Search Results (228)

Background and Purpose: The cerebral circulation is highly regulated to maintain brain perfusion, keeping an equilibrium between the brain tissue, cerebrospinal fluid (CSF) and blood of the arterial and venous systems. Cerebral venous drainage abnormalities have been implicated in multiple cerebrovascular diseases. The purpose of this study is to evaluate the relationship between the arterial inflow (AI) and the cerebral venous outflow (CVO) and their correlation with the cardiac outflow in healthy adults and children to understand the role of the emissary veins in normal venous drainage. Materials and Methods: A total of 31 healthy volunteers (24 adults (39.5 ± 16.0) and seven children (3.4 ± 2.2)) underwent intracranial 4D flow with full circle of Willis coverage and 2D PC-MRI at the level of the transverse sinus for measurement of the AI and CVO, respectively. The AI was calculated as the sum of the flow values in the bilateral internal carotid and basilar arteries. The CVO was calculated as the sum of the flow values in the bilateral transverse sinuses. The cardiac outflow was measured via 2D PC-MRI with retrospective ECG gating with images acquired at the proximal ascending aorta (AAo) and descending (DAo) aorta. The ratios of the AI/AAo flow and CVO/AI were calculated to characterize the fraction of cerebral arterial inflow in relation to cardiac outflow and venous blood draining through the transverse sinuses, respectively. Results: The AI and CVO were significantly correlated (r = 0.81, p < 0.001). The CVO constituted approximately 60–70% of the AI. The CVO/AI ratio was significantly lower in children versus adults (p = 0.025). In adults, the negative correlation of the AI with age remained strong (r = −0.81, p < 0.001). However, the CVO was not significantly associated with age. Conclusion: The CVO/AI ratio suggests an important role of the emissary veins, accounting for approximately 30–40% of venous drainage. The lower CVO/AI ratio in children, although partially related to decreased AI with age, suggests a greater role of the emissary veins in childhood, which strongly decreases with age. Full article

This paper introduces a novel deep learning model for ECG signal classification using feature fusion. The proposed methodology transforms the ECG time series into a spectrogram image using a short-time Fourier transform (STFT). This spectrogram is further processed to generate a histogram of oriented gradients (HOG) and local binary pattern (LBP) features. Three separate 2D convolutional neural networks (CNNs) then analyze these three image representations in parallel. To enhance performance, the extracted features are concatenated before feeding them into a gated recurrent unit (GRU) model. The proposed approach is extensively evaluated on two ECG datasets (MIT-BIH + BIDMC and MIT-BIH) with three and five classes, respectively. The experimental results demonstrate that the proposed approach achieves superior classification accuracy compared to existing algorithms in the literature. This suggests that the model has the potential to be a valuable tool for accurate ECG signal classification, aiding in the diagnosis and treatment of various cardiovascular disorders. Full article

Cardiovascular diseases pose a significant global health threat, with atrial fibrillation representing a critical precursor to more severe heart conditions. In this work, a multimodality-based deep learning model has been developed for diagnosing atrial fibrillation using an embedded system consisting of a Raspberry Pi 4B, an ESP8266 microcontroller, and an AD8232 single-lead ECG sensor to capture real-time ECG data. Our approach leverages a deep learning model that is capable of distinguishing atrial fibrillation from normal ECG signals. The proposed method involves real-time ECG signal acquisition and employs a multimodal model trained on the PTB-XL dataset. This model utilizes a multi-step approach combining a CNN–bidirectional LSTM for numerical ECG series tabular data and VGG16 for image-based ECG representations. A fusion layer is incorporated into the multimodal CNN-BiLSTM + VGG16 model to enhance atrial fibrillation detection, achieving state-of-the-art results with a precision of 94.07% and an F1 score of 0.94. This study demonstrates the efficacy of a multimodal approach in improving the real-time diagnosis of cardiovascular diseases. Furthermore, for edge devices, we have distilled knowledge to train a smaller student model, CNN-BiLSTM, using a larger CNN-BiLSTM model as a teacher, which achieves an accuracy of 83.21% with 0.85 s detection latency. Our work represents a significant advancement towards efficient and preventative cardiovascular health management. Full article

