Normal Cardiac Cycle Research Articles

Characterization of the cardiac cycle in Royal Canadian Mounted Police Cadets.

Royal Canadian Mounted Police (RCMP) cadets experience high volumes of potentially psychologically traumatic events, suggesting a need of normal cardiac cycle interval data on the cadets for comparison. We characterize the cardiac cycle of incoming RCMP cadets starting the 26-week training program. The cadets collected their cardiac data using the LLA Recordis™ device. Male RCMP cadets had higher (p<0.05) myocardial and diastolic performance indices, aortic valve open to aortic twist time, and isovolumic relaxation time than female RCMP cadets. Monitoring the cardiac cycle intervals in RCMP cadets can provide insights to changes in their heart function from their occupational demands.

Impact of Ultrasound Scanning Plane on Common Carotid Artery Longitudinal Wall Motion

ObjectiveThe arterial wall not only moves in the radial direction to expand circumferentially but also moves in the axial (longitudinal) direction in a predictable bidirectional pattern during a normal cardiac cycle. While common carotid artery (CCA) longitudinal wall motion (CALM) has been described previously, there is a lack of evidence-based method standardization to align practices for human measurement. The purpose of this study was to evaluate whether different scanning planes impact CALM outcomes in healthy males and females to provide clarity on data collection strategies. MethodsThirty-one healthy adults (16 females, 23 ± 3 y of age) underwent ultrasound scanning of the right CCA in the anterior, lateral, and posterior imaging planes. CALM was evaluated using a custom speckle-tracking algorithm and was analyzed as segmental motion outcomes (anterograde, retrograde, maximum displacement and radial-axial path length). ResultsNo differences in any CALM outcome were observed between imaging planes (p > 0.05), and equivalence testing indicated that retrograde CALM displacement was similar between anterior and posterior distal walls (p = 0.04). We observed no differences (p > 0.05) in CALM outcomes between the proximal (free-wall, adjacent to the internal jugular vein [IJV]) and distal wall in the posterior imaging plane. Qualitatively, it was more difficult to successfully track vascular tissue between the IJV and CCA due to the thin wall components and highly mobile wall in the radial direction. ConclusionIn the absence of clear differences between scanning planes, we recommend standardizing acquisition in the lateral plane and avoiding the IJV free-wall when evaluating CALM in humans.

PVCsNet : A Specialized Artificial Intelligence-Based Model to Classify Premature Ventricular Contractions from ECG Images.

Premature ventricular complexes (PVCs) are irregularities in heart rhythm where the ventricles contract earlier than expected, disrupting the normal cardiac cycle. Identifying the origin of PVCs before surgery is crucial as it can reduce operation duration, lower radiation exposure, and potentially enhance ablation success rates. Current detection methods face limitations in accuracy and data processing, often requiring large datasets and complex interpretations. This study presents PVCsNet, a deep-learning network specifically designed for classifying premature ventricular complexes (PVCs) in ECG images. It incorporates residual structures and attention mechanisms to enhance classification performance. PVCsNet consists of four 3×3 convolutional layers as feature extractors, followed by residual connections and attention blocks. This design enables the network to map image features to class probability distributions, enhancing performance even with limited data. Our experimental results demonstrate that using the SE Block with MaxPool and a ratio of 4, PVCsNet achieves an overall accuracy of 94.49%, with high precision in critical categories and a moderate parameter size. We successfully categorize the data into six distinct classes based on their origin locations in the heart: right ventricular outflow tract (RVOT), left ventricular outflow tract (LVOT), papillary muscle (PM), valvular annulus (VA), summit, and His-Purkinje system (HPS). Among these, RVOT is the most common and crucial origin of PVCs. PM and HPS are also significant origins due to their clinical implications. This study demonstrates the potential of PVCsNet in clinical diagnostics, providing promising results in classifying ECG images and contributing to future medical research and diagnosis.

Pacing of the specialized His-Purkinje conduction system: 'back to the future'.

