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Background: Diabetes mellitus (DM) is the most common metabolic disease worldwide and a major risk factor for adverse cardiovascular events, while the additive effects of DM on left ventricular (LV) deformation in the restrictive cardiomyopathy (RCM) cohort remain unclear. Accordingly, we aimed to investigate the additive effects of DM on LV deformation in patients with RCM. Materials and methods: One hundred thirty-six RCM patients without DM [RCM(DM−)], 46 with DM [RCM (DM+)], and 66 age- and sex-matched control subjects who underwent cardiac magnetic resonance (CMR) scanning were included. LV function, late gadolinium enhancement (LGE) type, and LV global peak strains (including radial, circumferential, and longitudinal directions) were measured. The determinant of reduced LV global myocardial strain for all RCM patients was assessed using multivariable linear regression analyses. The receiver operating characteristic curve (ROC) was performed to illustrate the relationship between DM and decreased LV deformation. Results: Compared with the control group, RCM (DM−) and RCM(DM+) patients presented increased LV end-diastolic index and end-systolic volume index and decreased LV ejection fraction. LV GPS in all three directions and longitudinal PDSR progressively declined from the control group to the RCM(DM−) group to the RCM(DM+) group (all p < 0.05). DM was an independent determinant of impaired LV GPS in the radial, circumferential, and longitudinal directions and longitudinal PDSR (β = − 0.217, 0.176, 0.253, and − 0.263, all p < 0.05) in RCM patients. The multiparameter combination, including DM, showed an AUC of 0.81(95% CI 0.75–0.87) to predict decreased LV GLPS and an AUC of 0.69 (95% CI 0.62–0.76) to predict decreased LV longitudinal PDSR. Conclusions: DM may have an additive deleterious effect on LV dysfunction in patients with RCM, especially diastolic dysfunction in RCM patients, indicating the importance of early identification and initiation of treatment of DM in patients with RCM. [ABSTRACT FROM AUTHOR]

Background: The relationship of left atrial (LA) strain to high‐risk heart failure (HF) events in patients with left ventricular myocardial noncompaction (LVNC) remains to be thoroughly investigated. Purpose: To evaluate the LA performance in patients with LVNC, and to investigate the prognostic value of LA phasic strain on high‐risk HF events, and its influencing factors. Study Type: Retrospective. Population: A total of 95 LVNC patients (74 with LA enlargement [LAE] and 21 without LAE) and 50 healthy controls. Field Strength/sequence: A 3.0 T, balanced steady‐state free‐precession cine imaging. Assessment: LA longitudinal strains were measured by cardiac MRI feature tracking technique. LA volume index (LAVI) and LA ejection fraction (LAEF) were calculated. Their intraobserver and interobserver reproducibility were evaluated. The primary outcome was high‐risk HF events, a composite of first HF hospitalization, hospitalization for worsening HF and death from HF. Statistical Tests: Student's t/Mann–Whitney U, one‐way analysis of variance/Kruskal–Wallis, Chi‐squared, receiver operating characteristic, Kaplan–Meier, log‐rank, Cox regression, Pearson and Spearman correlation and linear regression analyses were performed. The significance threshold was set at P < 0.05. Results: LAEF and LA longitudinal strains decreased in LVNC patients irrespective of the presence of LAE. During a median follow‐up of 32.17 months, high‐risk HF occurred in 13 (13.68%) patients. Patients with increased LAVI, decreased LAEF and decreased LA longitudinal strain had significantly higher risks of high‐risk HF events. In patients with LVNC, LA reservoir strain (εs) was independently associated with high‐risk HF (hazard ratio = 23.208 [95% CI: 2.993–179.967]). LV global longitudinal strain (LV GLS) (β = −1.783 [95% CI: −2.493 to −1.073]) was significantly and independently associated with εs. Intraobserver and interobserver reproducibility was excellent for LAVI, LAEF, and LA strain. Conclusion: In patients with LVNC, εs was an independent predictor for high‐risk HF events. LV GLS was an independent determinant of εs in LVNC. Evidence Level: 4 Technical Efficacy: Stage 4 [ABSTRACT FROM AUTHOR]