(1) Background: The novel SARS-CoV-2 virus infects the endothelium. Vasculitis may lead to specific coronary artery wall lesions. Coronary computed tomography angiography (CTA) imaging findings have not been systematically reported. The aim of this study was to describe a case series using CTA. (2) Methods: Patients with recent RT-PCR confirmed SARS-CoV-2 infection referred for coronary CTA for clinical indications (e.g., chest pain, troponin+, and ECG abnormalities) were included. Coronary CTA findings, such as atypical coronary lesions suggestive of vasculitis, perivascular inflammation measured by using pericoronary fat attenuation (PCAT) index, coronary artery disease, and extracoronary findings were collected. (3) Results: Results for 12 patients (54.8 ± 22 years; four females) with SARS-CoV-2 infection within 60 days (four acute care and eight stable patients) are reported. Time to positive RT-PCR was a mean of 15.1 days (range, 0–51). In four acute patients with signs of myocardial injury, plaque rupture (n = 1), hyperenhancing myocardium/MINOCA (n = 1), MINOCA (n = 1), and pericarditis with acute heart failure (LVEF 20%) (n = 1) were found. All (100%) had pericardial effusion and signs of perivascular inflammation. Among eight stable patients, pericardial effusion or perivascular inflammation were found in only two (25%). Coronary artery disease was ruled out in five (62.5%) (4) Conclusions: Coronary CTA is a useful imaging modality in the diagnostic work up of patients with COVID-19 infection, and is able to describe coronary and other cardiac abnormalities. Full article

Echocardiography (ECG) is a noninvasive technology that is widely used for recording heartbeats and diagnosing cardiac arrhythmias. However, interpreting ECG signals is challenging and may require substantial time from medical specialists. The evolution of technology and artificial intelligence has led to advances in the study and development of automatic arrhythmia classification systems to aid in medical diagnoses. Within this context, this paper introduces a framework for classifying cardiac arrhythmias on the basis of a multimodal convolutional neural network (CNN) with an adaptive attention mechanism. ECG signal segments are transformed into images via the Hilbert space-filling curve (HSFC) and recurrence plot (RP) techniques. The framework is developed and evaluated using the MIT-BIH public database in alignment with AAMI guidelines (ANSI/AAMI EC57). The evaluations accounted for interpatient and intrapatient paradigms, considering variations in the input structure related to the number of ECG leads (lead MLII and V1 + MLII). The results indicate that the framework is competitive with those in state-of-the-art studies, particularly for two ECG leads. The accuracy, precision, sensitivity, specificity and F1 score are 98.48%, 94.15%, 80.23%, 96.34% and 81.91%, respectively, for the interpatient paradigm and 99.70%, 98.01%, 97.26%, 99.28% and 97.64%, respectively, for the intrapatient paradigm. Full article

Background and Objectives: Although left ventricular excessive trabeculation (LVET) can cause heart failure, arrhythmia and thromboembolism, limited literature is available on the ECG characteristics of primary LVET with preserved left ventricular function (EF). We aimed to compare the ECG characteristics and cardiac MR (CMR) parameters of LVET individuals with preserved left ventricular EF to a control (C) group, to identify sex-specific differences, and to compare the genetic subgroups of LVET with each other and with a C population. Methods: In our study, we selected 69 LVET individuals (EF > 50%) without any comorbidities and compared them to 69 sex- and age-matched control subjects (42% females in both groups, p = 1.000; mean age LVET-vs-C: 38 ± 14 vs. 38 ± 14 years p = 0.814). We analyzed the pattern and notable parameters of the 12-lead ECG recordings. We determined the volumetric and functional parameters, as well as the muscle mass values of the left and right ventricles (LV, RV) based on the CMR recordings. Based on the genotype, three subgroups were established: pathogenic, variant of uncertain significance and benign. Results: In the LVET group, we found normal but elevated volumetric and muscle mass values and a decreased LV_EF, wider QRS, prolonged QTc, higher RV Sokolow index values and lower T wave amplitude compared to the C. When comparing MR and ECG parameters between genetic subgroups, only the QTc showed a significant difference. Over one-third of the LVET population had arrhythmic episodes and a positive family history. Conclusions: The subclinical morphological and ECG changes and the clinical background of the LVET group indicate the need for follow-up of this population, even with preserved EF. Full article

