Value of three-dimensional strain parameters for predicting left ventricular remodeling after ST-elevation myocardial infarction

High-Resolution Maps of Left Atrial Displacements and Strains Estimated With 3D Cine MRI Using Online Learning Neural Networks

The functional analysis of the left atrium (LA) is important for evaluating cardiac health and understanding diseases like atrial fibrillation. Cine MRI is ideally placed for the detailed 3D characterization of LA motion and deformation but is lacking appropriate acquisition and analysis tools. Here, we propose tools for the Analysis of Left Atrial Displacements and DeformatIons using online learning neural Networks (Aladdin) and present a technical feasibility study on how Aladdin can characterize 3D LA function globally and regionally. Aladdin includes an online segmentation and image registration network, and a strain calculation pipeline tailored to the LA. We create maps of LA Displacement Vector Field (DVF) magnitude and LA principal strain values from images of 10 healthy volunteers and 8 patients with cardiovascular disease (CVD), of which 2 had large left ventricular ejection fraction (LVEF) impairment. We additionally create an atlas of these biomarkers using the data from the healthy volunteers. Results showed that Aladdin can accurately track the LA wall across the cardiac cycle and characterize its motion and deformation. Global LA function markers assessed with Aladdin agree well with estimates from 2D Cine MRI. A more marked active contraction phase was observed in the healthy cohort, while the CVD $\text {LVEF}_{\downarrow } $ group showed overall reduced LA function. Aladdin is uniquely able to identify LA regions with abnormal deformation metrics that may indicate focal pathology. We expect Aladdin to have important clinical applications as it can non-invasively characterize atrial pathophysiology. All source code and data are available at: https://github.com/cgalaz01/aladdin_cmr_la.

Prognostic Value of Advanced Echocardiography in Patients with Ischemic Heart Disease: A Comprehensive Review

Cardiovascular (CV) diseases caused 20.5 million deaths in 2021, making up nearly one-third of global mortality. This highlights the need for practical prognostic markers to better classify patients and guide treatment, especially in ischemic heart disease (IHD), which represents one of the leading causes of CV mortality. Transthoracic echocardiography (TTE) is a key, non-invasive imaging tool widely used in cardiology for diagnosing and managing a range of CV conditions. It is the first choice for diagnosing and monitoring patients with acute coronary syndrome (ACS). Alongside well-established echocardiographic measures, new techniques have proven useful for predicting adverse events in IHD patients, such as three-dimensional (3D) and tissue Doppler imaging (TDI), and speckle tracking technology. This review aims to explore the latest echocardiographic tools that could provide new prognostic markers for patients in the acute phase and during follow-up after an acute myocardial infarction (AMI). We focus on new imaging methods like TDI, myocardial work index (MWI), speckle-tracking strain, and 3D technologies using TTE, which are easy to use and widely available at all stages of coronary artery disease (CAD).

Values of three-dimensional speckle tracking imaging for the diagnosis of coronary artery disease

Background: Coronary artery disease (CAD) is a top life-threatening disease and early and sensitive detection of CAD remains a challenge. This study aimed to assess the value of three-dimensional speckle tracking imaging (3D-STI) in diagnosing CAD patients and investigate the parameters of 3D-STI associated with disease severity. Methods: A total of 260 suspected CAD patients who met the study criteria underwent coronary angiography within one week after the ultrasound examination. Based on the examination results, 142 patients were confirmed to have CAD (CAD group), while 118 patients were classified as non-CAD (NCAD group). Age, gender, family history, smoking status, diabetes, hypertension, dyslipidemia, electrocardiogram, BMI, heart rate, and left ventricular ejection fraction were compared between the two groups. Additionally, 3D-STI parameters including left ventricular global radial strain (GRS), left ventricular global longitudinal strain (GLS), left ventricular global area strain (GAS), and left ventricular global circumferential strain (GCS) were analyzed. Results: No significant differences were found between the CAD and NCAD groups in terms of demographics, smoking history, physiological measurements, and common comorbidities such as diabetes mellitus and dyslipidemia. However, when comparing the 3D-STI parameters, all four parameters, including GLS, GRS, GCS, and GAS, were significantly different in the CAD group compared to the NCAD group. The results suggest that 3D-STI parameters have diagnostic value for CAD, and their changes are associated with CAD severity. Conclusions: Combined detection of these parameters enhances diagnostic accuracy compared to individual detection.

Clinical Utility of Three-Dimensional Speckle-Tracking Echocardiography in Heart Failure

Heart failure (HF) is an extremely major health problem with gradually increasing incidence in developed and developing countries. HF may lead to cardiac remodeling; thus, advanced imaging techniques are required to comprehensively evaluate cardiac mechanics. Recently, three-dimensional speckle-tracking echocardiography (3D-STE) has been developed as a novel imaging technology that is based on the three-dimensional speckle-tracking on the full volume three-dimensional datasets. Three-dimensional speckle-tracking echocardiography allows a more accurate evaluation of global and regional myocardial performance, assessment of cardiac mechanics, detection of subclinical cardiac dysfunction, and prediction of adverse clinical events in a variety of cardiovascular diseases. Therefore, this review summarizes the clinical usefulness of 3D-STE in patients with HF.

Left atrial strain and recurrence of atrial fibrillation after thoracoscopic surgical ablation: a subanalysis of the AFACT study

To assess transthoracic echocardiographic (TTE) left atrial (LA) strain parameters and their association with atrial fibrillation (AF) recurrence after thoracoscopic surgical ablation (SA) in patients in sinus rhythm (SR) or in AF at baseline. Patients participating in the Atrial Fibrillation Ablation and Autonomic Modulation via Thoracoscopic Surgery trial were included. All patients underwent thoracoscopic pulmonary vein isolation with LA appendage exclusion and were randomized to ganglion plexus (GP) or no GP ablation. In TTEs performed before surgery, LA strain and mechanical dispersion (MD) of the LA reservoir and conduit phase in all patients, and of the contraction phase in patients in SR were obtained. Recurrence of AF was defined as any documented atrial tachyarrhythmia lasting > 30 s during one year of follow-up. Two hundred and four patients (58.6 ± 7.8 years, 73% male, 57% persistent AF) were included. At baseline TTE 121 (59%) were in SR and 83 (41%) had AF. Patients with AF recurrence had lower LA strain of the reservoir phase (13.0% vs. 16.6%; p =  < 0.001) and a less decrease in strain of the conduit phase (−9.0% vs. −11.8%; p = 0.006), regardless of rhythm. MD of the conduit phase was larger in patients with AF recurrence (79.4 vs. 43.5 ms; p = 0.012). Multivariate cox regression analysis demonstrated solely an association between LA strain of the reservoir phase and AF recurrence in patients in SR (HR 0.95, p = 0.046) or with AF (HR 0.90, p = 0.038). A reduction in LA strain of the reservoir phase prior to SA predicts recurrence of AF in both patients with SR or AF. Left atrial strain assessment may therefore add to a better patient selection for SA.

Myocardial strain analysis of echocardiography based on deep learning

BACKGROUND

Strain analysis provides more thorough spatiotemporal signatures for myocardial contraction, which is helpful for early detection of cardiac insufficiency. The use of deep learning (DL) to automatically measure myocardial strain from echocardiogram videos has garnered recent attention. However, the development of key techniques including segmentation and motion estimation remains a challenge. In this work, we developed a novel DL-based framework for myocardial segmentation and motion estimation to generate strain measures from echocardiogram videos.

METHODS

Three-dimensional (3D) Convolutional Neural Network (CNN) was developed for myocardial segmentation and optical flow network for motion estimation. The segmentation network was used to define the region of interest (ROI), and the optical flow network was used to estimate the pixel motion in the ROI. We performed a model architecture search to identify the optimal base architecture for motion estimation. The final workflow design and associated hyperparameters are the result of a careful implementation. In addition, we compared the DL model with a traditional speck tracking algorithm on an independent, external clinical data. Each video was double-blind measured by an ultrasound expert and a DL expert using speck tracking echocardiography (STE) and DL method, respectively.

