Transposition of the Great Arteries (TGA) is a congenital heart defect characterized by the abnormal positioning of the pulmonary artery over the left ventricle and aorta over the right ventricle. Systemic oxygen delivery, therefore, is dependent on the ability for blood to flow (shunt) between the "parallel" (systemic and pulmonary) circulations. Prior to the standard procedure for treatment of TGA (the arterial switch operation (ASO)), shunting is commonly inadequate, resulting in systemic hypoxemia and hypoxia. In this case the standard intervention is the balloon atrial septostomy, but it may not be sufficient and has a certain complication rate. Other adjustable anatomical and physiological factors may influence shunting but have not been adequately studied. In this investigation, we develop a lumped parameter model (LPM) of TGA to explore the influence of several adjustable factors that can be altered by catheter or pharmacological interventions aimed at improving systemic arterial oxygen delivery to clinically acceptable levels in the preoperative period for newborns with TGA. This model is used to ascertain the sensitivity of oxygen saturation to these parameters and to propose optimal treatment scenarios using formal optimization techniques. Sensitivity in this study is determined using finite difference methods, and a Nelder Mead (NM) algorithm is used for optimization. Out of 729 tested cases in the sensitivity study, percentage systemic arterial oxygen saturation (Ssa) was most sensitive to systemic vascular resistance (SVR) in 32.77% of cases and was the most sensitive to PDA diameter in 32.46% of cases. Increasing patent ductus arteriosus (PDA) diameter and SVR both yield an increase in Ssa in nearly all cases, while decreasing pulmonary vascular resistance (PVR) yields an increase in Ssa in nearly all cases. Notably, atrial septal defect (ASD) enlargement was not always most sensitive parameter for increasing Ssa. Best results were obtained with an objective function with a weight on pulmonary-to-systemic flow ratio of 0.1 compared to the weight of unity on Ssa. Lastly, while it does not significantly impact the results of optimization, compliance ratio does have the potential to influence optimal pre-operative strategy. This study illuminates the influence of SVR and PVR in oxygen delivery to the systemic circulation through extensive sensitivity testing. These results hold promise for applying other interventions aside from atrial septostomy for improving systemic arterial oxygen saturation. Using our methodology in conjunction with machine learning (ML) using clinical data, an optimization-based tool will be developed to guide pre-operative decision-making in TGA management.

Tricuspid valve replacement is the preferred method when valve repair is not feasible. Stented xenobioprostheses, which limit the growth of the fibrous ring due to their rigid titanium frame and often have a short service life, are particularly problematic in children. An alternative approach is the implantation of a mitral valve homograft in the tricuspid position, which is more resistant to calcification. However, the limited availability of small-diameter homografts from adult donors restricts their use. To address this, a new technique for downsizing an adult mitral homograft was developed and tested in a wet lab and in silico (using 3D printing technologies). Two techniques for reducing the size of the mitral homograft were developed: one creating a single papillary muscle and the other creating two neo-papillary muscles. The hydrodynamics of the resulting prostheses were assessed using visual inspection and ultrasound evaluation. It was demonstrated that reducing the mitral homograft by resecting the commissures, a portion of the anterior leaflet, and the posterior leaflet along with their subvalvular structures is a reliable method. This technique does not violate the congruence of the anterior and posterior leaflets and ensures optimal hydrodynamic parameters. The proposed technique makes it possible to downsize an adult mitral homograft to a "pediatric" size. It can be used clinically as an intraoperative adaptation technique, performed on the "back table" in 30-40 minutes.

Accurate assessment of cardiac preload remains a clinical challenge, particularly in heart failure patients where preload manipulation is impractical or contraindicated. Ejection fraction (EF), while widely used, reflects a combination of preload, contractility, and afterload, and may obscure the specific contribution of preload. Inspired by a preload recruitable stroke work (PRSW) model for heart function, a concise, three factor expression for ejection fraction (EF) can be obtained where EF is directly proportional to preload, directly proportional to contractility, and inversely proportional to afterload. The contractility and afterload factors are common metrics; whereas the preload factor, filling fraction (FF), is a novel, dimensionless preload metric that sets a physiologic upperbound on EF. Unfortunately, FF measurement requires an estimate of the volume intercept or dead-space volume of the left ventricle, and such a measure has, conventionally, required preload manipulation with extrapolation to the volume axis. To address this, we propose a single-beat extrapolation method for estimating the volume intercept using end-diastolic and end-systolic measurements. In-silico testing across 10,000 synthetic left ventricular geometries demonstrates strong agreement between the estimated intercept and actual, prescribed dead-space volumes. This method enables non-invasive computation of FF from single-beat data without the need for in vivo preload manipulation. Potential clinical applications include characterizing cardiac function, stratifying heart failure subtypes, and enhancing diagnostic precision when EF is preserved but preload reserve is impaired. Future validation in clinical imaging datasets is warranted to assess real-world applicability.

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. 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. The results (mean squared error: 3.698E-08 and signal-to-noise ratio improvement: 12dB) obtained through the proposed technique ensure its supremacy compared to other state-of-the-art techniques. Hence, the proposed method can be utilised for electrocardiogram signal enhancement.

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. 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. 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. 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.

