Early Glaucoma Detection by Using Style Transfer to Predict Retinal Nerve Fiber Layer Thickness Distribution on the Fundus Photograph.

Objective: We aimed to develop a deep learning (DL)-based algorithm for early glaucoma detection based on color fundus photographs that provides information on defects in the retinal nerve fiber layer (RNFL) and its thickness from the mapping and translating relations of spectral domain OCT (SD-OCT) thickness maps. Design: Developing and evaluating an artificial intelligence detection tool. Subjects: Pretraining paired data of color fundus photographs and SD-OCT images from 189 healthy participants and 371 patients with early glaucoma were used. Methods: The variational autoencoder (VAE) network training architecture was used for training, and the correlation between the fundus photographs and RNFL thickness distribution was determined through the deep neural network. The reference standard was defined as a vertical cup-to-disc ratio of ≥0.7, other typical changes in glaucomatous optic neuropathy, and RNFL defects. Convergence indicates that the VAE has learned a distribution that would enable us to produce corresponding synthetic OCT scans. Main Outcome Measures: Similarly to wide-field OCT scanning, the proposed model can extract the results of RNFL thickness analysis. The structural similarity index measure (SSIM) and peak signal-to-noise ratio (PSNR) were used to assess signal strength and the similarity in the structure of the color fundus images converted to an RNFL thickness distribution model. The differences between the model-generated images and original images were quantified. Results: We developed and validated a novel DL-based algorithm to extract thickness information from the color space of fundus images similarly to that from OCT images and to use this information to regenerate RNFL thickness distribution images. The generated thickness map was sufficient for clinical glaucoma detection, and the generated images were similar to ground truth (PSNR: 19.31 decibels; SSIM: 0.44). The inference results were similar to the OCT-generated original images in terms of the ability to predict RNFL thickness distribution. Conclusions: The proposed technique may aid clinicians in early glaucoma detection, especially when only color fundus photographs are available.

Intelligent Bio-Impedance System for Personalized Continuous Blood Pressure Measurement.

Continuous blood pressure (BP) measurement is crucial for long-term cardiovascular monitoring, especially for prompt hypertension detection. However, most of the continuous BP measurements rely on the pulse transit time (PTT) from multiple-channel physiological acquisition systems that impede wearable applications. Recently, wearable and smart health electronics have become significant for next-generation personalized healthcare progress. This study proposes an intelligent single-channel bio-impedance system for personalized BP monitoring. Compared to the PTT-based methods, the proposed sensing configuration greatly reduces the hardware complexity, which is beneficial for wearable applications. Most of all, the proposed system can extract the significant BP features hidden from the measured bio-impedance signals by an ultra-lightweight AI algorithm, implemented to further establish a tailored BP model for personalized healthcare. In the human trial, the proposed system demonstrates the BP accuracy in terms of the mean error (ME) and the mean absolute error (MAE) within 1.7 ± 3.4 mmHg and 2.7 ± 2.6 mmHg, respectively, which agrees with the criteria of the Association for the Advancement of Medical Instrumentation (AAMI). In conclusion, this work presents a proof-of-concept for an AI-based single-channel bio-impedance BP system. The new wearable smart system is expected to accelerate the artificial intelligence of things (AIoT) technology for personalized BP healthcare in the future.

Electrocardiogram lead selection for intelligent screening of patients with systolic heart failure.

Electrocardiogram (ECG)-based intelligent screening for systolic heart failure (HF) is an emerging method that could become a low-cost and rapid screening tool for early diagnosis of the disease before the comprehensive echocardiographic procedure. We collected 12-lead ECG signals from 900 systolic HF patients (ejection fraction, EF < 50%) and 900 individuals with normal EF in the absence of HF symptoms. The 12-lead ECG signals were converted by continuous wavelet transform (CWT) to 2D spectra and classified using a 2D convolutional neural network (CNN). The 2D CWT spectra of 12-lead ECG signals were trained separately in 12 identical 2D-CNN models. The 12-lead classification results of the 2D-CNN model revealed that Lead V6 had the highest accuracy (0.93), sensitivity (0.97), specificity (0.89), and f1 scores (0.94) in the testing dataset. We designed four comprehensive scoring methods to integrate the 12-lead classification results into a key diagnostic index. The highest quality result among these four methods was obtained when Leads V5 and V6 of the 12-lead ECG signals were combined. Our new 12-lead ECG signal-based intelligent screening method using straightforward combination of ECG leads provides a fast and accurate approach for pre-screening for systolic HF.

Anti-Inflammatory and Antiarrhythmic Effects of Beta Blocker in a Rat Model of Rheumatoid Arthritis.