The conduction system of the human heart is composed of specialized cardiomyocytes that initiate and propagate the electric impulse with consequent rhythmic and synchronized contraction of the atria and ventricles, resulting in the normal cardiac cycle. Although the His-Purkinje system (HPS) was already described more than a century ago, there has been a recent resurgence of conduction system pacing (CSP), where pacing leads are positioned in the His bundle region and left bundle branch area to provide physiological cardiac activation as alternatives to the unnatural myocardial stimulation obtained with conventional right ventricular and biventricular pacing. In this review, we describe the fundamental anatomical and pathophysiological aspects of the specialized HPS along with the CSP technique's nuts and bolts to highlight its potential benefits in everyday clinical practice.

Coronary Artery Radial Deformation and Velocity in Native and Stented Arteries.

Introduction Coronary arteries are exposed to a variety of complex biomechanical forces during a normal cardiac cycle. These forces have the potential to contribute to coronary stent failure. Recent advances in stent design allow for the transmission of native pulsatile biomechanical forces in the stented vessel. However, there is a significant lack of evidence in a human model to measure vessel motion in native coronary arteries and stent conformability. Thus, we aimed to characterize and define coronary artery radial deformation and the effect of stent implantation on arterial deformation. Materials and Methods Intravascular ultrasound (IVUS) pullback DICOM images were obtained from human coronary arteries using a coronary ultrasound catheter. Using two-dimensional speckle tracking, coronary artery radial deformation was defined as the inward and outward displacement (mm) and velocity (cm/s) of the arterial wall during the cardiac cycle. These deformation values were obtained in native and third-generation drug-eluting stented artery segments. Results A total of 20 coronary artery segments were independently analyzed pre and poststent implantation for a total of 40 IVUS runs. Stent implantation impacted the degree of radial deformation and velocity. Mean radial deformation in native coronary arteries was 0.1230 mm ± 0.0522 mm compared to 0.0775 mm ± 0.0376 mm in stented vessels (p=0.0031). Mean radial velocity in native coronary arteries was 0.1194 cm/s ± 0.0535 cm/s compared to 0.0840 cm/s ± 0.0399 cm/s in stented vessels (p=0.0228). Conclusion In this in vivo analysis of third-generation stents, stent implantation attenuates normal human coronary deformation during the cardiac cycle. The implications of these findings on stent failure and improved clinical outcomes require further investigation.

Intra and inter-patient arrhythmia classification using feature fusion with novel feature set based on fractional-order and fibonacci series

Cardiac ailments are increasing at an alarming rate globally due to the sedentary lifestyle and increased desk-bound activities. For decades, the ECG signal is used in aiding the analysis of human heart. Arrhythmia is a disorder that alters the normal cardiac cycle of ECG signal. The automatic classification of arrhythmia is a highly desirable and tough task. Mainly, the traditional methods of arrhythmia classification, are evaluated on the intra-patient criterion that may not befit the inter-patient criterion. A complete classification method has been proposed in the paper which performs well in intra-patient, inter-patient criterion and it is effective for minority class of MIT-BIH arrhythmia database (MIT-BIH-AD). In the proposed method, after preliminary processing based on Riesz fractional-order digital differentiator and R-peak detection, various features are extracted from ECG beat. The feature set proposed is a fusion of time-domain, time–frequency domain features and the new and novel features based on the Fibonacci series and coefficients of fractional-order Riesz based derivative signals which are proposed in this work. The results are evaluated on the MIT-BIH-AD and the results for intra-patients’ criterion have achieved an overall accuracy, sensitivity and positive predictivity values of 99.85%, 99.16%, 99.93% respectively, and for the inter-patient scheme 92.5%, 89.89% and 95.54% an average value of accuracy, sensitivity and positive predictivity of six ECG classes. The obtained results in both criterions have outperformed other methods in the literature and the proposed work has also attained better results for minority class of MIT-BIH-AD in both the scheme.