The management of resistant tuberculosis (tb) can be extremely difficult, especially in case of novel unpredicted complications. In this report, we present a case of a 48-year-old patient with pre-extensively drug-resistant (XDR) tb who received a treatment regimen including pretomanid, bedaquiline, linezolid, cycloserine, and amikacin and died due to myocarditis. Acquired resistance to first- and second-line drugs developed due to previous poor adherence to medication. The clinical presentation of the patient, along with her initial ultrasonographical, electrocardiogram (ECG), and laboratory examinations, were typical for acute myocarditis; however, the patient was considered unstable, and further investigations, including magnetic resonance imaging (MRI), pericardiocentesis, and endomyocardial biopsy were not performed. To our knowledge, this is the first case of myocarditis in such a patient, the clinical features of which raised a high suspicion of drug induction that could be attributed to the treatment regimen that was administered. Clinicians who manage cases of drug-resistant tb should be aware of this newly reported, potentially lethal, adverse event. Full article

Prehospital electrocardiogram (PH-ECG) transmission is an important technology for reducing door-to-balloon time, but the decision to transmit often depends on the discretion of emergency medical technicians (EMTs). Additionally, studies based on real-world data remain insufficient. This study reports a machine learning-based method for classifying the severity of PH-ECG images and explores its feasibility. PH-ECG data were compiled from 120 patients between September 2017 and September 2020. The model we created from these data was the first classification model for PH-ECG images using data from a Japanese study population and showed a weighted F1-score of 0.85 and an Area Under the Curve (AUC) of 0.93. This result can be interpreted as having an excellent balance of sensitivity and specificity. The Cohen’s Kappa coefficient between AI’s inferences and the correct labels created by two cardiologists was 0.68 (p < 0.05), which is considered “substantial” according to the guidelines presented by Landis and Koch. In this study, although we were not able to remove noise caused by patient movement or electrode detachment, the results indicate that image-based abnormality detection from PH-ECGs is feasible and effective, particularly in regions like Japan where ECG data are often stored and transmitted as images. In addition, in our region, paramedics follow a multi-step process to decide whether to transmit an ECG, which takes time for the first screening. However, if the ECG is transmitted when either the paramedics or the deep learning model detects an abnormality, it is expected to reduce reading time and door-to-balloon time, as well as decrease false negatives. Full article

Cardiovascular diseases (CVDs) continue to be a major global health concern, representing a leading cause of morbidity and mortality. This review provides a comprehensive examination of CVDs, encompassing their pathophysiology, diagnostic biomarkers, advanced imaging techniques, pharmacological treatments, surgical interventions, and the emerging role of herbal remedies. The review covers various cardiovascular conditions such as coronary artery disease, atherosclerosis, peripheral artery disease, deep vein thrombosis, pulmonary embolism, cardiomyopathy, rheumatic heart disease, hypertension, ischemic heart disease, heart failure, cerebrovascular diseases, and congenital heart defects. The review presents a wide range of cardiac biomarkers such as troponins, C-reactive protein, CKMB, BNP, NT-proBNP, galectin, adiponectin, IL-6, TNF-α, miRNAs, and oxylipins. Advanced molecular imaging techniques, including chest X-ray, ECG, ultrasound, CT, SPECT, PET, and MRI, have significantly enhanced our ability to visualize myocardial perfusion, plaque characterization, and cardiac function. Various synthetic drugs including statins, ACE inhibitors, ARBs, β-blockers, calcium channel blockers, antihypertensives, anticoagulants, and antiarrhythmics are fundamental in managing CVDs. Nonetheless, their side effects such as hepatic dysfunction, renal impairment, and bleeding risks necessitate careful monitoring and personalized treatment strategies. In addition to conventional therapies, herbal remedies have garnered attention for their potential cardiovascular benefits. Plant extracts and their bioactive compounds, such as flavonoids, phenolic acids, saponins, and alkaloids, offer promising cardioprotective effects and enhanced cardiovascular health. This review underscores the value of combining traditional and modern therapeutic approaches to improve cardiovascular outcomes. This review serves as a vital resource for researchers by integrating a broad spectrum of information on CVDs, diagnostic tools, imaging techniques, pharmacological treatments and their side effects, and the potential of herbal remedies. Full article