Background Patients with rheumatoid arthritis are at twice the risk of ventricular arrhythmia and sudden cardiac death as the general population. We hypothesize that ß-blocker treatment of rheumatoid arthritis is antiarrhythmic by producing synergistic anticatecholaminergic and anti-inflammatory effects. Methods and Results Collagen-induced arthritis (CIA) was induced in Lewis rats by immunization with type II collagen in Freund's incomplete adjuvant. The treatment with propranolol (4 mg/kg) started on the first day of immunization. We evaluated the ventricular vulnerability to ventricular arrhythmia using in vivo programmed stimulation and performed ex vivo optical mapping to measure the electrical remodeling of the heart. The ventricular tissue was further processed for immunohistochemical staining and protein array analysis. The assessment of ventricular vulnerability showed that the number and duration of the induced ventricular arrhythmia episodes were increased in CIA rats, which were improved with propranolol treatment. The sympathovagal index and the plasma level of catecholamines significantly increased in CIA rats, whereas the use of propranolol attenuated sympathetic hyperactivity. In the optical mapping study, electrical remodeling, characterized by prolonged action potential duration, slow conduction velocity, and steepened action-potential duration restitution, were noted in CIA rats and reversed in the propranolol-treatment group. The propranolol treatment was associated with decreases in paw thickness, fewer inflammatory cell infiltrations in the heart, reduced levels of cardiac inflammatory cytokines, and less cardiac fibrosis as compared with the CIA group. Conclusions CIA increased ventricular arrhythmia vulnerability through sympathetic hyperinnervation and proarrhythmic ventricular electrophysiological remodeling. Treatment with propranolol in CIA rats was both anti-inflammatory and antiarrhythmic.

Reverse electromechanical modelling of diastolic dysfunction in spontaneous hypertensive rat after sacubitril/valsartan therapy.

AIMS: Hypertension is a significant risk for the development of left ventricular hypertrophy, diastolic dysfunction, followed by heart failure and sudden cardiac death. While therapy with sacubitril/valsartan (SV) reduces the risk of sudden cardiac death in patients with heart failure and systolic dysfunction, the effect on those with diastolic dysfunction remains unclear. We hypothesized that, in the animal model of hypertensive heart disease, treatment with SV reduces the susceptibility to ventricular arrhythmia. METHODS AND RESULTS: Young adult female spontaneous hypertensive rats (SHRs) were randomly separated into three groups, which were SHRs, SHRs treated with valsartan, and SHRs treated with SV. In addition, the age-matched and weight-matched Wistar Kyoto rats were considered as controls, and there were 12 rats in each group. In vivo ventricular tachyarrhythmia induction and in vitro optical mapping were used to measure the inducibility of ventricular arrhythmias and to characterize the dynamic properties of electrical propagation. The level of small-conductance Ca2+ -activated potassium channel type 2 (KCNN2) was analysed in cardiac tissue. Compared with SHR with left ventricular hypertrophy, treatment with SV significantly improved cardiac geometry (relative wall thickness, 0.68 ± 0.11 vs. 0.76 ± 0.13, P < 0.05) and diastolic dysfunction (isovolumetric relaxation time, 59.4 ± 3.2 vs. 70.5 ± 4.2 ms, P < 0.05; deceleration time of mitral E wave, 46 ± 4.8 vs. 42 ± 3.8, P < 0.05). The incidence of induced ventricular arrhythmia was significantly reduced in SHR treated with SV compared with SHR (ventricular tachycardia, 1.14 ± 0.32 vs. 2.91 ± 0.5 episodes per 10 stimuli, P < 0.001; ventricular fibrillation, 1.72 ± 0.31 vs. 5.81 ± 0.42 episodes per 10 stimuli, P < 0.001). The prolonged action potential duration (APD) and increase of the maximum slope of APD restitution were observed in SHR, while the treatment of SV improved the arrhythmogeneity (APD, 37.12 ± 6.18 vs. 92.41 ± 10.71 ms at 250 ms pacing cycle length, P < 0.001; max slope 0.29 ± 0.01 vs. 1.48 ± 0.04, P < 0.001). These effects were strongly associated with down-regulation of KCNN2 (0.38 ± 0.07 vs. 0.74 ± 0.12 ng/ml, P < 0.001). The treatment of SV also decreased the level of N-terminal pro-B-type natriuretic peptide, cardiac bridging integrator-1, and intramyocardial fibrosis of SHR. CONCLUSIONS: In conclusion, synergistic blockade of the neprilysin and the renin-angiotensin system by SV in SHRs results in KCNN2-associated electrical remodelling in ventricle, which stabilizes electrical dynamics and attenuates arrhythmogenesis.

Effects of long-term exercise on arrhythmogenesis in aged hypertensive rats.

Chronic hypertension is a multifactorial disease that is highly associated with cardiovascular disorders. Physical activity, such as long-term exercise, is advocated as a treatment for hypertension, but the responses of different age groups to long-term exercise are unknown. We used aged spontaneous hypertensive rats (SHRs, 80 weeks old) to test the hypothesis that long-term exercise compensated for deficient autonomic control and reduced susceptibility to ventricular tachycardia (VT) and ventricular fibrillation (VF) in this animal model. The aged SHRs were divided into control and voluntary exercise groups. Ambulatory electrocardiography was recorded for the heart rate variability (HRV) analysis. Programmed stimulation was applied to exposed hearts to induce ventricular arrhythmia in situ. Then, the hearts were isolated for an optical mapping study. The results showed that increased HRV indices were broadly related to vagal dominance in the high-intensity exercise group. Exercise altered the electrical propagation dynamic properties, such as the action potential duration restitution (APDR). Furthermore, the VF inducibility decreased with increased exercise intensity. Taken together, our results suggest that long-term exercise reduces the risk of arrhythmogenesis in aged SHRs through enhanced vagal control and stabilized electrical dynamics.