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Abstract Aortic stenosis, hypertension, and left ventricular hypertrophy often coexist in the elderly, causing a detrimental mismatch in coupling between the heart and vasculature known as ventricular−vascular (VA) coupling. Impaired left VA coupling, a critical aspect of cardiovascular dysfunction in aging and disease, poses significant challenges for optimal cardiovascular performance. This systematic review aims to assess the impact of simulating and studying this coupling through computational models. By conducting a comprehensive analysis of 34 relevant articles obtained from esteemed databases such as Web of Science, Scopus, and PubMed until July 14, 2022, we explore various modeling techniques and simulation approaches employed to unravel the complex mechanisms underlying this impairment. Our review highlights the essential role of computational models in providing detailed insights beyond clinical observations, enabling a deeper understanding of the cardiovascular system. By elucidating the existing models of the heart (3D, 2D, and 0D), cardiac valves, and blood vessels (3D, 1D, and 0D), as well as discussing mechanical boundary conditions, model parameterization and validation, coupling approaches, computer resources and diverse applications, we establish a comprehensive overview of the field. The descriptions as well as the pros and cons on the choices of different dimensionality in heart, valve, and circulation are provided. Crucially, we emphasize the significance of evaluating heart−vessel interaction in pathological conditions and propose future research directions, such as the development of fully coupled personalized multidimensional models, integration of deep learning techniques, and comprehensive assessment of confounding effects on biomarkers.

Background: Vagal reflexes regulate homeostasis in visceral organs and systems through afferent and efferent neurons and nerve fibers. Small, unmyelinated, C-type afferents comprise over 80% of fibers in the vagus and form the sensory arc of autonomic reflexes of the gut, lungs, heart and vessels and the immune system. Selective bioelectronic activation of C-afferents could be used to mechanistically study and treat diseases of peripheral organs in which vagal reflexes are involved, but it has not been achieved. Methods: We stimulated the vagus in rats and mice using trains of kHz-frequency stimuli. Stimulation effects were assessed using neuronal c-Fos expression, physiological and nerve fiber responses, optogenetic and computational methods. Results: Intermittent kHz stimulation for 30 min activates specific motor and, preferentially, sensory vagus neurons in the brainstem. At sufficiently high frequencies (>5 kHz) and at intensities within a specific range (7–10 times activation threshold, T, in rats; 15-25 × T in mice), C-afferents are activated, whereas larger, A- and B-fibers, are blocked. This was determined by measuring fiber-specific acute physiological responses to kHz stimulus trains, and by assessing fiber excitability around kHz stimulus trains through compound action potentials evoked by probing pulses. Aspects of selective activation of C-afferents are explained in computational models of nerve fibers by how fiber size and myelin shape the response of sodium channels to kHz-frequency stimuli. Conclusion: kHz stimulation is a neuromodulation strategy to robustly and selectively activate vagal C-afferents implicated in physiological homeostasis and disease, over larger vagal fibers.

Background: The electrode placement and pulse width for electroconvulsive therapy (ECT) are important treatment parameters associated with ECT related retrograde memory side-effects. Modification of these parameters with right unilateral (RUL) ECT may have utility for further reducing these side-effects. Objective: This study explored use of the frontoparietal (FP) placement for reducing retrograde memory side effects with ECT. We hypothesised that superior retrograde memory outcomes would occur with FP compared to temporoparietal (TP) placement and with ultrabrief (UB: 0.3 ms) compared to brief pulse (BP: 1.0 ms) width ECT. Methods: In this randomised cross-over, double-blinded study, participants received a single treatment of BP TP, BP FP, UB TP and UB FP ECT. Neuropsychological testing was conducted prior to and immediately following each treatment. Computational modelling was conducted to explore associations between E-fields in regions-of-interest associated with memory. Results: Nine participants completed the study. The FP placement was not superior to TP for retrograde memory outcomes. For both electrode placements UB pulse width was associated with significantly better visual retrograde memory compared to BP (p

Additive manufacturing (3D printing) and computer-aided design (CAD) still have limited uptake in biomedical and bioengineering research and education, despite the significant potential of these technologies. The utility of organ-scale 3D-printed models of living structures is widely appreciated, while the workflows for microscopy data translation into tactile accessible replicas are not well developed yet. Here, we demonstrate an accessible and reproducible CAD-based methodology for generating 3D-printed scalable models of human cells cultured in vitro and imaged using conventional scanning confocal microscopy with fused deposition modeling (FDM) 3D printing. We termed this technology CiTo-3DP (Cells-in-Touch for 3D Printing). As a proof-of-concept, we created dismountable CiTo-3DP models of human epithelial, mesenchymal, and neural cells by using selectively stained nuclei and cytoskeletal components. We also provide educational and research context for the presented cellular models. In the future, the CiTo-3DP approach can be adapted to different imaging and 3D printing modalities and comprehensively present various cell types, subcellular structures, and extracellular matrices. The resulting CAD and 3D printed models could be used for a broad spectrum of education and research applications.

