and growth optimiser, have been applied for the optimal design of adaptive Hammerstein filter-based structures. The proposed structure has been analysed for electrocardiogram with various noise signals such as muscle artefact, white Gaussian noise etc. RESULTS: Among the adopted-metaheuristic algorithms applied to adaptive Hammerstein filter-based structures, the growth optimiser-optimised adaptive Hammerstein filter-based structures performed better with improved signal-to-noise ratio and minimal mean squared error values. A digital signal processor kit is used to authenticate the simulation outcomes.

Conclusion: The results (mean squared error: 3.698E-08 and signal-to-noise ratio improvement: 12 dB) obtained through the proposed technique ensure its supremacy compared to other state-of-the-art techniques.

Significance: Hence, the proposed method can be utilised for electrocardiogram signal enhancement.

Purpose: Computational modeling holds promise in predicting patient-specific outcomes and guiding clinical decision-making. The patient-specific model forming the basis of a digital twin can be considered biomedical software, thereby necessitating trust in its predictive accuracy.

Methods: This study applies the ASME V&V40 framework to demonstrate the credibility of patient-specific models of aneurysmal thoracic ascending aorta (ATAA) biomechanics. A comprehensive verification, validation, and uncertainty quantification process was performed to evaluate the accuracy of the patient-specific ATAA model.

Results: After implementing the ASME V&V40 standard, the verification errors on the model inputs (i.e., material parameters and hemodynamic variables) resulted in relative errors (RE) < 1%. Validation and its uncertainty quantification of the output aneurysm diameter response showed area metric errors below 5% in the majority of cases, highlighting the accuracy of the patient-specific ATAA model against the clinical comparator. Uncertainties in wall stress predictions due to model inputs were also quantified by probability density functions. Sensitivity analysis revealed that the unknown value of aneurysm wall thickness drives the model output at the highest extent.

Conclusions: These findings contribute to a standardized methodology for evaluating the credibility of patient-specific models, enhancing their utility in computer-based clinical decision support systems for managing patients with ATAAs.

Purpose: Understanding and categorizing fetal health is an influential field of research that profoundly impacts the well-being of both mother and child. The primary desire to precisely examine and cure fetal disorders during pregnancy to enhance fetal and maternal outcomes is the driving force behind the classification of fetal health. Fetal cardiac abnormalities (structural or functional) need immediate doctor attention, and their early identification and detection in all stages of pregnancy can help doctors with the timely treatment of the mother and the unborn child by enabling appropriate prenatal counseling and management. By knowing about fetal health and taking necessary precautions for fetal health, the rate of fetal mortality can be decreased. Advancements in machine learning (ML) algorithms have revolutionized the analysis of fetal electrocardiogram (ECG) signals. Machine Learning and Deep Learning algorithms automate the fetal monitoring process and decisions in emergencies, save time, and enable telemonitoring.

Methods: This paper introduces a new hybrid approach to enhance fetal health classification using an intelligent and dynamic combination of Random Forest (RF) and AdaBoost machine learning algorithms. The proposed work includes a detailed review of existing models and the challenges in handling fetal health data, setting the foundation for the design of advanced hybrid models. The implemented algorithm effectively integrates the strengths of RF and AdaBoost to enhance fetal health monitoring and classification performance. The RF algorithm is widely established for its capacity to manage large and highly dimensional data sets, whereas AdaBoost focuses on enhancing classification accuracy by correcting for mistakes in the RF models' predictions.

Results: The proposed hybrid model is tested on a recognized benchmark CTG dataset, where it attained a classification accuracy of 95.98%, a precision of 92.88%, a recall of 92.78% and an F1 score of 92.70%. Achieved results demonstrate the potential of our novel approach in real-world applications, offering a promising tool for early detection of fetal anomalies, which is crucial for both fetal and maternal health.

Conclusions: Fetal health classification and timely prediction of fetal diseases seem to be a critical step throughout pregnancy. So, to deal with this problem, an attempt has been made to propose an accurate, reliable, and novel hybrid approach for enhancing fetal health classification. By combining the strengths of two algorithms, named RF and AdaBoost, superior classification accuracy, precision, F1 score, and recall have been achieved, and much better robustness compared to standalone models. We have strived to make a noteworthy impact on the health sector by developing this hybrid model for the timely evaluation and prediction of fetal-maternal health.