RESULTS

The DL method successfully performed automatic segmentation, motion estimation, and global longitudinal strain (GLS) measurements in all examinations. The 3D segmentation has better spatio-temporal smoothness, average dice correlation reaches 0.82, and the effect of target frame is better than that of previous 2D networks. The best motion estimation network achieved an average end-point error of 0.05 ± 0.03 mm per frame, better than previously reported state-of-the-art. The DL method showed no significant difference relative to the traditional method in GLS measurement, Spearman correlation of 0.90 (p < 0.001) and mean bias -1.2 ± 1.5%.

CONCLUSION

In conclusion, our method exhibits better segmentation and motion estimation performance and demonstrates the feasibility of DL method for automatic strain analysis. The DL approach helps reduce time consumption and human effort, which holds great promise for translational research and precision medicine efforts.

Segmentation of Coronary Arteries Images Using Spatio-temporal Feature Fusion Network with Combo Loss

PURPOSE

Coronary heart disease is a serious disease that endangers human health and life. In recent years, the incidence and mortality of coronary heart disease have increased rapidly. The quantification of the coronary artery is critical in diagnosing coronary heart disease.

METHODS

In this paper, we improve the coronary arteries segmentation performance from two aspects of network model and algorithm. We proposed a U-shaped network based on spatio-temporal feature fusion structure to segment coronary arteries from 2D slices of computed tomography angiography (CTA) heart images. The spatio-temporal feature combines features of multiple levels and different receptive fields separately to get more precise boundaries. It is easy to cause over-segmented for the small proportion of coronary arteries in CTA images. For this reason, a combo loss function was designed to deal with the notorious imbalance between inputs and outputs that plague learning models. Input imbalance refers to the class imbalance in the input training samples. The output imbalance refers to the imbalance between the false positive and false negative of the inference model. The two imbalances in training and inference were divided and conquered with our combo loss function. Specifically, a gradient harmonizing mechanism (GHM) loss was employed to balance the gradient contribution of the input samples and at the same time punish false positives/negatives using another sensitivity-precision loss term to learn better model parameters gradually.

RESULTS

Compared with some existing methods, our proposed method improves the segmentation accuracy significantly, achieving the mean Dice coefficient of 0.87. In addition, accurate results can be obtained with little data using our method. Code is available at: https://github.com/Ariel97-star/FFNet-CoronaryArtery-Segmentation .

CONCLUSIONS

Our method can intelligently capture coronary artery structure and achieve accurate flow reserve fraction (FFR) analysis. Through a series of steps such as CPR curved reconstruction, the detection of coronary heart disease can be achieved without affecting the patient's body. In addition, our work can be used as an effective means to assist in the detection of stenosis. In the screening of coronary heart disease among high-risk cardiovascular factors, automatic detection of luminal stenosis can be performed based on the application of later algorithm transformation.

Use of Longitudinal Strain Bull’s-Eye Plot by Speckle Tracking Echocardiography for Evaluation of Homozygous Familial Hypercholesterolemia with Myocardial Ischemia

Background: In recent years, two-dimensional speckle tracking echocardiography (2D-STE) has been increasingly used to detect left ventricular myocardial ischemia with high accuracy for a reliable and comprehensive assessment of myocardial function by myocardial strain analysis. The present study aimed to assess whether the longitudinal strain (LS) bull’s eye plot could accurately detect left ventricular myocardial ischemia in homozygous familial hypercholesterolemia (HoFH) patients. Methods: A total of 28 HoHF patients, who underwent 2D-STE and myocardial perfusion imaging (MPI), were classified into two groups as diagnosed by MPI for myocardial ischemia. The myocardial ischemia score by MPI, LS bull’s-eye plot, and strain parameters were analyzed and compared. Results: Among the 28 HoFH patients, MPI detected 30.77% and 2D-STE showed 30.19% ischemic segments in 13 and 15 HoFH patients with myocardial ischemia, respectively. All segmental LSs in the left anterior descending artery (LAD) perfusion territory were significantly decreased in patients with myocardial ischemia. The diagnostic capability of 2D-STE for myocardial ischemia was 85.29%, 95.34%, and 93.91% for sensitivity, specificity and accuracy, respectively. Conclusion: Left ventricular LS bull’s-eye plot can assist rapid and accurate evaluation of myocardial ischemia in HoFH patients. The myocardial ischemia is mainly distributed in the LAD perfusion territory in these patients.

Cardiac Magnetic Resonance Feature Tracking: A Novel Method to Assess Left Ventricular Three-Dimensional Strain Mechanics After Chronic Myocardial Infarction

RATIONALE AND OBJECTIVES

This study was designed to assess left ventricular deformation after chronic myocardial infarction (CMI) using cardiac magnetic resonance feature tracking (CMR-FT) technology, and analyze its relationship with left ventricular ejection fraction (LVEF) and infarcted transmurality.

MATERIALS AND METHODS

Ninety-six patients with CMI and 72 controls underwent 3.0 T CMR scanning. Strain parameters were measured by dedicated software, including global peak longitudinal strain (GPLS), global peak circumferential strain (GPCS), global peak radial strain (GPRS), segmental peak longitudinal strain (PLS), peak circumferential strain (PCS), and peak radial strain (PRS). All enhanced myocardium segments were divided into subendocardial infarction (SI) and transmural infarction (TI) group. Pearson, intraclass correlation coefficient and receiver operating characteristic analysis were performed to compare the parameters' mean values between SI and TI groups.

RESULTS

GPLS, GPRS, and GPCS in CMI group were significantly decreased comparing with control group. PRS and PCS in TI group were significantly lower than those in SI group, whereas no statistical difference was observed in PLS. In Pearson correlation analysis, LVEF was strongly correlated with GPLS, GPRS, and GPCS in CMI patients. Additionally, excellent reproducibility of all strain parameters was observed. In receiver operating characteristic analysis, segmental PRS and PCS might differentiate SI from TI with higher diagnostic efficiency (p < 0.05), while PLS was less valuable (p > 0.05).

CONCLUSION

CMR-FT could noninvasively and quantitatively assess global and regional myocardial strain in CMI patients with excellent reproducibility and strong correlation with LVEF. Additionally, segmental myocardial strain parameters indicate potential clinical value in differentiating myocardial infarction subtype.

The effect of nurse-led interventions on re-admission and mortality for congestive heart failure: A meta-analysis

BACKGROUND

The European Society of Cardiology guidelines recommend the implementation of nurse-led heart failure programs to achieve optimal management of patients with congestive heart failure (CHF). In this analysis, we aimed to systematically show the impact of nurse-led interventions (NLI) on re-admission and mortality in patients with CHF (reduced ejection fraction).

METHODS

Publications reporting the impact of NLI on readmission and mortality in patients with CHF were carefully searched from electronic databases. Rehospitalization and mortality were the endpoints. For this analysis, the latest version of the RevMan software was used. Risk ratios (RR) with 95% confidence intervals (CI) were used to represent data following analysis.

RESULTS

A total number of 3282 participants with CHF were included in this analysis. A total of 1571 patients were assigned to the nurse-led intervention group whereas 1711 patients were assigned to the usual care group. The patients had a mean age ranging from 50.8 to 80.3 years. Male patients varied from 27.3% to 73.8%. Comorbidities including hypertension (24.6%-80.0%) and diabetes mellitus (16.7%-59.7%) were also reported. Patients had a mean left ventricular ejection fraction varying from 29.0% to 61.0%. Results of this current analysis showed that rehospitalization (RR: 0.81, 95% CI: 0.74-0.88; P = .00001) and mortality (RR: 0.69, 95% CI: 0.56-0.86; P = .0009) were significantly lower among CHF patients who were assigned to the nurse-led intervention. Whether during a shorter (3-6 months) or a longer (1-2 years) follow up time period, rehospitalization for shorter [(RR: 0.73, 95% CI: 0.65-0.82; P = .00001) vs for longer (RR: 0.81, 95% CI: 0.72-0.91; P = .0003) respectively] and mortality for shorter [(RR: 0.55, 95% CI: 0.38-0.80; P = .002) vs longer follow up time period (RR: 0.76, 95% CI: 0.58-0.99; P = .04) respectively] were significantly lower and in favor of the nurse-led interventional compared to the normal care group.

CONCLUSIONS

This systematic review and meta-analysis of randomized controlled trials showed that NLI had significant impacts in reducing the risk of rehospitalization and mortality in these patients with CHF (reduced ejection fraction). Hence, we believe that nurse-led clinics and other interventional programs would be beneficial to patients with heart failure and this practice should, in the future be implemented to the health care system.