In electrocardiograms (ECGs), multiple forms of encryption and preservation formats create difficulties for data sharing and retrospective disease analysis. Additionally, photography and storage using mobile devices are convenient, but the images acquired contain different noise interferences. To address this problem, a suite of novel methodologies was proposed for converting paper-recorded ECGs into digital data. Firstly, this study ingeniously removed gridlines by utilizing the Hue Saturation Value (HSV) spatial properties of ECGs. Moreover, this study introduced an innovative adaptive local thresholding method with high robustness for foreground–background separation. Subsequently, an algorithm for the automatic recognition of calibration square waves was proposed to ensure consistency in amplitude, rather than solely in shape, for digital signals. The original signal reconstruction algorithm was validated with the MIT–BIH and PTB databases by comparing the difference between the reconstructed and the original signals. Moreover, the mean of the Pearson correlation coefficient was 0.97 and 0.98, respectively, while the mean absolute errors were 0.324 and 0.241, respectively. The method proposed in this study converts paper-recorded ECGs into a digital format, enabling direct analysis using software. Automated techniques for acquiring and restoring ECG reference voltages enhance the reconstruction accuracy. This innovative approach facilitates data storage, medical communication, and remote ECG analysis, and minimizes errors in remote diagnosis. Full article

Sarcoidosis is an inflammatory condition that can affect multiple organ systems and is characterized by the formation of non-caseating granulomas in various organs, including the heart. Due to suboptimal diagnostic rates, the true prevalence and incidence of cardiac sarcoidosis (CS) remain to be determined. In patients with suspected CS, an initial examination should include 12-lead ECG or ambulatory ECG monitoring, and echocardiography with the estimation of LV, RV function, and strain rate. In patients with confirmed extracardiac sarcoidosis and with high clinical suspicion for CS, sophisticated imaging modalities, including cardiac MRI and PET, are indicated. Typical inflammation patterns and myocardial scarring should pose a high suspicion for CS. In patients without diagnosed extracardiac sarcoidosis and high clinical suspicion, although with low diagnostic probability, an endomyocardial biopsy should be considered to establish the diagnosis of definite isolated cardiac sarcoidosis. Timely diagnosis enables the initiation of therapy and close monitoring of adverse cardiac events that can be life-threatening, including sudden cardiac death, ventricular tachycardia, high-degree AV block, and heart failure. Implementing biomarkers in correlation to cardiac imaging can determine the disease’s severity and progression but can also be helpful in following the treatment response. The formation of larger global registries can be helpful in the identification of independent predictors of adverse clinical events and the development of specific diagnostic algorithms to reduce the overall risk of this serious condition. Full article

Congenital heart diseases (CHD) are one of the most common birth defects and the main leading cause of death in children. Many patients with CHD are reaching adulthood due to the success of improved contemporary surgical procedures. Understanding the etiology of CHD remains important for patient clinical management. Both genetic and environmental factors are involved in the development and progression of CHD. Variations in many different genes and chromosomal anomalies can be associated with CHD, by expression of different mechanisms. Sporadic cases are the most frequently encountered in these patients. Atrial septal defect is a common congenital heart disease that refers to direct communication between atrial chambers, found isolated or associated with other syndromes. Imaging techniques, especially transthoracic and transesophageal echocardiography (TOE) represent the key for diagnosis and management of ASD. The disease has a major incidence in adulthood, due to late symptomatology, but assessment and treatment are important to avoid time-related complications. Ebstein’s anomaly is a rare congenital disease, with a dominant genetic participation, characterized by an abnormal displacement of the tricuspid valve and right ventricular myopathy, often requiring surgical intervention. Alongside echocardiography, cardiac magnetic resonance (CMR) imaging is the gold standard tool for the assessment of ventricular volumes. Early diagnosis and adequate treatment are mandatory to avoid possible complications of CHD, and thus, ECG, as well as imaging techniques, are important diagnostic tools. However, patients with CHD need a special healthcare team for the entire monitorization in various life stages. Full article