DICOM X-rays are not easily accessible for telemedicine, and existing learning-based automated Cobb angle (CA) predictions are not accurate on suboptimal X-ray images. To develop an automated CA prediction system irrespective of image quality, with no restrictions on curve patterns, 367 consecutive patients attending our scoliosis clinic were recruited and their coronal X-rays were re-captured using mobile phones. Five-fold cross-validation was conducted (each with 294 randomly selected images for training a neural network SpineHRNet to detect endplate landmarks and end-vertebrae, and the remaining 73 images for testing). The predicted heatmaps of vertebral landmarks were visualized to enhance interpretability of the SpineHRNet. Per-landmark Euclidean distance (L2) errors and recall of landmark detection were calculated to assess the accuracy of the predicted landmarks. Further computed CAs were quantitatively compared with spine-specialists measured ground truth (GT). The average L2 error and the recall of the detected endplates landmarks were 2.8 pixels and 0.99 respectively. The predicted CAs were all significantly correlated with GT ($\text{p}

Summary: Background: Assessment of spine alignment is crucial in the management of scoliosis, but current auto-analysis of spine alignment suffers from low accuracy. We aim to develop and validate a hybrid model named SpineHRNet+, which integrates artificial intelligence (AI) and rule-based methods to improve auto-alignment reliability and interpretability. Methods: From December 2019 to November 2020, 1,542 consecutive patients with scoliosis attending two local scoliosis clinics (The Duchess of Kent Children's Hospital at Sandy Bay in Hong Kong; Queen Mary Hospital in Pok Fu Lam on Hong Kong Island) were recruited. The biplanar radiographs of each patient were collected with our medical machine EOS™. The collected radiographs were recaptured using smartphones or screenshots, with deidentified images securely stored. Manually labelled landmarks and alignment parameters by a spine surgeon were considered as ground truth (GT). The data were split 8:2 to train and internally test SpineHRNet+, respectively. This was followed by a prospective validation on another 337 patients. Quantitative analyses of landmark predictions were conducted, and reliabilities of auto-alignment were assessed using linear regression and Bland-Altman plots. Deformity severity and sagittal abnormality classifications were evaluated by confusion matrices. Findings: SpineHRNet+ achieved accurate landmark detection with mean Euclidean distance errors of 2·78 and 5·52 pixels on posteroanterior and lateral radiographs, respectively. The mean angle errors between predictions and GT were 3·18° and 6·32° coronally and sagittally. All predicted alignments were strongly correlated with GT (p 0·97), with minimal overall difference visualised via Bland-Altman plots. For curve detections, 95·7% sensitivity and 88·1% specificity was achieved, and for severity classification, 88·6–90·8% sensitivity was obtained. For sagittal abnormalities, greater than 85·2–88·9% specificity and sensitivity were achieved. Interpretation: The auto-analysis provided by SpineHRNet+ was reliable and continuous and it might offer the potential to assist clinical work and facilitate large-scale clinical studies. Funding: RGC Research Impact Fund (R5017–18F), Innovation and Technology Fund (ITS/404/18), and the AOSpine East Asia Fund (AOSEA(R)2019–06).

A modified monopole patch antenna for microwave-based hemorrhagic or ischemic stroke recognition is presented in this article. The designed antenna is fabricated on a cost-effective FR-4 lossy material with a 0.02 loss tangent and 4.4 dielectric constant. Its overall dimensions are 0.32 λ × 0.28 λ × 0.007 λ, where λ is the lower bandwidth 1.3 GHz frequency wavelength. An inset feeding approach is utilized to feed the antenna to reduce the input impedance (z = voltage/current). A total bandwidth (below −10 dB) of 2.4 GHz (1.3–3.7 GHz) is achieved with an effective peak gain of over 6 dBi and an efficiency of over 90%. A time-domain analysis confirms that the antenna produces minimal signal distortion. Simulated and experimental findings share a lot of similarities. Brain tissue is penetrated by the antenna to a satisfactory degree, while still exhibiting a safe specific absorption rate (SAR). The maximum SAR value measured for the head model is constrained to be equal to or below 0.1409 W/kg over the entire usable frequency band. Evaluation of theoretical and experimental evidence indicates the intended antenna is appropriate for Microwave Imaging (MWI) applications.