Type A Thoracic Aortic Dissections are a highly morbid and complex clinical challenge often managed with hemiarch or total arch repair. Hemiarch repair is more commonly performed due to improved neurologic morbidity profile however it leaves behind a residual dissection flap which can lead to aneurysmal degeneration. Bare metal stent placement in conjunction with hemiarch repair is a novel technique which can theoretically avoid leaving a residual dissection flap. In this paper we analyze the biomechanical changes observed after in silico deployment of a bare metal stent in a post-hemiarch type A aortic dissection. We obtain computed tomography scans from pre-operative bare metal stent patients and perform high-fidelity segmentations. This geometry is then utilized for in silico stent deployment via finite element analysis. Deformed geometries are then utilized for computational fluid dynamic simulations to analyze the evolution of pressure gradients in the aorta. We analyze the resulting geometry from in silico stent deployment for three different stiffness ratios between the flap and aortic wall. We demonstrate an acceptable stress evolution in the stent across all 3 stiffness configurations. We show a reduction in the false luminal volume across all stiffness ratios. Our analysis of pressure distributions that evolve in the aorta show that even in scenarios of high flap stiffness, where the false lumen volume shrinks correspondingly less, we still achieve a reduction in the pressure gradient across the aorta. We show that bare metal stent deployment hemodynamically stabilizes the aorta via our finite element analysis and subsequent computational fluid dynamic modelling.

Radiofrequency cardiac ablation (RFCA) is a widely utilized treatment for atrial fibrillation (AF). However, its therapeutic efficacy can be compromised by either insufficient or excessive ablation, potentially leading to serious adverse effects. Therefore, precise control of the thermal lesion size generated during RFCA is critical for surgical success. Neural network is an implementation method of artificial intelligence, which has a strong ability to learn and adapt to complex data patterns, and shows significant application potential in the field of prediction. This study aimed to construct an artificial neural network (ANN) model capable of predicting the depth, width, and volume of ablation thermal lesions. A two-branch ANN model was developed to predict lesion size on the basis of four key parameters: RF power, ablation duration, catheter‒tissue contact force, and contact angle. The training dataset for the model was derived from a finite element model of radiofrequency cardiac ablation. The model incorporated two types of RF power; catheter-tissue contact forces of 10g, 20g, 30g, and 40g; and contact angles of 0°, 45°, and 90°. The test dataset was obtained from ex vivo experiments conducted on a swine model, involving ten sets of experiments. The finite element model effectively simulated the process of thermal lesion formation during RFCA, generating a substantial amount of effective training data. The ex vivo experiments provided reliable test data. The two-branch ANN model was able to predict the depth, width, and volume of thermal lesions, with errors of 0.1986mm, 0.7891mm, and 4.9384 mm3, respectively. This study introduces a two-branch ANN model that serves as an efficient and reliable tool for predicting lesion size for RFCA. The two-branch ANN model proposed in this study enhances the model's ability to fit complex relationships through activation functions and nonlinear combination features. Compared with other models, it has superior predictive capabilities regarding the depth, width, and volume of ablation thermal lesions.

The widespread prevalence and significant consequences of cardiac arrhythmias have been addressed by adopting cardiac stimulation and neuromodulation implantable devices. The oldest, most commonly employed, and most well-known technology is the permanent transvenous cardiac pacemaker. However, in select emergent clinical scenarios and transient pathologies, temporary pacing is preferred. More recently, neuromodulatory vagal nerve stimulation has emerged to address neurologic, psychiatric, and nociceptive pathologies, generating significant clinical and scientific interest in the invention of temporary corollary devices for a subset of indications of nociceptive origin. The dominance of particular implant approaches and anatomic targets in both temporary pacing and neuromodulation in the clinic is owed to capabilities and limitations present in the current technological landscape. However, recent innovations in industry and academia may lead to a fundamental shift in how temporary pacing and neuromodulation are delivered in terms of procedural approach and patient outcomes. In this review, we present an overview of contemporary temporary pacemakers, neuromodulatory therapies, and devices, highlighting novel temporary pacing technologies from the clinic, industry, and academia, such as temporary permanent pacemakers, innovations in non-blood-contacting devices, bioresorbable pacemakers, and advances in neuromodulatory approaches.

This study aims to investigate the effects of transcatheter edge-to-edge repair (TEER) on left ventricular hemodynamics and its potential implications for patient health. An in vitro experimental platform was designed to replicate the anatomical and functional characteristics of the left ventricle (LV). This platform integrates native porcine mitral and aortic valves with a patient-specific 3D-printed silicone LV. The LV hemodynamics after TEER is assessed using echocardiography and particle image velocimetry, focusing on critical indices such as vorticity, Reynolds shear stress (RSS), viscous shear stress (VSS), and energy dissipation rate (ε). TEER effectively reduces the degree of mitral regurgitation (MR); however, it significantly increases RSS, VSS, and ε due to the formation of numerous small-scale vortices in the LV. These hemodynamic changes may lead to adverse left ventricular remodeling, red blood cell damage, and reduced cardiac pumping efficiency, which have to be taken into consideration to optimize the TEER procedure and improve patient outcomes.

Advancements in minimally invasive technologies to decrease postoperative morbidity and recovery times represent a large opportunity for mitral valve repair operations. However, current technologies are unable to replicate gold standard surgical neochord implantation. We developed a novel neochordal repair device, Minimally Invasive Ventricular Anchoring Neochordoplasty (MIVAN), which operates via transcatheter, trans-septal anchoring to the posterior ventricular wall. We evaluated MIVAN in an ex vivo heart simulator and compared it with surgical neochordal repair and MitraClip using a prolapse model. Upon MIVAN repair of the model (n = 5), regurgitant fraction was reduced from 19.46 ± 1.77% to 7.30 ± 0.99% (p = 0.01). Surgical neochordal repair reduced regurgitant fraction to 5.65 ± 0.66%, but there was no significant difference between MIVAN and surgical repair (p = 0.22). Unpaired MitraClip repair had significantly higher regurgitant fraction of 11.9 ± 1.40%, compared with those of neochord (p < 0.01) and MIVAN (p = 0.03) repairs. MIVAN represents a high-value opportunity for minimally invasive mitral valve repair. The benefits of the percutaneous, trans-septal approach for implantation on the posterior ventricular wall necessitate the expanded exploration of this device as a treatment alternative.