The Wright Table Project. Validating a Novel Active Learning Tool for the Cardiac Cycle in Valvular Pathologies

In response to students’ traditional struggles understanding the physiological dynamics of the cardiac cycle, the first author conceived a novel model, the Wright table of the cardiac cycle, that helps students visualize the heart working as a pump. This model shows direction of blood flow in response to pressure changes within cardiac chambers and major vessels, correlated with valve opening and closing as well as electrical events and auscultatory findings. Whether students could create and use Wright tables on their own as part of their active learning was unknown. Hypothesis We hypothesized that in mixed groups of year 1 & 2 medical students, that students would be capable of 1) creating versions of the Wright table for specific pathologies and 2) using this table as a teaching and learning tool to increase cardiac cycle and cardiac pathophysiology knowledge. Methods This initial phase of a multi-phase project was designed to validate the Wright Table as an active learning tool for cardiac physiology and pathophysiology using qualitative and quantitative data. Following IRB approval, teams of 2-3 students from research and cardiology clubs were each assigned 1 of 8 valvular disorders following their participation in an educational session on the Wright table for the normal cardiac cycle. Over three weeks, each team created a model for their condition citing resources used. Student-crafted Wright tables were presented in a Delphi-type session, allowing student attendees to choose, by anonymous vote, the best model representing each assigned cardiac pathology. Data collected and analyzed included qualitative process and progress feedback from student groups during model development; quantitative measurement of cardiac cycle physiology before and after initial exposure to the Wright table; and quantitative measurement of student understanding of cardiac valvular pathophysiology before and after the final Delphi session. Results 68 students began the study, and 46 finished all assignments. Of 32 starting groups, 22 tables with resources were submitted for Delphi review. In pre-and post-tests for valvular disorders, students demonstrated a significant increase in understanding valvular pathophysiology (36% to 47%, p< 0.001) after the Delphi session. The qualitative data revealed that the models that received the highest votes (>70%) were clear, simple, provided arrows to indicate blood flow, compared between either right and left heart or between normal and diseased heart, emphasized the damaged valve, highlighted the heart sounds and murmur, and provided brief notes on opening and closing of valves during the cardiac cycle. Conclusion The results have provided an initial level of validation for the Wright table of the cardiac cycle as an effective teaching tool for certain pathologies. The table can be used as an active learning tool by students to illustrate changes in cardiac pathophysiology in valvular disorders. Data from this process will inform the further development of this teaching tool. The next phase of this research project will include repeating this study with more time for student teams to research and create their respective tables.

An in vitro assessment of atrial fibrillation flow types on cardiogenic emboli trajectory paths.

Atrial fibrillation is the most significant contributor to thrombus formation within the heart and is responsible for 45% of all cardio embolic strokes, which account for approximately 15% of acute ischemic strokes cases worldwide. Atrial fibrillation can result in a reduction of normal cardiac output and cycle length of up to 30% and 40%, respectively. A total of 240 embolus analogues were released into a thin-walled, patient-specific aortic arch under normal (60 embolus analogues) and varying atrial fibrillation (180 embolus analogues) pulsatile flow conditions. Under healthy flow conditions (n = 60), the embolus analogues tended to follow the flow rate split through each outlet vessel. There was an increase in clot trajectories along the common carotid arteries under atrial fibrillation flow conditions. A shorter pulse period (0.3 s) displayed the highest percentage of clots travelling to the brain (24%), with a greater percentage of clots travelling through the left common carotid artery (17%). This study provides an experimental insight into the effect varying cardiac output and cycle length can have on the trajectory of a cardiac source blood clots travelling to the cerebral vasculature and possibly causing a stroke.

Hemodynamics and tissue biomechanics of the thoracic aorta with a trileaflet aortic valve at different phases of valve opening.

In a normal cardiac cycle, the trileaflet aortic valve opening is progressive, which correlates with the phasic blood flow. Therefore, we aimed to determine the impact of including an anatomically accurate reconstructed trileaflet aortic valve within a fluid-structure interaction (FSI) simulation model and determine the cyclical hemodynamic forces imposed on the thoracic aortic walls from aortic valve opening to closure. A pediatric patient with a normal trileaflet valve was recruited. Using the Cardiac Magnetic Resonance Data (CMR), a 3D model of the aortic valve and thoracic aorta was reconstructed. FSI simulations were employed to assess the tissue stress during a cardiac cycle as the result of changes in the valve opening. The blood flow was simulated as a mixture of blood plasma and red blood cells to account for non-Newtonian effects. The computation was validated with phase-contrast CMR. Windkessel boundary conditions were employed to ensure physiological pressures during the cardiac cycle. The leaflets' dynamic motion during the cardiac cycle was defined with an analytic grid velocity function. At the beginning of the valve opening a thin jet is developing. From mid-open towards full opening the stress level increases where the jet impinges the convex wall. At peak systole two counter-rotating Dean-like vortex cores manifest in the ascending aorta, which correlates with increased integrated mean stress levels. An accurate trileaflet aortic valve is needed for capturing of both primary and secondary flow features that impact the forces on the thoracic aorta wall. Omitting the aortic valve underestimates the biomechanical response.