Recent retinal studies have directed more attention to sophisticated stimulation strategies based on high-frequency (>1.0 kHz) electrical stimulation (HFS). In these studies, each retinal ganglion cell (RGC) type demonstrated a characteristic stimulus-strength-dependent response to HFS, offering the intriguing possibility of focally targeting retinal neurons to provide useful visual information by retinal prosthetics. Ionic mechanisms are known to affect the responses of electrogenic cells during electrical stimulation. However, how these mechanisms affect RGC responses is not well understood at present, particularly when applying HFS. Here, we investigate this issue via an in silico model of the RGC. We calibrate and validate the model using an in vitro retinal preparation. An RGC model based on accurate biophysics and realistic representation of cell morphology, was used to investigate how RGCs respond to HFS. The model was able to closely replicate the stimulus-strength-dependent suppression of RGC action potentials observed experimentally. Our results suggest that spike inhibition during HFS is due to local membrane hyperpolarization caused by outward membrane currents near the stimulus electrode. In addition, the extent of HFS-induced inhibition can be largely altered by the intrinsic properties of the inward sodium current. Finally, stimulus-strength-dependent suppression can be modulated by a wide range of stimulation frequencies, under generalized electrode placement conditions. In vitro experiments verified the computational modeling data. This modeling and experimental approach can be extended to further our understanding on the effects of novel stimulus strategies by simulating RGC stimulus-response profiles over a wider range of stimulation frequencies and electrode locations than have previously been explored.

Computational models have become essential in predicting medical device efficacy prior to clinical studies. To investigate the performance of a left-ventricular assist device (LVAD), a fully-coupled cardiac fluid-electromechanics finite element model was developed, incorporating electrical activation, passive and active myocardial mechanics, as well as blood hemodynamics solved simultaneously in an idealized biventricular geometry. Electrical activation was initiated using a simplified Purkinje network with one-way coupling to the surrounding myocardium. Phenomenological action potential and excitation-contraction equations were adapted to trigger myocardial contraction. Action potential propagation was formulated within a material frame to emulate gap junction-controlled propagation, such that the activation sequence was independent of myocardial deformation. Passive cardiac mechanics were governed by a transverse isotropic hyperelastic constitutive formulation. Blood velocity and pressure were determined by the incompressible Navier-Stokes formulations with a closed-loop Windkessel circuit governing the circulatory load. To investigate heart-LVAD interaction, we reduced the left ventricular (LV) contraction stress to mimic a failing heart, and inserted a LVAD cannula at the LV apex with continuous flow governing the outflow rate. A proportional controller was implemented to determine the pump motor voltage whilst maintaining pump motor speed. Following LVAD insertion, the model revealed a change in the LV pressure-volume loop shape from rectangular to triangular. At higher pump speeds, aortic ejection ceased and the LV decompressed to smaller end diastolic volumes. After multiple cycles, the LV cavity gradually collapsed along with a drop in pump motor current. The model was therefore able to predict ventricular collapse, indicating its utility for future development of control algorithms and pre-clinical testing of LVADs to avoid LV collapse in recipients.

The ability for visual prostheses to preferentially activate functionally-distinct retinal ganglion cells (RGCs) is important for improving visual perception. This study investigates the use of high frequency stimulation (HFS) to elicit RGC activation, using a closed-loop algorithm to search for optimal stimulation parameters for preferential ON and OFF RGC activation, resembling natural physiological neural encoding in response to visual stimuli. We evaluated the performance of a wide range of electrical stimulation amplitudes and frequencies on RGC responses in vitro using murine retinal preparations. It was possible to preferentially excite either ON or OFF RGCs by adjusting amplitudes and frequencies in HFS. ON RGCs can be preferentially activated at relatively higher stimulation amplitudes (>150 μA) and frequencies (2–6.25 kHz) while OFF RGCs are activated by lower stimulation amplitudes (40–90 μA) across all tested frequencies (1–6.25 kHz). These stimuli also showed great promise in eliciting RGC responses that parallel natural RGC encoding: ON RGCs exhibited an increase in spiking activity during electrical stimulation while OFF RGCs exhibited decreased spiking activity, given the same stimulation amplitude. In conjunction with the in vitro studies, in silico simulations indicated that optimal HFS parameters could be rapidly identified in practice, whilst sampling spiking activity of relevant neuronal subtypes. This closed-loop approach represents a step forward in modulating stimulation parameters to achieve appropriate neural encoding in retinal prostheses, advancing control over RGC subtypes activated by electrical stimulation.