Heart failure after myocardial infarction: incidence and predictors

Aims

The aim of the present paper was to provide an up‐to‐date view on epidemiology and risk factors of heart failure (HF) development after myocardial infarction.

Methods and results

Based on literature review, several clinical risk factors and biochemical, genetic, and imaging biomarkers were identified to predict the risk of HF development after myocardial infarction.

Conclusions

Heart failure is still a frequent complication of myocardial infarction. Timely identification of subjects at risk for HF development using a multimodality approach, and early initiation of guideline‐directed HF therapy in these patients, can decrease the HF burden.

Copeptin levels predict left ventricular systolic function in STEMI patients: A 2D speckle tracking echocardiography-based prospective observational study

In the present study, we aimed to investigate whether copeptin values on admission are related to left ventricle (LV) systolic function and its improvement at 6 months in ST-segment elevation myocardial infarction (STEMI) patients.In this single-center, prospective observational study, we included 122 STEMI patients from January 2016 to November 2016. LV systolic functions in the form of global longitudinal strain (GLS) in addition to conventional echocardiography parameters were evaluated on admission and at 6-month. Serum copeptin levels were determined using an ultrasensitive immunofluorescence assay.The study population was divided into 2 groups according to median values of copeptin. GLS was significantly lower in patients with high copeptin levels compared to those with low copeptin levels at early stage and 6-month (-16% (16-16.5) vs -15% (15-15.5), P < .001 and -18% (18-19) vs -16% (16-16.25), P < .001, respectively). Copeptin values were negatively correlated with an early and 6-month GLS (r = -0.459 at early stage and r = -0.662 at 6-month). In addition, we observed that copeptin values were negatively correlated with the improvement of GLS at 6-month follow-up (r = -0.458, P < .001 and r = -0.357, P = .005, respectively).Serum copeptin levels in STEMI patients at the time of admission may predict early and 6-month LV systolic function assessed by two-dimensional GLS. To the best of our knowledge, this study is the first to specifically address the relationship between copeptin values and GLS in STEMI patients.

Deep learning analysis in coronary computed tomographic angiography imaging for the assessment of patients with coronary artery stenosis

BACKGROUND AND OBJECTIVE

Recently, deep convolutional neural network has significantly improved image classification and image segmentation. If coronary artery disease (CAD) can be diagnosed through machine learning and deep learning, it will significantly reduce the burdens of the doctors and accelerate the critical patient diagnoses. The purpose of the study is to assess the practicability of utilizing deep learning approaches to process coronary computed tomographic angiography (CCTA) imaging (termed CCTA-artificial intelligence, CCTA-AI) in coronary artery stenosis.

MATERIALS AND METHODS

A CCTA reconstruction pipeline was built by utilizing deep learning and transfer learning approaches to generate auto-reconstructed CCTA images based on a series of two-dimensional (2D) CT images. 150 patients who underwent successively CCTA and digital subtraction angiography (DSA) from June 2017 to December 2017 were retrospectively analyzed. The dataset was divided into two parts comprising training dataset and testing dataset. The training dataset included the CCTA images of 100 patients which are trained using convolutional neural networks (CNN) in order to further identify various plaque classifications and coronary stenosis. The other 50 CAD patients acted as testing dataset that is evaluated by comparing the auto-reconstructed CCTA images with traditional CCTA images on the condition that DSA images are regarded as the reference method. Receiver operating characteristic (ROC) analysis was used for statistical analysis to compare CCTA-AI with DSA and traditional CCTA in the aspect of detecting coronary stenosis and plaque features.

RESULTS

AI significantly reduces time for post-processing and diagnosis comparing to the traditional methods. In identifying various degrees of coronary stenosis, the diagnostic accuracy of CCTA-AI is better than traditional CCTA (AUC_AI = 0.870, AUC_CCTA = 0.781, P < 0.001). In identifying ≥ 50% stenotic vessels, the accuracy, sensitivity, specificity, positive predictive value and negative predictive value of CCTA-AI and traditional method are 86% and 83%, 88% and 59%, 85% and 94%, 73% and 84%, 94% and 83%, respectively. In the aspect of identifying plaque classification, accuracy of CCTA-AI is moderate compared to traditional CCTA (AUC = 0.750, P < 0.001).

CONCLUSION

The proposed CCTA-AI allows the generation of auto-reconstructed CCTA images from a series of 2D CT images. This approach is relatively accurate for detecting ≥50% stenosis and analyzing plaque features compared to traditional CCTA.

The effect of nicorandil in patients with cardiac syndrome X: A meta-analysis of randomized controlled trials

BACKGROUND

The prevalence of cardiac syndrome X (CSX) is considerable. Some patients show recurrent angina attacks and have a poor prognosis. However, the knowledge of CSX pathophysiological mechanism is still limited, and the treatment fails to achieve a satisfactory suppression of symptoms. Nicorandil has a beneficial effect on improving coronary microvascular dysfunction (CMD). This study aims to evaluate the clinical effects and safety of nicorandil on CSX patients.

METHODS

The Cochrane Library, Pubmed, EMBASE, ClinicalTrials.gov and 4 Chinese databases were searched to identify relevant studies. The Cochrane "Risk of bias" tool was used to assess the methodological quality of eligible studies. Meta-analysis was performed by RevMan 5.3 software. The Eggers test and meta-regression were performed by software Stata 14.0. Quality of evidence was assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) approach.

RESULTS

Twenty four randomized controlled trials (RCTs) involving 2323 patients were included. Most of the included studies were classified as having an unclear risk of bias because of poor reported methodology. The main outcomes are angina symptoms improvement, resting electrocardiogram (ECG) improvement, treadmill test result, and endothelial function. Meta-analysis showed that nicorandil had some benefit on improving angina symptoms (RR 1.24, 95% CI 1.19 to 1.29, I = 20%, P < .00001), resting ECG (RR = 1.24, 95% IC: 1.15 to 1.33, I = 0%, P < .00001), and prolonged the time to 1 mm ST-segment depression in treadmill test result (WMD = 38.41, 95% IC: 18.46 to 58.36, I = 0%, P = .0002). Besides nicorandil could reduce the level of endothelin-1 (ET-1) (SMD = -2.22, 95% IC: -2.61 to -1.83, I = 77%, P < .00001) and increase the level of nitric oxide (NO) (WMD = 27.45, 95% IC: 125.65 to 29.24, I = 81%, P < .00001). No serious adverse drug event was reported. The Eggers test showed that significant statistical publication bias was detected (Eggers test P = .000). The quality of evidence ranged from very low to low.

CONCLUSIONS

Nicorandil shows the potential of improving angina symptoms, ECG, and endothelial dysfunction in patients with CSX. However, there is insufficient evidence for the clinical benefits of nicorandil due to the very low-quality evidence.

A Comparison of Three-Dimensional Speckle Tracking Echocardiography Parameters in Predicting Left Ventricular Remodeling

Three-dimensional speckle tracking echocardiography (3D STE) is an emerging noninvasive method for predicting left ventricular remodeling (LVR) after acute myocardial infarction (AMI). Previous studies analyzed the predictive value of 3D STE with traditional models. However, no models that contain comprehensive risk factors were assessed, and there are limited data on the comparison of different 3D STE parameters. In this study, we sought to build a machine learning model for predicting LVR in AMI patients after effective percutaneous coronary intervention (PCI) that contains the majority of the clinical risk factors and compare 3D STE parameters values for LVR prediction. We enrolled 135 first-onset AMI patients (120 males, mean age 54 ± 9 years). All patients went through a 3D STE and a traditional transthoracic echocardiography 24 hours after reperfusion. A second echocardiography was repeated at the three-month follow-up to detect LVR (defined as a 20 percent increase in left ventricular end-diastolic volume). Six models were constructed using 15 risk factors. A receiver operator characteristic curve and four performance measurements were used as evaluation methods. Feature importance was used to compare 3D STE parameters. 26 patients (19.3%) had LVR. Our evaluation showed that RF can best predict LVR with the best AUC of 0.96. 3D GLS was the most valuable 3D STE parameters, followed by GCS, global area strain, and global radial strain (feature importance 0.146, 0.089, 0.087, and 0.069, respectively). To sum up, RF models can accurately predict the LVR after AMI, and 3D GLS was the best 3D STE parameters in predicting the LVR.