An Approach for Automatic Identification of Fundamental and Additional Sounds from Cardiac Sounds Recordings.

This paper presents an approach for automatic segmentation of cardiac events from non-invasive sounds recordings, without the need of having an auxiliary signal reference. In addition, methods are proposed to subsequently differentiate cardiac events which correspond to normal cardiac cycles, from those which are due to abnormal activity of the heart. The detection of abnormal sounds is based on a model built with parameters which are obtained following feature extraction from those segments that were previously identified as normal fundamental heart sounds. The proposed algorithm achieved a sensitivity of 91.79% and 89.23% for the identification of normal fundamental, S1 and S2 sounds, and a true positive (TP) rate of 81.48% for abnormal additional sounds. These results were obtained using the PASCAL Classifying Heart Sounds challenge (CHSC) database.

Estimation of Mental Distress from Photoplethysmography

This paper introduces the design of a new wearable photoplethysmography (PPG) sensor and its assessment for mental distress estimation. In our design, a PPG sensor obtains blood volume information by means of an optical plethysmogram technique. A number of temporal, morphological and frequency markers are computed using time intervals between adjacent normal cardiac cycles to characterize pulse rate variability (PRV). In order to test the efficiency of the developed wearable for classifying distress versus calmness, the well-known International Affective Picture System has been used to induce different levels of arousal in forty-five healthy participants. The obtained results have shown that temporal features present a single discriminant power between emotional states of calm and stress, ranging from 67 to 72%. Moreover, a discriminant tree-based model is used to assess the possible underlying relationship among parameters. In this case, the combination of temporal parameters reaches 82.35% accuracy. Considering the low difficulty of metrics and methods used in this work, the algorithms are prepared to be embedded into a micro-controller device to work in real-time and in a long-term fashion.

The contribution of fatty acid and ketone body oxidation to energy production increases in the failing heart and is associated with a decrease in cardiac efficiency

Background: The failing heart is energy-starved and inefficient due to perturbations in energy metabolism. Since recent evidence suggests that ketone body oxidation increases in the failing heart as an adaptive mechanism to counteract reductions in fatty acid oxidation, our aim was to assess overall cardiac metabolism in heart failure, to establish what metabolic alterations contribute to reduced cardiac efficiency. Methods: C57BL/6J male mice (12 wk old) underwent either sham surgery, or transverse aortic constriction (TAC) surgery to induce pressure overload hypertrophy over a 4 wk period. Isolated working hearts from these mice were then perfused with appropriately 3H or 14C labelled glucose (5 mM), palmitate (0.8 mM), and ß-hydroxybutyrate (0.6 mM) to assess oxidative metabolism and glycolysis. Results: A 45% reduction in %EF was seen in intact TAC mice and a 54% decrease in cardiac work was seen in isolated working hearts from TAC mice. However, normal cardiac Krebs Cycle acetyl CoA production was seen compared to sham mice, reflecting a reduction in cardiac efficiency. Correspondingly, absolute glucose oxidation rates decreased in TAC compared to sham hearts, whereas absolute rates of fatty acid and ketone body oxidation were similar. However, normalization to cardiac work revealed that glucose oxidation was not depressed in failing hearts, although glycolysis was increased. Conversely, both fatty acid and ketone body oxidation increased in TAC hearts when normalized to cardiac work. This increased reliance on fatty acid oxidation challenges the current dogma suggesting that fatty acid oxidation is depressed in the failing heart. Conclusion: In the failing heart, a decreased cardiac efficiency is associated with increases in the contributions of ketone body and fatty acid oxidation to energy production. The latter observation suggests that normalizing excessive fatty acid oxidation in the failing heart may be a novel approach to improve cardiac efficiency.