Fetal magnetic resonance imaging (fMRI) represents a second-line imaging modality that provides multiparametric and multiplanar views that are crucial for confirming diagnoses, detecting associated pathologies, and resolving inconclusive ultrasound findings. The introduction of high-field magnets and new imaging sequences has expanded MRI’s role in pregnancy management. Recent innovations in ECG-gating techniques have revolutionized the prenatal evaluation of congenital heart disease by synchronizing imaging with the fetal heartbeat, thus addressing traditional challenges in cardiac imaging. Fetal cardiac MRI (fCMR) is particularly valuable for assessing congenital heart diseases, especially when ultrasound is limited by poor imaging conditions. fCMR allows for detailed anatomical and functional evaluation of the heart and great vessels and is also useful for diagnosing additional anomalies and analyzing blood flow patterns, which can aid in understanding abnormal fetal brain growth and placental perfusion. This review emphasizes fMRI’s potential in evaluating cardiac and thoracic structures, including various gating techniques like metric optimized gating, self-gating, and Doppler ultrasound gating. The review also covers the use of static and cine images for structural and functional assessments and discusses advanced techniques like 4D-flow MRI and T1 or T2 mapping for comprehensive flow quantification and tissue characterization. Full article

In this paper, a novel deep learning method Mamba-RAYOLO is presented, which can improve detection and classification in the processing and analysis of ECG images in real time by integrating three advanced modules. The feature extraction module in our work with a multi-branch structure during training can capture a wide range of features to ensure efficient inference and rich feature extraction. The attention mechanism module utilized in our proposed network can dynamically focus on the most relevant spatial and channel-wise features to improve detection accuracy and computational efficiency. Then, the extracted features can be refined for efficient spatial feature processing and robust feature fusion. Several sets of experiments have been carried out to test the validity of the proposed Mamba-RAYOLO and these indicate that our method has made significant improvements in the detection and classification of ECG images. The research offers a promising framework for more accurate and efficient medical ECG diagnostics. Full article

The use of bioprostheses is increasing in younger patients, but it is associated with the risk of later valve deterioration, especially in the mitral position. A new bioprosthesis for mitral valve replacement offers possible longer-term durability and improved hemodynamics. Objectives: Here, we report the implantation of the novel Edwards MITRIS RESILIA mitral valve (Edwards Lifesciences Inc., Irvine, CA, USA) through microinvasive fully endoscopic access as an innovative surgical approach based on a series of twelve patients. Methods: Contrast-based ECG gated CT was preoperatively performed in all patients to determine the intravascular calcifications and vascular parameters, as well as to assess noticeable problems during the operation. CT software for cardiac interventions (3Mensio Medical Imaging BV) was used to simulate surgical prostheses digitally inside the native annulus. With this, a digital LVOT and neo LVOT was created, and the difference between the valve prostheses was measured. Implantation of the MITRIS RESILIA valve was performed in 12 patients according to the instructions for use through microinvasive access in a fully endoscopic fashion using 3D visualization. Results: The mean patient age was 56.50 years, and 7/12 (58.33%) were redo procedures. All patients survived the first 30 days after the procedure, the mean aortic cross-clamp time was 40.17 ± 13.72 min. and mean postoperative transvalvular gradient was 4.45 ± 1.74 mmHg. The neo LVOT in the CT-based simulation was measured with an average area of 414.98 ± 88.69 mm². The average difference between the LVOT and neo LVOT area was 65.35 ± 34.99 mm². There was no case of paravalvular leakage or obstruction of the left ventricular outflow tract. Conclusions: The novel MITRIS RESILIA valve is a promising new bioprosthesis for mitral valve replacement that offers improved features as compared to other prostheses. The ease of implantation is increased by this prosthesis by the improved pliability of the sewing cuff and the inward folding of the struts, which was confirmed by short operative times in our series. Full article