Cardiovascular diseases are the number one cause of death worldwide. Currently, portable battery-operated systems such as mobile phones with wireless ECG sensors have the potential to be used in continuous cardiac function assessment that can be easily integrated into daily life. These portable point-of-care diagnostic systems can therefore help unveil and treat cardiovascular diseases. The basis for ECG analysis is a robust detection of the prominent QRS complex, as well as other ECG signal characteristics. However, it is not clear from the literature which ECG analysis algorithms are suited for an implementation on a mobile device. We investigate current QRS detection algorithms based on three assessment criteria: 1) robustness to noise, 2) parameter choice, and 3) numerical efficiency, in order to target a universal fast-robust detector. Furthermore, existing QRS detection algorithms may provide an acceptable solution only on small segments of ECG signals, within a certain amplitude range, or amid particular types of arrhythmia and/or noise. These issues are discussed in the context of a comparison with the most conventional algorithms, followed by future recommendations for developing reliable QRS detection schemes suitable for implementation on battery-operated mobile devices.

Dilated cardiomyopathy (DCM) is the most common myocardial disease. It not only leads to systolic dysfunction but also diastolic deficiency. We sought to investigate the effect of idiopathic and ischemic DCM on the intraventricular fluid dynamics and myocardial wall mechanics using a 2D axisymmetrical fluid structure interaction model. In addition, we also studied the individual effect of parameters related to DCM, i.e. peak E-wave velocity, end systolic volume, wall compliance and sphericity index on several important fluid dynamics and myocardial wall mechanics variables during ventricular filling. Intraventricular fluid dynamics and myocardial wall deformation are significantly impaired under DCM conditions, being demonstrated by low vortex intensity, low flow propagation velocity, low intraventricular pressure difference (IVPD) and strain rates, and high-end diastolic pressure and wall stress. Our sensitivity analysis results showed that flow propagation velocity substantially decreases with an increase in wall stiffness, and is relatively independent of preload at low-peak E-wave velocity. Early IVPD is mainly affected by the rate of change of the early filling velocity and end systolic volume which changes the ventriculo:annular ratio. Regional strain rate, on the other hand, is significantly correlated with regional stiffness, and therefore forms a useful indicator for myocardial regional ischemia. The sensitivity analysis results enhance our understanding of the mechanisms leading to clinically observable changes in patients with DCM.

In retinal neuroprostheses, spatial interaction between electric fields from various electrodes - electric crosstalk - may occur in multielectrode arrays during simultaneous stimulation of the retina. Depending on the electrode design and placement, this crosstalk can either enhance or degrade the functional characteristics of a visual prosthesis. To optimize the device performance, a balance must be satisfied between the constructive interference of crosstalk on dynamic range and power consumption and its negative effect on artificial visual acuity. In the present computational modeling study, we have examined the trade-off in these positive and negative effects using a range of currently available electrode array configurations, compared to a recently proposed stimulation strategy - the quasi monopolar (QMP) configuration - in which the return current is shared between local bipolar guards and a distant monopolar electrode. We evaluate the performance of the QMP configuration with respect to the implantation site and electrode geometry parameters. Our simulation results demonstrate that the beneficial effects of QMP are only significant at electrode-to-cell distances greater than the electrode dimensions. Possessing a relatively lower activation threshold, QMP was found to be superior to the bipolar configuration in terms of providing a relatively higher visual acuity. However, the threshold for QMP was more sensitive to the topological location of the electrode in the array, which may need to be considered when programming the manner in which electrode are simultaneously activated. This drawback can be offset with a wider dynamic range and lower power consumption of QMP. Furthermore, the ratio of monopolar return current to total return can be used to adjust the functional performance of QMP for a given implantation site and electrode parameters. We conclude that the QMP configuration can be used to improve visual information-to-stimulation mapping in a visual prosthesis, while maintaining low power consumption.

A lumped parameter model of the cardiovascular system has been developed and optimized using experimental data obtained from 13 healthy subjects during graded head-up tilt (HUT) from the supine position to [Formula: see text]. The model includes descriptions of the left and right heart, direct ventricular interaction through the septum and pericardium, the systemic and pulmonary circulations, nonlinear pressure volume relationship of the lower body compartment, arterial and cardiopulmonary baroreceptors, as well as autoregulatory mechanisms. A number of important features, including the separate effects of arterial and cardiopulmonary baroreflexes, and autoregulation in the lower body, as well as diastolic ventricular interaction through the pericardium have been included and tested for their significance. Furthermore, the individual effect of parameter associated with heart failure, including LV and RV contractility, baseline systemic vascular resistance, pulmonary vascular resistance, total blood volume, LV diastolic stiffness and reflex gain on HUT response have also been investigated. Our fitted model compares favorably with our experimental measurements and published literature at a range of tilt angles, in terms of both global and regional hemodynamic variables. Compared to the normal condition, a simulated congestive heart failure condition produced a blunted response to HUT with regards to the percentage changes in cardiac output, stroke volume, end diastolic volume and effector response (i.e., heart contractility, venous unstressed volume, systemic vascular resistance and heart rate) with progressive tilting.