Identification of Elevated ST Segment and Deep Q Type MI Variant Using Cross Wavelet Transform and Hierarchical Classification From ECG Signals

Coronary artery disease being one of the leading causes of mortality in the world requires prompt attention and for which technological intervention is helpful. The present manuscript proposes a cross wavelet transform based method for classification of Type I Inferior Myocardial Infraction (ST elevated and attenuated T wave) and Type II Inferior Myocardial Infarction (elongated Q wave and inverted T wave morphology). Cross-examination of cross-correlation between two time series reveals localised similarities in time-scale where distinguishing parameters for classification are extracted from wavelet cross spectrum and wavelet coherence. When ECG pattern in the QT region differ from the normal cardiac cycle and a variation is observed in the QT region of lead III, which gives an indication of Inferior MI. The WCS and WCOH of the ECG spectrum together show substantive spectral variations in the QRS complex region (R1) and over the T wave occurrences (R2). The classification of two types of MIs and normal parameters are identified from the corresponding regions R1 and R2. This method gives an accuracy of 99.43% for normal and abnormal class and 88.5 and 87.02% for Type I and Type II Inferior MI respectively.

Intraoperative management of critical arrhythmia.

The incidence of intraoperative arrhythmia is extremely high, and some arrhythmias require clinical attention. Therefore, it is essential for the anesthesiologist to evaluate risk factors for arrhythmia and understand their etiology, electrophysiology, diagnosis, and treatment. Anesthetic agents reportedly affect normal cardiac electrical activity. In the normal cardiac cycle, the sinoatrial node initiates cardiac electrical activity through intrinsic autonomous pacemaker activity. Sequential atrial and ventricular contractions result in an effective cardiac pumping mechanism. Arrhythmia occurs due to various causes, and the cardiac pumping mechanism may be affected. A severe case may result in hemodynamic instability. In this situation, the anesthesiologist should eliminate the possible causes of arrhythmia and manage the condition, creating hemodynamic stability under proper electrocardiographic monitoring.

Cardiac Catheterization and Intervention

Cardiac catheterization involves the insertion of a catheter (hollow polymer-coated tubing) into a blood vessel of the heart or into one of its chambers. Cardiac catheterization procedures are one of the most commonly performed cardiac procedures today. This review outlines the basics of angiography and coronary anatomy, the technical details of cardiac catheterizations, preferred access sites, and hemodynamic measurements. The basic steps in coronary intervention are listed. Common indications and contraindications for cardiac catheterization and intervention are described, as are appropriate use criteria for diagnostic catheterization and coronary intervention, fractional flow reserve (FFR) and intravascular ultrasonography, and complications of cardiac catheterization and percutaneous coronary intervention. Future directions in the field are discussed. Tables describe normal hemodynamic measurements, derived measurements during right heart catheterization, coronary artery disease prognostic index for medically managed patients, American College of Cardiology (ACC)/American Heart Association (AHA) guidelines regarding indications for coronary angiography, ACC/AHA appropriate use criteria for diagnostic catheterization, common indications for FFR, and risk of cardiac catheterization and coronary angiography. Figures include an overview of coronary anatomy, angiograms of the coronary arteries, images of a normal cardiac cycle and hemodynamic waveforms, the design of a stent, FFR evaluation, basic intravascular ultrasonography measurements, and coronary imaging with an optical coherence tomography system. This review contains 7 highly rendered figures, 8 tables, and 62 references.

Detection of systolic ejection click using time growing neural network

In this paper, we present a novel neural network for classification of short-duration heart sounds: the time growing neural network (TGNN). The input to the network is the spectral power in adjacent frequency bands as computed in time windows of growing length. Children with heart systolic ejection click (SEC) and normal children are the two groups subjected to analysis. The performance of the TGNN is compared to that of a time delay neural network (TDNN) and a multi-layer perceptron (MLP), using training and test datasets of similar sizes with a total of 614 normal and abnormal cardiac cycles. From the test dataset, the classification rate/sensitivity is found to be 97.0%/98.1% for the TGNN, 85.1%/76.4% for the TDNN, and 92.7%/85.7% for the MLP. The results show that the TGNN performs better than do TDNN and MLP when frequency band power is used as classifier input. The performance of TGNN is also found to exhibit better immunity to noise.