A review of current trends in three-dimensional analysis of left ventricular myocardial strain

Three-dimensional (3D) left ventricular (LV) myocardial strain measurements using transthoracic 3D echocardiography speckle tracking analysis have several advantages over two-dimensional (2D) LV strain measurements, because 3D strain values are derived from the entire LV myocardium, yielding more accurate estimates of global and regional LV function. In this review article, we summarize the current status of 3D LV myocardial strain. Specifically, we describe how 3D LV strain analysis is performed. Next, we compare characteristics of 2D and 3D strain, and we explain validation of 3D strain measurements, feasibility and measurement differences between 2D and 3D strain, reference values of 3D strain, and its applications in several clinical scenarios. In some parts of this review, we used a meta-analysis to draw reliable conclusions. We also describe the added value of 3D over 2D strain in several specific pathologies and prognoses. Finally, we discuss novel techniques using 3D strain and suggest its future directions.

Left ventricle automatic segmentation in cardiac MRI using a combined CNN and U-net approach

Cardiovascular diseases can be effectively prevented from worsening through early diagnosis. To this end, various methods have been proposed to detect the disease source by analyzing cardiac magnetic resonance images (MRI), wherein left ventricular segmentation plays an indispensable role. However, since the left ventricle (LV) is easily confused with other regions in cardiac MRI, segmentation of the LV is a challenging problem. To address this issue, we propose a composite model combining CNN and U-net to accurately segment the LV. In our model, CNN is used to locate the region of interest (ROI) and the U-net network achieve segmentation of LV. We used the cardiac MRI datasets of the MICCAI 2009 left ventricular segmentation challenge to train and test our model and demonstrated the accuracy and robustness of the proposed model. The proposed model achieved state-of-the-art results. The metrics are Dice metric (DM), volumetric overlap error (VOE) and Hausdorff distance (HD), in which DM reaches 0.951, VOE reaches 0.053 and HD reaches 3.641.

Pyramid feature adaptation for semi-supervised cardiac bi-ventricle segmentation

Cardiac bi-ventricle segmentation (BVS) is an essential task for assessing cardiac indices, such as the ejection fraction and volume of the left ventricle (LV) and right ventricle (RV). However, BVS is extremely challenging due to the high variability of the bi-ventricle structure and lack of labeled data. In this paper, we propose a pyramid feature adaptation based semi-supervised method (PABVS) for cardiac bi-ventricle segmentation. The PABVS first extracts the multiscale pyramid features of bi-ventricle structure to cope with the high variability of bi-ventricle structure. Then, a weighted pyramid feature adaptation strategy is proposed to ensure a smooth feature space among labeled data and unlabeled data. In particular, the PABVS performs weighted feature adaptation at each level of a multiscale pyramid feature based on adversarial learning. It gives less importance to outlier feature layers of labeled data and more importance to representative layers. The experimental results on magnetic resonance images show that our proposed PABVS can achieve Dice values 0.915 for EpiLV with 40% labeled data and the Dice values 0.976 for EpiLV with all labeled data, which outperforms mainstream semi-supervised methods. This endows our PABVS with great potential for the effective clinical application of BVS.

A Network-Based Bioinformatics Approach to Identify Molecular Biomarkers for Type 2 Diabetes that Are Linked to the Progression of Neurological Diseases

Neurological diseases (NDs) are progressive disorders, the progression of which can be significantly affected by a range of common diseases that present as comorbidities. Clinical studies, including epidemiological and neuropathological analyses, indicate that patients with type 2 diabetes (T2D) have worse progression of NDs, suggesting pathogenic links between NDs and T2D. However, finding causal or predisposing factors that link T2D and NDs remains challenging. To address these problems, we developed a high-throughput network-based quantitative pipeline using agnostic approaches to identify genes expressed abnormally in both T2D and NDs, to identify some of the shared molecular pathways that may underpin T2D and ND interaction. We employed gene expression transcriptomic datasets from control and disease-affected individuals and identified differentially expressed genes (DEGs) in tissues of patients with T2D and ND when compared to unaffected control individuals. One hundred and ninety seven DEGs (99 up-regulated and 98 down-regulated in affected individuals) that were common to both the T2D and the ND datasets were identified. Functional annotation of these identified DEGs revealed the involvement of significant cell signaling associated molecular pathways. The overlapping DEGs (i.e., seen in both T2D and ND datasets) were then used to extract the most significant GO terms. We performed validation of these results with gold benchmark databases and literature searching, which identified which genes and pathways had been previously linked to NDs or T2D and which are novel. Hub proteins in the pathways were identified (including DNM2, DNM1, MYH14, PACSIN2, TFRC, PDE4D, ENTPD1, PLK4, CDC20B, and CDC14A) using protein-protein interaction analysis which have not previously been described as playing a role in these diseases. To reveal the transcriptional and post-transcriptional regulators of the DEGs we used transcription factor (TF) interactions analysis and DEG-microRNAs (miRNAs) interaction analysis, respectively. We thus identified the following TFs as important in driving expression of our T2D/ND common genes: FOXC1, GATA2, FOXL1, YY1, E2F1, NFIC, NFYA, USF2, HINFP, MEF2A, SRF, NFKB1, USF2, HINFP, MEF2A, SRF, NFKB1, PDE4D, CREB1, SP1, HOXA5, SREBF1, TFAP2A, STAT3, POU2F2, TP53, PPARG, and JUN. MicroRNAs that affect expression of these genes include mir-335-5p, mir-16-5p, mir-93-5p, mir-17-5p, mir-124-3p. Thus, our transcriptomic data analysis identifies novel potential links between NDs and T2D pathologies that may underlie comorbidity interactions, links that may include potential targets for therapeutic intervention. In sum, our neighborhood-based benchmarking and multilayer network topology methods identified novel putative biomarkers that indicate how type 2 diabetes (T2D) and these neurological diseases interact and pathways that, in the future, may be targeted for treatment.

Assess the Performance and Cost-Effectiveness of LACE and HOSPITAL Re-Admission Prediction Models as a Risk Management Tool for Home Care Patients: An Evaluation Study of a Medical Center Affiliated Home Care Unit in Taiwan

The LACE index and HOSPITAL score models are the two most commonly used prediction models identifying patients at high risk of readmission with limited information for home care patients. This study compares the effectiveness of these two models in predicting 30-day readmission following acute hospitalization of such patients in Taiwan. A cohort of 57 home care patients were enrolled and followed-up for one year. We compared calibration, discrimination (area under the receiver operating curve, AUC), and net reclassification improvement (NRI) to identify patients at risk of 30-day readmission for both models. Moreover, the cost-effectiveness of the models was evaluated using microsimulation analysis. A total of 22 readmissions occurred after 87 acute hospitalizations during the study period (readmission rate = 25.2%). While the LACE score had poor discrimination (AUC = 0.598, 95% confidence interval (CI) = 0.488–0.702), the HOSPITAL score achieved helpful discrimination (AUC = 0.691, 95% CI = 0.582–0.785). Moreover, the HOSPITAL score had improved the risk prediction in 38.3% of the patients, compared with the LACE index (NRI = 0.383, 95% CI = 0.068–0.697, p = 0.017). Both prediction models effectively reduced readmission rates compared to an attending physician’s model (readmission rate reduction: LACE, 39.2%; HOSPITAL, 43.4%; physician, 10.1%; p < 0.001). The HOSPITAL score provides a better prediction of readmission and has potential as a risk management tool for home care patients.

Multi-branch fusion network for Myocardial infarction screening from 12-lead ECG images

BACKGROUND AND OBJECTIVE

Myocardial infarction (MI) is a myocardial anoxic incapacitation caused by severe cardiovascular obstruction that can cause irreversible injury or even death. In medical field, the electrocardiogram (ECG) is a common and effective way to diagnose myocardial infarction, which often requires a wealth of medical knowledge. It is necessary to develop an approach that can detect the MI automatically.

METHODS

In this paper, we propose a multi-branch fusion framework for automatic MI screening from 12-lead ECG images, which consists of multi-branch network, feature fusion and classification network. First, we use text detection and position alignment to automatically separate twelve leads from ECG images. Then, those 12 leads are input into the multi-branch network constructed by a shallow neural network to get 12 feature maps. After concatenating those feature maps by depth fusion, classification is explored to judge the given ECG is MI or not.