Purpose: Drug-coated balloon (DCB) therapy is a promising approach to treat peripheral artery disease (PAD), wherein lesion site preparation, balloon inflation, and the local delivery of anti-proliferative drugs such as paclitaxel (PTX) restores and retains lumen patency. Although largely successful in PAD applications, broader clinical deployment is in part limited by the occurrence of late lumen loss due to inward vessel remodeling at the treatment site, a maladaptive chronic response that has been clinically-observed to coincide with elevations in resident vascular smooth muscle cell (vSMC) tone. This study aims to explore a novel strategy to improve DCB efficacy via drug-based attenuation of vSMC tone at the treatment site.

Methods: As a strategy to mitigate this post-DCB failure mode, we consider the local co-delivery of PTX and an additional drug that induces relaxation of vSMCs, specifically the clinically-approved anti-hypertensive drug valsartan (VAL). The potential benefit of drug-based regulation of vSMC tone is supported by recent theoretical studies that predict inward remodeling in the presence of hypertension and endothelial cell dysfunction, both common co-morbidities in PAD patients and established causes of elevated vSMC contractility. The specific selection of VAL as the anti-contractile payload constituent is motivated by its well-known pharmacokinetic and safety profiles, and the notion that current clinical use and familiarity could promote rapid translation in the context of DCBs.

Results: Our obtained results quantify the potency of VAL to induce local vSMC relaxation in arterial tissue, demonstrate the feasibility of PTX and VAL co-delivery using the canonical excipient urea for balloon coating formation, and elucidate key structure-function relations to facilitate efficient drug delivery with these novel coatings.

Conclusion: Our study supports the continued evaluation of VAL for inclusion in DCB formulations due to its potential to redirect post-treatment arterial remodeling. Future in-vivo studies which examine the co-delivery of PTX and VAL in the context of DCBs are needed to establish both the safety and efficacy of this novel approach.

Purpose: Transcatheter aortic valve replacement (TAVR) is an established treatment for severe aortic stenosis; however, it carries the risk of periprocedural strokes. Current cerebral embolic protection (CEP) devices, such as the Sentinel, provide partial protection but are limited by inadequate anatomical coverage and inability to capture smaller emboli effectively. This study aimed to evaluate the effectiveness of a novel CEP device, the F2 filter with a 28 μm pore size and full cervical vessel coverage, in preventing emboli from entering the cerebral circulation.

Methods: The Sentinel and F2 filter were evaluated for the ability to prevent embolic particles of various sizes (45-300 µm) from entering cerebral arteries using two in vitro flow models, incorporating standard and tortuous aortic anatomies. Additionally flow rates were also measured to confirm that normal perfusion was maintained while the devices were in place.

Results: The F2 filter maintained normal cerebral arterial flow and significantly reduced the number of particles across all sizes compared to the Sentinel and control groups. This reduction was observed in all four cerebral branches and across both standard and tortuous aorta models.

Conclusions: The F2 filter showed superior neuroprotective effectiveness to prevent embolic debris from entering the cerebral circulation in the in vitro models. By offering comprehensive coverage to all cervical arteries and with a smaller mesh size, this filter has the potential to improve cerebral protection during TAVR.

Background: This study aims to explore the association between LA and RA remodeling and their influences on ablation efficacy in AF patients.

Methods: The study involved AF patients undergoing their first catheter ablation using CARTO 3 system. After isolating pulmonary veins, three-dimensional electro-anatomical mapping (3D-EAM) of LA and RA was conducted during sinus rhythm. Low voltage area (LVA) was defined as regions with bipolar voltage < 0.5 mv. If LVA constituted ≥ 10% of the total area of the ipsilateral atrium, it was considered an extensive LVA (ELVA).

Results: A total of 271 patients (male 58.3%, median age 63 years) were enrolled. Biatrial 3D-EAM found that the RA had a larger volume and volume index, longer total activation time, and higher maximum voltage than the LA (P < 0.001). The presence of LVAs, especially ELVAs, was more common in LA (LVAs: 47 patients (17.3%) vs. 29 patients (10.7%), P = 0.011; ELVAs: 26 patients (9.6%) vs. 7 patients (2.6%), P < 0.001). The multivariate logistic analysis revealed that older age, female gender, persistent AF, and LA enlargement were independent predictors of LA LVAs, while female gender and AF duration were associated with RA LVAs. Strong associations were found between variables reflecting the LA and the RA remodeling. Multivariate Cox regression indicated that ELVA in the LA was the only independent predictor of post-ablation recurrence.

Conclusions: AF patients had different characteristics and intrinsic correlations between LA and RA remodeling. The LVAs, especially the ELVAs, were more prevalent in the LA than in the RA. There were distinctions in related factors and impacts on ablation efficacy between the LA LVAs and the RA LVAs.