3D multifunctional integumentary membranes for spatiotemporal cardiac measurements and stimulation across the entire epicardium

Means for high-density multiparametric physiological mapping and stimulation are critically important in both basic and clinical cardiology. Current conformal electronic systems are essentially 2D sheets, which cannot cover the full epicardial surface or maintain reliable contact for chronic use without sutures or adhesives. Here we create 3D elastic membranes shaped precisely to match the epicardium of the heart via the use of 3D printing, as a platform for deformable arrays of multifunctional sensors, electronic and optoelectronic components. Such integumentary devices completely envelop the heart, in a form-fitting manner, and possess inherent elasticity, providing a mechanically stable biotic/abiotic interface during normal cardiac cycles. Component examples range from actuators for electrical, thermal and optical stimulation, to sensors for pH, temperature and mechanical strain. The semiconductor materials include silicon, gallium arsenide and gallium nitride, co-integrated with metals, metal oxides and polymers, to provide these and other operational capabilities. Ex vivo physiological experiments demonstrate various functions and methodological possibilities for cardiac research and therapy.

How to use…the paediatric ECG

Cardiac contraction is associated with electricity, discovered by Italian physicist Carlo Matteucci in 1842, subsequently captured as a tracing in 1878 by British physiologists John Burdon Sanderson and Frederick Page,...

Left ventricular vortex following atrial contraction and its interaction with early systolic ejection

Introduction: Flow inside cardiac chambers organises in vortices, rotational flow structures that could play a role in energy preservation, optimizing cardiac performance. No comparison has been established between the two vortices that appear in the left ventricle (LV) in a normal cardiac cycle, following early ventricular filling (V1) and atrial contraction (V2) and relating their potential differences to their role in cardiac performance. Objective and methods: To describe the potential differences between V1 and V2 and their significance in cardiac function, 50 patients (50% male, aged 53,4±29, LVEF 69,3%±14.8) in sinus rhythm and without valve disease underwent transthoracic echocardiography. LV 3-chamber views were acquired and analyzed using Vector Flow Mapping (VFM), a novel technique allowing intracardiac flow visualization. We measured parameters describing vortex flow intensity, size, location and duration. Results: No significant differences were observed between V1 and V2 in size or flow intensity. However, location and duration differed significantly between V1 and V2. V1 appeared close to the anterior wall, in the mid-basal region of the LV remaining there in 70% of patients. V2 initially appeared in the same region but evolved towards the submitral area in 84% of patients (Figure 1). V1 duration was significantly longer and with significantly higher variation than V2 (18% ± 13% vs. 15% ± 9% of the cardiac cycle, p = 0.017). ![Figure][1] Figure 1. Vortices' location Conclusions: Vortices generated in a normal cardiac cycle are similar in size and intensity, but their duration and position vary significantly. V2's shorter duration, change in position inside the LV and lower variability in its behaviour may be related to the opening of the aortic valve and closure of the anterior leaflet of the mitral valve. [1]: pending:yes

On the Projection Matrices Influence in the Classification of Compressed Sensed ECG Signals

In this paper the classification results of compressed sensed ECG signals based on various types of projection matrices is investigated. The compressed signals are classified using the KNN (K-Nearest Neighbour) algorithm. A comparative analysis is made with respect to the projection matrices used, as well as of the results obtained in the case of the original (uncompressed) signals for various compression ratios. For Bernoulli projection matrices it has been observed that the classification results for compressed cardiac cycles are comparable to those obtained for uncompressed cardiac cycles. Thus, for normal uncompressed cardiac cycles a classification ratio of 91.33% was obtained, while for the signals compressed with a Bernoulli matrix, up to a compression ratio of 15:1 classification rates of approximately 93% were obtained. Significant improvements of classification in the compressed space take place up to a compression ratio of 30:1.