RESULTS

Based on extensive experiments on an ECG image dataset, performances of different combinations of structures are analyzed. The proposed network is compared with other networks and also compared with physicians in the practical use. All the experiments verify that the proposed method is effective for MI screening based on ECG images, which achieves accuracy, sensitivity, specificity and F1-score of 94.73%, 96.41%, 95.94% and 93.79% respectively.

CONCLUSIONS

Rather than using the typical one-dimensional electrical ECG signal, this paper gives an effective model to screen MI by analyzing 12-lead ECG images. Extracting and analyzing these 12 leads from their corresponding ECG images is a good attempt in the application of MI screening.

Gated recurrent unit-based heart sound analysis for heart failure screening

BACKGROUND

Heart failure (HF) is a type of cardiovascular disease caused by abnormal cardiac structure and function. Early screening of HF has important implication for treatment in a timely manner. Heart sound (HS) conveys relevant information related to HF; this study is therefore based on the analysis of HS signals. The objective is to develop an efficient tool to identify subjects of normal, HF with preserved ejection fraction and HF with reduced ejection fraction automatically.

METHODS

We proposed a novel HF screening framework based on gated recurrent unit (GRU) model in this study. The logistic regression-based hidden semi-Markov model was adopted to segment HS frames. Normalized frames were taken as the input of the proposed model which can automatically learn the deep features and complete the HF screening without de-nosing and hand-crafted feature extraction.

RESULTS

To evaluate the performance of proposed model, three methods are used for comparison. The results show that the GRU model gives a satisfactory performance with average accuracy of 98.82%, which is better than other comparison models.

CONCLUSION

The proposed GRU model can learn features from HS directly, which means it can be independent of expert knowledge. In addition, the good performance demonstrates the effectiveness of HS analysis for HF early screening.

Super-resolution of cardiac magnetic resonance images using Laplacian Pyramid based on Generative Adversarial Networks

BACKGROUND AND OBJECTIVE

Cardiac magnetic resonance imaging (MRI) can assist in both functional and structural analysis of the heart, but due to hardware and physical limitations, high-resolution MRI scans is time consuming and peak signal-to-noise ratio (PSNR) is low. The existing super-resolution methods attempt to resolve this issue, but there are still shortcomings, such as hallucinate details after super-resolution, low precision after reconstruction, etc. To dispose these problems, we propose the Laplacian Pyramid Generation Adversarial Network (LSRGAN) in order to generate visually better cardiovascular ultrasound images so as to aid physician diagnosis and treatment.

METHODS AND RESULTS

In order to address the problem of low image resolution, we used the Laplacian Pyramid to analyze the high-frequency detail features of super-resolution (SR) reconstruction of images with different pixel sizes. To eliminate gradient disappearance, we implemented the least squares loss function as the discriminator, we introduce the residual-dense block (RDB) as the basic network building unit is used to generate higher quality images. The experimental results show that the LSRGAN can effectively avoid the illusion details after super-resolution and has the best reconstruction quality. Compared with the state-of-the-art methods, our proposed algorithm generates higher quality super-resolution images that comes with higher peak signal-to-noise ratio and structural similarity (SSIM) scores.

CONCLUSION

We implemented a novel LSRGAN network model, which solves reduces insufficient resolution and hallucinate details of MRI after super-resolution. Our research presents a superior super-resolution method for medical experts to diagnose and treat myocardial ischemia and myocardial infarction.

Prevalence and associated factors of influenza vaccination coverage in Korean adults with cardiovascular disease

Infection with influenza virus increases morbidity and mortality in patients with risk factors, including cardiovascular disease (CVD). This study aimed to evaluate factors associated with influenza vaccination coverage in Korean CVD patients.We included 19,599 adults from the 2010 to 2012 Korea National Health and Nutrition Examination Survey. Influenza vaccination rates were compared in subjects with and without CVD. Logistic regression analysis was performed to identify factors associated with influenza vaccination in Korean adults with CVD before and after stratification for age (<65 and ≥65 years).Significantly higher vaccination rates were observed in individuals with CVD than in those without CVD (61.4% vs 31.0%, P < .001). However, young individuals (19-49 years) had decreased influenza vaccination rates, with no difference based on CVD status (20.3% vs 21.6%, P = .859). A lack of private insurance (odds ratio [OR], 0.47; 95% confidence interval [CI], 0.23-0.98) and recent health screening (OR, 4.56; 95% CI, 1.90-10.92) were independent factors for influenza vaccination in CVD patients aged <65 years, whereas female sex (OR, 3.71; 95% CI, 1.24-11.07) and less education (OR, 4.59; 95% CI, 1.27-16.61) were independent factors in CVD patients aged ≥65 years.Improving influenza vaccination coverage for Korean adults with CVD is important, especially in young patients. For young patients with CVD, influenza vaccination status is independently associated with the presence of private insurance and recent health screening. This finding could help establish public health policies to promote influenza vaccination in this population.

Learning tree-structured representation for 3D coronary artery segmentation

Extensive research has been devoted to the segmentation of the coronary artery. However, owing to its complex anatomical structure, it is extremely challenging to automatically segment the coronary artery from 3D coronary computed tomography angiography (CCTA). Inspired by recent ideas to use tree-structured long short-term memory (LSTM) to model the underlying tree structures for NLP tasks, we propose a novel tree-structured convolutional gated recurrent unit (ConvGRU) model to learn the anatomical structure of the coronary artery. However, unlike tree-structured LSTM proposed for semantic relatedness as well as sentiment classification in natural language processing, our tree-structured ConvGRU model considers the local spatial correlations in the input data as the convolutions are used for input-to-state as well as state-to-state transitions, thus more suitable for image analysis. To conduct voxel-wise segmentation, a tree-structured segmentation framework is presented. It consists of a fully convolutional network (FCN) for multi-scale discriminative feature extraction and the final prediction, and a tree-structured ConvGRU layer for anatomical structure modeling. The proposed framework is extensively evaluated on four large-scale 3D CCTA dataset (the largest to the best of our knowledge), and experiments show that our method is more accurate as well as efficient, compared with other coronary artery segmentation approaches.

3-Dimensional Echocardiography: Latest Developments and Future Directions

The ongoing refinements in 3-dimensional (3D) echocardiography technology continue to expand the scope of this imaging modality in clinical cardiology by offering new features that stem from the ability to image the heart in its complete dimensionality. Over the years, countless publications have described these benefits and tested new frontiers where 3D echocardiographic imaging seemed to offer promising ways to improve patients' care. These include improved techniques for chamber quantification and novel ways to visualize cardiac valves, including 3D printing, virtual reality, and holography. The aims of this review article are to focus on the most important developments in the field in the recent years, discuss the current utility of 3D echocardiography, and highlight several interesting future directions.

A noninvasive and highly sensitive approach for the assessment of coronary collateral circulation by 192-slice third-generation dual-source computed tomography

The coronary collateral circulation (CCC) is an alternative source of blood supply when the original vessels fail to provide sufficient blood. The accurate detection of CCC is critical for the treatment of ischemic heart disease, especially when the stent surgery is not an option. The assessment of minute vessels such as coronary collateral arteries is challenging. The objective of this study was to assess the feasibility of detection and classification of CCC using the192-slice third-generation dual-source computed tomography angiography (192-slice DSCT CTA).Eight hundred patients (450 men and 350 women, mean age: 56 ± 11 years) with complete or subtotal occlusion of at least 1 major coronary artery were enrolled for our study. February 2016 and September 2018, the patient both 192-slice DSCT CTA and conventional coronary angiography (CAG) were performed in all enrolled patients. The interval between two approaches for a given patient was 6.1 ± 3.7 days (Range: 1-15). The diagnostic accuracy of 192-slice DSCT CTA was evaluated by comparing it with that of CAG. The identified CCC was graded according to the Rentrop classification.The prevalence among patients of having at least 1 CCC was 43.8%. The sensitivity for detecting CCC by 192-slice DSCT was 91.7% (95% CI: 88.3% to 94.3%), specificity was 95.5% (95% CI: 93.1% to 97.2%), positive predictive value was 94.3% (95% CI: 91.5% to 96.2%), and negative predictive value was 93.3% (95% CI: 90.9% to 95.3%). Cohen-Kappa analysis showed that the consistency of the correct classification of CCC using CAG and 192-slice DSCT was very high with the kappa coefficient (κ) of 0.94 (95% CI: 0.91-0.96, P value = .01). Additionally, the radiation dose for 192-slice DSCT was as low as 0.42 ± 0.04 mSv (range, 0.35-0.43 mSv).The 192-slice DSCT CTA is a reliable and sensitive non-invasive method for the evaluation of CCC with low radiation doses.

Visualization of Myocardial Strain Pattern Uniqueness with Respect to Activation Time and Contractility: A Computational Study

Speckle tracking echography is used to measure myocardial strain patterns in order to assess the state of myocardial tissue. Because electro-mechanical coupling in myocardial tissue is complex and nonlinear, and because of the measurement errors the uniqueness of strain patterns is questionable. In this study, the uniqueness of strain patterns was visualized in order to revel characteristics that may improve their interpretation. A computational model of sarcomere mechanics was used to generate a database of 1681 strain patterns, each simulated with a different set of sarcomere parameters: time of activation (TA) and contractility (Con). TA and Con ranged from −100 ms to 100 ms and 2% to 202% in 41 steps respectively, thus forming a two-dimensional 41 × 41 parameter space. Uniqueness of the strain pattern was assessed by using a cohort of similar strain patterns defined by a measurement error. The cohort members were then visualized in the parameter space. Each cohort formed one connected component (or blob) in the parameter space; however, large differences in the shape, size, and eccentricity of the blobs were found for different regions in the parameter space. The blobs were elongated along the TA direction (±50 ms) when contractility was low, and along the Con direction (±50%) when contractility was high. The uniqueness of the strain patterns can be assessed and visualized in the parameter space. The strain patterns in the studied database are not degenerated because a cohort of similar strain patterns forms only one connected blob in the parameter space. However, the elongation of the blobs means that estimations of TA when contractility is low and of Con when contractility is high have high uncertainty.

Low expression of PIK3C2A gene: A potential biomarker to predict the risk of acute myocardial infarction

AIMS

Phosphoinositide 3-kinases (PI3Ks) are a family of enzymes that phosphorylate the 3'-OH of inositol ring of phosphatidylinositol (PI) and regulate a broad range of signaling pathways. PIK3C2A is structurally distinct from the other members of this class and is expressed in endothelial cells, vascular endothelium, and smooth muscle. In ischemic cardiovascular diseases, such as coronary artery disease, pathology is associated with endothelial damage and inflammation, downregulation of the EPC cell population and function, and impaired angiogenesis. This study aims to make an assessment on whether expression of PIK3C2A gene can be used as a biomarker for predicting the risk of acute myocardial infarction (AMI).

METHODS

We collected peripheral blood from 84 subjects with non-coronary heart disease and 70 patients with AMI. The real-time quantitative PCR test was applied to measure levels of PIK3C2A gene expression at mRNA level in peripheral blood.

RESULTS

Our results indicated that the level of PIK3C2A gene expression in peripheral blood of AMI patients was significantly lower than one in the non-coronary heart disease subjects. Binary logistic regression analysis showed that low expression of PIK3C2A gene was an independent risk factor of AMI and increased the risk of AMI by 2.231 folds. Moreover, it was found that low expression of PIK3C2A gene was not associated with level of fasting blood glucose, platelet count, Gensini score of coronary artery, and quantity of cardiac troponin.

CONCLUSION

The level of PIK3C2A gene expression in patients with AMI is significantly lower than that of healthy people. Low expression of PIK3C2A gene is an independent risk factor of AMI. Low expression of PIK3C2A could serve as a potential biomarker to predict risk of AMI.

Crush versus Culotte stenting techniques for coronary bifurcation lesions: A systematic review and meta-analysis of clinical trials with long-term follow-up

BACKGROUND

In patients with complex true coronary bifurcation lesions (CBLs), Crush or Culotte stenting has been the commonest approaches of percutaneous coronary intervention (PCI). However, the optimal one remains in debate.

METHODS

A systematic review and meta-analysis of cohort studies searched from PubMed, EMBASE, Cochrane Central Register of Controlled Trials (CENTRAL), Chinese National Knowledge Infrastructure (CNKI), VIP information database, and WangFang Data Information Site, to compare the long-term safety and efficacy of PCI with Crush versus Culotte in patients with CBLs. The primary end point was target lesion revascularization (TLR) and secondary end points were a composite of major adverse cardiac events (MACE) including cardiac death (CD), myocardial infarction (MI), stent thrombosis (ST), and target vessel revascularization (TVR) by PCI or bypass surgery, and each individual component at long-term follow-up. Furthermore, omitting each study in turn was used to sensitivity analysis for high heterogeneity of studies.

RESULTS

A total of 7 studies were included to perform a meta-analysis, 3 randomized trials and 4 observational studies with 2211 patients, 1281 treated with Crush and 930 with Culotte. There was no significant difference in TLR and MACE between Crush and Culotte [RR 0.76, 95% CI (0.48-1.23), I = 57%; RR 0.78, 95% CI (0.47-1.29), I = 83%, respectively]. ST tended to be lower in patients treated with Crush [RR 0.61, 95% CI (0.37-1.01), I = 23%]. CD and MI were comparable between the 2 groups [RR 0.80, 95% CI (0.43-1.49), I = 0%; RR 0.74, 95% CI (0.49-1.13), I = 32%, respectively]. TVR was also associated with the similar risk [RR 0.76, 95% CI (0.49-1.16), I = 60%]. However, high heterogeneity was detected for TLR, MACE, and TVR, and the source of heterogeneity was DKCRUSH-III study by Chen, SL.

CONCLUSIONS

In the treatment of coronary bifurcation lesions, TLR and MACE were not significant difference between the Crush and Culotte groups, but TLR and MACE were also regarded as high heterogeneity mainly due to better outcomes achieved by DK Crush and there was a trend toward lower ST in the Crush group. Crush, particularly DK Crush, may be superior to conventional Culotte for treatment of CBLs.

PROSPERO REGISTRATION NUMBER

CRD42018111868.

Prevalence of extracranial carotid atherosclerosis in the patients with coronary artery disease in a tertiary hospital in Malaysia

There is limited information regarding the prevalence of extracranial carotid atherosclerosis in the patients with coronary artery disease (CAD) undergoing coronary artery bypass graft (CABG) surgery in South East Asia. The primary objective was to assess the prevalence of extracranial carotid stenosis, raised carotid intima media thickness (CIMT), and plaques in the patients with CAD undergoing elective CABG. The secondary objective was to evaluate the risk factors for extracranial carotid atherosclerosis.A total of 119 consecutive patients with CAD undergoing elective CABG in a tertiary hospital in Malaysia were recruited. Data on the demographic characteristics and risk factors were collected. The ultrasound carotid Doppler findings comprising of raised CIMT, plaques, and stenosis in the extracranial carotid vessels were recorded.The mean age of the patients was 64.26 ± 10.12 (range 42-89). Most of the patients were men (73.1%). The patients consisted of 44 (37%) Malays, 26 (21.8%) Chinese, and 49 (41.2%) Indians.A total of 67 (56.3%) patients had raised CIMT, 89 (74.8%) patients had plaques, and 10 (8.4%) patients had stenosis in the internal and common carotid arteries. The mean age of patients with plaques was higher compared to those without plaques (66.00 ± 9.63 vs 59.10 ± 9.92, P = .001). The body mass index (BMI) of patients with stenosis was higher compared to those without stenosis (28.35 ± 4.92 vs 25.75 ± 3.16, P = .02).The patients with plaques were more likely to be older, whereas the patients with carotid stenosis were more likely to have higher BMI.

The relationship between compression garments and electrocardiogram signals during exercise and recovery phase

BACKGROUND

The direction of the current research was to investigate whether electrocardiogram (ECG) signals have been impacted by using compression garments during exercise and recovery phase. Each subject is non-athletes, conducted two running tests, wearing either non-compression garments (NCGs) or compression garments (CGs) throughout experiments and 2-h of the recovery phase. Experiment 1 (number of participants (n) = 8; 61.4 ± 13.7 kg, 25.1 ± 3.8 years, 165.9 ± 8.3 cm) focused on the exercising phase while Experiment 2 (n = 14; 60.9 ± 12.0 kg, 24.7 ± 4.5 years, 166.0 ± 7.6 cm) concentrated on the recovery phase. Electrocardiogram (ECG) data were collected through wearable biosensors.

RESULTS

The results demonstrated a significant difference between compression garments and non-compression garments at the end of the tests and from 90 min onwards during the recovery phase (p < 0.05). Corrected QT (QTc), ST interval and heart rate (HR) indicated the significant difference between NCGs and CGs.

CONCLUSION

Based on the findings, the utilization of compression garments showed a positive influence in non-athletes based on the quicker recovery in HR, ST, and QTc.

The use of nonthoracoscopic Nuss procedure for the correction of pectus excavatum by trans-esophageal echocardiography monitoring

This study was aimed to review the current experience regarding the correction of pectus excavatum by Nuss procedure with nonthoracoscopic assistance using trans-esophageal echocardiography monitoring.A total of 172 patients with pectus excavatum were surgically treated from August 2011 to August 2016. The sample size comprised 131 boys and 41 girls and the average age was 13 years and 2 months. A total of 144 cases were initially operated on, whereas 13 subjects exhibited postoperative recurrence following Ravitch repair of a pectus excavatum deformity and 15 cases experienced a history of median sternotomy. The intraoperative Haller index ranged from 3.6 to 14.2 (mean 4.1). The intraoperative TEE monitoring was conducted with middle-esophageal 4-champer view and middle-esophageal Aortic short axis view to detect the injury of heart and of the large vessels by the introducer and Nuss steel bars.The operation conducted in all patients was successful in the absence of severe complications. The time of operation ranged from 38 to 80 minutes (mean 50 minutes). The bleeding volume during the procedure was between 10 and 40 mL (mean 15 mL). The time from operation to discharge was from 5 to 7 days (mean 6 days). Pneumothorax occurred in 25 cases following the termination of the operation, including 9 cases of needle puncture aspiration and 6 cases of closed drainage. Pleural effusion occurred in 4 cases. No patients suffered from wood infection. Effusion occurred in 9 cases following 6 to 23 months, whereas dressing changes and surgical debridement were evident in 2 and 7 cases, respectively. The bars were removed in 82 of the 172 patients within 3 years. The progression of the thoracic wall was assessed for the period of 8 to 68 months following the surgery, during the follow-up period. The average time period of follow-up was 32 months.Nuss procedure with nonthoracoscopic assistance with trans-esophageal echocardiography monitoring for the correction of pectus excavatum was safe for all of the cases investigated. It exhibited lesser trauma and required a shorter time period.

Comparison of clinical outcomes between intravascular optical coherence tomography-guided and angiography-guided stent implantation: A meta-analysis of randomized control trials and systematic review

OBJECTIVE

This systematic review was designed to evaluate the overall efficacy of optical coherence tomography (OCT)-guided implantation versus angiography-guided for percutaneous coronary intervention.

METHODS

The following electronic databases, such as CENTRAL, PubMed, Cochrane, and EMBASE were searched for systematic reviews to investigate OCT-guided and angiography-guided implantation. We measured the following 7 parameters in each patient: stent thrombosis, cardiovascular death, myocardial infarction, major adverse cardiac events (MACE), target lesion revascularization (TLR), target vessel revascularization (TVR), all-cause death.

RESULTS

In all, 11 studies (6 RCTs and 5 observational studies) involving 4026 subjects were included, with 1903 receiving intravascular ultrasound-guided drug-eluting stent (DES) implantation and 2123 using angiography-guided DES implantation. With regard to MACE, MT, TLR, TVR, stent thrombosis and all-cause death, the group of OCT-guided implantation had no significant statistical association with remarkably improved clinical outcomes. However, its effect on cardiovascular death has a significant statistical difference in angiography-guided implantation group.

CONCLUSION

In the present pool analysis, OCT-guided DES implantation showed a tendency toward improved clinical outcomes compared to angiography-guided implantation. More eligible randomized clinical trials are warranted to verify the findings and to determine the beneficial effect of OCT-guidance for patients.

Spontaneous regression of cervical discs: Retrospective analysis of 14 cases

Cervical disc herniation is a condition which arises from compression of cervical spinal nerve root by the degenerated disc and vast majority of the patients are aged between 30 and 40 years. Spontaneous regression of cervical disc was first reported by Kriegerand Maniker in 1992. Our study is the second large series in literature. Besides, 4 patients are the first who were shown to have resorption in C 4-5.The records of patients diagnosed with cervical disc herniation who applied to the Spine Polyclinic between 2014 and 2018 were reviewed retrospectively. The files of the patients who were recommended surgery with the diagnosis of cervical disc herniation were examined. Patients who did not accept surgery on their own initiative, but who attended our outpatient clinic for a check-up were included in the study.Of a total of 14 patients, 28.57% (n = 4) were male and 71.43% (n = 10) were female. Mean age of the patients was 40.79 (range 25-60).The results of the study indicate that likelihood of spontaneous regression is higher in para-central or foraminal disc compared to central disc hernias. Although there are a limited number of case reports in the literature, conservative treatment seems to be a good option in patients without neurological deficits, with foraminal disc hernias and not requiring emergency surgery.

Evaluation of myocardial viability in patients with acute myocardial infarction: Layer-specific analysis of 2-dimensional speckle tracking echocardiography

BACKGROUND

The value of layer-specific two-dimensional speckle tracking echocardiography (LS2D-STE) for evaluating viable myocardium (VM) in patients with acute myocardial infarction (AMI) was unclear, this study provides new insights into it and to make a comparison with dualisotope simultaneous acquisition single photon emission computed tomography ( DISA-SPECT).

METHODS

Forty hospitalized patients with AMI and left ventricular systolic dysfunction (left ventricular ejection fraction <50%) underwent LS2D-STE and DISA-SPECT before percutaneous coronary intervention (PCI). The longitudinal, circumferential, and radial peak systolic strains and the peak systolic strain rates of 3 myocardiallayers (endocardium, mid-myocardium, and epicardium), as well as the total wall thickness, were determined by LS2D-STE. Routine echocardiography was followedup at 1, 3, 6 months after PCI, with the improvement of the wall motion as the goldenstandard for evaluating VM.

RESULTS

The sensitivity, specificity and accuracy of DISA-SPECT for evaluating VM were 82.1%, 74.3%, and 79.3%, respectively. Among the layer-specific parameters, only endocardial (endo-) longitudinal strain (LS) and endo- longitudinal strain rate (LSr) were used as independent parameters for evaluating VM (P < .05), and the sensitivity, specificity and accuracy of endo-LS and endo-LSr in evaluation of VM were 77.1%, 65.4%, and 72.9% vs 72.9%, 65.4%, and 69.7%. Endo-LS and endo-LSr were superior to total wall thickness LS and LSr (AUC endo-LS 0.767 vs total-LS 0.669; endo-LSr 0.743 vs total-LSr 0.682). The parallel test and the serial test of combination of endo-LS and endo-LSr showed similar sensitivity, specificity and accuracy to DISA-SPECT (P > .05).

CONCLUSION

The endo-LS and endo-LSr analysis of LS2D-STE can evaluate the VM well, and its sensitivity, specificity and accuracy in detection of VM are similar to those of DISA-SPECT, resulting in LS2D-STE being a good option for the assessment of VM.

Blood homocysteine levels could predict major adverse cardiac events in patients with acute coronary syndrome: A STROBE-compliant observational study

The Global Registry of Acute Coronary Events (GRACE) risk score independently predicts major adverse cardiac events (MACEs) in patients with acute coronary syndrome (ACS). This study aims to evaluate whether the level of plasma homocysteine in addition to the GRACE score enhances the predictive value for MACEs in patients with acute coronary syndrome.A total of 361 patients with ACS evaluated at our hospital were included in the study and tested for blood homocysteine levels. We recorded 40 (11.1%) instances of MACE during a median follow-up of 43.3 months (quartile 40.6-44.4 months), including 29 cases (8.0%) of all-cause death and 11 cases (3.1%) of nonfatal myocardial infarction.The GRACE score was significantly associated with homocysteine levels, and multivariate Cox regression analysis showed that both the GRACE risk score and homocysteine content were independent predictors of MACEs (HR 2.63; 95% confidence interval (CI) 1.54 to 4.49; P < .001 and 2.27; 1.06 to 4.86; P = .035, respectively). Moreover, meta-analysis showed that as the homocysteine level increased, the incidence of MACEs also increased (log-rank 8.41; P = .015). GRACE scores adjusted by homocysteine level increased the area under the curve (AUC) from 0.78 to 0.83 (P = 0.006).Blood homocysteine levels are significantly associated with the GRACE risk score, and using both parameters can further improve risk stratification in patients with acute coronary syndrome.

Autoimmune activation as a determinant of atrial fibrillation among Turks: A prospective evaluation

Although low-grade inflammation has been linked to the prediction of atrial fibrillation (AF), evidence from some reports suggest that autoimmune activation might potentially be a relevant mechanism. We assessed the predictive value of inflammation and other markers for the risk of incident AF.A score of age-controlled anthropometric, lipid, and nonlipid variables was compared in participants with recorded nonvalvular persistent/permanent AF (n = 110) to those of a nested cohort sample (n = 1126) of the Turkish Adult Risk Factor study. Available values preceding by 2 (±1) years the development of AF were used regarding incident AF (n = 87) in multivariable regression.Comparing age-controlled inflammation and other markers across the 2 groups, low apolipoprotein (apo) B and total cholesterol levels differed highly significantly in each sex. Moreover, low-density lipoprotein (LDL)-cholesterol and fasting insulin concentrations were significantly lower, sex hormone binding globulin (SHBG), glucose and systolic blood pressure higher in women alone, while C-reactive protein levels were similar. A model of multivariable logistic regression analyses for overall AF and 2 models for incident AF demonstrated a consistent inverse predictive value for apoB in each gender [relative risk (RR) 0.44 (95% confidence interval (CI), 95% CI 0.30-0.66], along with age, as main determinants. SHBG in females and waist circumference in males were further significantly associated with initial AF. Never smoking (compared with ever smoking) tended to predict AF.These findings, collectively, are highly consistent with an autoimmune process in which damaged epitope of apoB due to proinflammatory state emerge as a basic mechanism in the development of AF. ApoB level is likely only apparently reduced due to partial escape from assay.

The effect of myocardial action potential duration on cardiac pumping efficacy: a computational study

BACKGROUND AND AIMS

Although studies on the relation between arrhythmias and the action potential duration (APD) have been carried out, most of them are based only on electrophysiological factors of the heart and lack experiments that consider cardiac mechanical and electromechanical characteristics. Therefore, we conducted this study to clarify the relevance of the shortening of APD of a cell in relation to the mechanical contraction activity of the heart and the associated risk of arrhythmia.

METHODS

The human ventricular model used in this study has two dynamic characteristics: electrophysiological conduction and mechanical contraction. The model simulating electrophysiological characteristics was consisted of lumped parameter circuit that can mimic the phenomenon of ion exchange through the cell membrane of myocyte and consisted of 214,319 tetrahedral finite elements. In contrast, the model simulating mechanical contraction characteristics was constructed to mimic cardiac contraction by means of the crossbridge of a myofilament and consisted of 14,720 hermite-based finite elements to represent a natural 3D curve of the cardiac surface. First, we performed a single cell simulation and the electrophysiological simulation according to the change of the APD by changing the electrical conductivity of the I Ks channel. Thus, we confirmed the correlation between APD and intracellular Ca2+ concentration. Then, we compared mechanical response through mechanical simulation using Ca2+ data from electrical simulation.

RESULTS

The APD and the sum of the intracellular Ca2+ concentrations showed a positive correlation. The shortened APD reduced the conduction wavelength of ventricular cells by shortening the plateau and early repolarization in myocardial cells. The decrease in APD reduced ventricular pumping efficiency by more than 60% as compared with the normal group (normal conditions). This change is caused by the decline of ventricular output owing to reduced ATP consumption during the crossbridge of myofilaments and decreased tension.

CONCLUSION

The shortening of APD owing to increased electrical conductivity of a protein channel on myocardial cells likely decreases the wavelength and the pumping efficiency of the ventricles. Additionally, it may increase tissue sensitivity to ventricular fibrillation, including reentry, and cause symptoms such as dyspnea and dizziness.

Investigation of elastic features of aorta and color M-mode flow propagation velocity (APV) of descending aorta in the patients with ischemic and non-ischemic dilated cardiomyopathy

Aortic flow propagation velocity (APV) is a novel echocardiographic parameter used in coronary artery disease. It has also been used for the evaluation of aortic stiffness. In the present study, APV was measured in patients with ischemic and non-ischemic dilated cardiomyopathy (DCM) and was compared with the parameters of aortic stiffness such as aortic distensibility (AD) and aortic strain (AS). A total of 140 patients who had undergone coronary angiographic imaging were included in the study. Out of these patients, 44 had ischemic DCM, 46 had non-ischemic DCM, and 50 had normal coronary angiography (control group). AS, AD, and APV were calculated echocardiographically. One-way analysis of variance (ANOVA) and the Kruskal-Wallis test were used to compare continuous variables between the groups, while the categorical variables were compared using Pearson's Chi square test. Pearson's correlation test was used to investigate the parameters associated with APV, AS, and AD. Ischemic DCM and non-ischemic DCM groups differed significantly. The comparison of these groups with the control group, in terms of AS, AD, and APV values (ANOVA p < 0.001 for all) also showed a significant difference. APV was found to be significantly correlated with AS (r = 0.645, p < 0.001) and AD (r = 0.604, p < 0.001). In ROC analysis, the area under the curve (AUC) value for APV was 0.999 (p = 0.000) for detection of patients ischemic DCM and non-ischemic DCM. APV may be considered to be a novel and a simple echocardiographic marker, for both, distinguishing ischemic from non-ischemic DCM as well as for the presence of dilated cardiomyopathy with or without critical coronary artery disease.

Value of three dimensional-speckle tracking imaging for predicting left ventricular function after non-ST-segment elevation myocardial infarction with percutaneous coronary intervention

BACKGROUND

Percutaneous coronary intervention (PCI) is the recommended treatment for high risk patients with non-ST-segment elevation myocardial infarction (NSTEMI).

OBJECTIVE

To investigate the application of three dimensional-speckle tracking imaging (3D-STI) on patients diagnosed with NSTEMI undergoing PCI.

METHODS

Forty-four NSTEMI patients and 20 healthy subjects that received basic clinical and laboratory examinations were included in our study. NSTEMI patients were divided into three groups: heart failure (HF) with normal ejection fraction (HF-NEF group, n = 19), heart failure with preserved ejection fraction (HF-PEF group, n = 14) and heart failure with a reduced ejection fraction (HF-REF group, n = 11). The global longitudinal peak systolic strain (GLS), global circumferential peak systolic strain (GCS), global radial peak systolic strain (GRS) and left ventricular (LV) torsion of all subjects were measured by 3D-STI before PCI and 1 month, 3 months after PCI. The high-sensitivity troponin T (hs-TNT), high-sensitivity C-reactive protein (hs-CRP) and N-terminal pro-brain natriuretic peptide (NT-pro BNP) were measured in each group. Correlations between these parameters and LV ejection fraction (LVEF) were tested by Pearson correlation analysis.

RESULTS

GLS, GCS and torsion were significantly decreased in the 3 NSTEMI groups compared with control group (P < 0.05). GLS, torsion were significantly improved in the three NSTEMI groups at postoperative 1 and 3 months (P < 0.05). HF-REF group showed improved GCS on postoperative 1 and 3 month compared with preoperative data, and improved GLS at 3-month follow-up compared with 1-month follow-up (P < 0.05). The hs-TNT, hs-CRP and NT-pro BNP increased in the three NSTEMI groups before PCI (P < 0.05), and decreased at postoperative 1 and 3 month (P < 0.05). LVEF has the positive correlations with LV endsystolic volume (LVESV) and torsion, as well as the negative correlations with LVGLS, LVGCS, NT-pro BNP (P < 0.05).

CONCLUSIONS

The combinative detection of 3D-STI and NT-pro BNP is an efficient way to assess the cardiac function in patients diagnosed with NSTEMI undergoing PCI.