Background: Cardiac myxomas (CMs) and thrombi are associated with high morbidity and mortality. These two conditions need totally different treatments. However, they are difficult to distinguish using naked eye. In clinical, misdiagnoses occur now and then. This study aimed to compare the characteristics of CMs and cardiac thrombi and investigate the value of a radiomics signature in distinguishing CMs from cardiac thrombi, based on cardiovascular contrast-enhanced computed tomography (CECT) images.Methods: A total of 109 patients who had CMs (n = 59) and cardiac thrombi (n = 50) were enrolled in this retrospective study from 2009 to 2019. First, the lesion characteristics of cardiovascular CECT images were documented and compared by two radiologists. Then all patients were randomly allotted to either a primary group or a validation group according to a 7:3 ratio. Univariate analysis and the least absolute shrinkage and selection operator were used to select robust features. The best radiomics signature was constructed and validated using multivariate logistic regression. An independent clinical model was created for comparison.Results: The best radiomics signature was developed using eight selected radiomics. The classification accuracies of the radiomics signature were 90.8% and 90.9%, and the area under the receiver operating characteristic curves were 0.969 and 0.926 in the training and testing cohorts, respectively. Cardiovascular CECT images showed that the two diseases had significant differences in location, surface, Hydrothorax, pericardial effusion and heart enlargement. The naked eye findings were used to create the clinical model. All metrics of the radiomics signature were higher than those of clinical model.Conclusions: Compared with clinical model, the radiomics signature based on cardiovascular CECT performed better in differentiating CMs and thrombi, suggesting that it could help improving the diagnostic efficiency. [ABSTRACT FROM AUTHOR]

Background: Metabolic syndrome (MetS) is a cluster of metabolic abnormalities that collectively cause an increased risk of type 2 diabetes mellitus (T2DM) and nonatherosclerotic cardiovascular disease. This study aimed to evaluate the role of myocardial steatosis in T2DM patients with or without MetS, as well as the relationship between subclinical left ventricular (LV) myocardial dysfunction and myocardial steatosis. Methods and materials: We recruited 53 T2DM patients and 20 healthy controls underwent cardiac magnetic resonance examination. All T2DM patients were subdivide into two group: MetS group and non-MetS. LV deformation, perfusion parameters and myocardial triglyceride (TG) content were measured and compared among these three groups. Pearson's and Spearman analysis were performed to investigate the correlation between LV cardiac parameters and myocardial steatosis. The receiver operating characteristic curve (ROC) was performed to illustrate the relationship between myocardial steatosis and LV subclinical myocardial dysfunction. Results: An increase in myocardial TG content was found in the MetS group compared with that in the other groups (MetS vs. non-MetS: 1.54 ± 0.63% vs. 1.16 ± 0.45%; MetS vs. normal: 1.54 ± 0.63% vs. 0.61 ± 0.22%; all p < 0.001). Furthermore, reduced LV deformation [reduced longitudinal and radial peak strain (PS); all p < 0.017] and microvascular dysfunction [increased time to maximum signal intensity (TTM) and reduced Upslope; all p < 0.017)] was found in the MetS group. Myocardial TG content was positively associated with MetS (r = 0.314, p < 0.001), and it was independently associated with TTM (β = 0.441, p < 0.001) and LV longitudinal PS (β = 0.323, p = 0.021). ROC analysis exhibited that myocardial TG content might predict the risk of decreased LV longitudinal myocardial deformation (AUC = 0.74) and perfusion function (AUC = 0.71). Conclusion: Myocardial TG content increased in T2DM patients with concurrent MetS. Myocardial steatosis was positively associated with decreased myocardial deformation and perfusion dysfunction, which may be an indicator for predicting diabetic cardiomyopathy. [ABSTRACT FROM AUTHOR]

Background: Type 2 diabetes mellitus (DM2) may induce epicardial coronary artery diseases and left ventricular myocardial damaging as well. Left ventricular dysfunction was found in DM2. In this research, we compared the left ventricular dysfunction of coronary artery disease (CAD) patients with and without type 2 diabetes mellitus as well as normal controls using the volume-time curve of cardiac magnetic resonance (CMR).Methods: Sixty-one CAD patients (28 with DM2 and 33 without DM2) and 18 normal individuals were enrolled in this study. Left ventricular function parameters, including the end-diastolic and end-systolic volumes (EDV, ESV), stroke volume (SV) and ejection fraction (EF), and morphologic dimension parameters (end diastolic and systolic diameter (EDD and ESD), were measured and compared. Volume-time curve parameters, including the peak ejection rate (PER), peak ejection time (PET), peak filling rate (PFR), peak filling time from ES (PFT), peak ejection rate normalized to EDV (PER/EDV), and peak filling rate normalized to EDV (PFR/EDV), were derived automatically and compared.Results: LVEF in the diabetic CAD group was markedly reduced when compared to the normal and CAD without DM2 groups (all p < 0.05). LVEDD of the diabetic CAD group was significantly enlarged compared to the normal and non-diabetic CAD groups (all p < 0.05). More importantly, the lowest parameters of the left ventricle volume time curve (i.e., PER, PFR, PER/EDV and PFR/EDV) were obtained in diabetic CAD patients (all p < 0.05). In diabetic CAD patients, logistic regression analysis indicated that PET, PFT and PFR/EDV were independent predictors of left ventricular dysfunction (odds ratio [OR]: 1.1208, 1.0161, and 0.0139, respectively). The sensitivity and specificity of PET were 81.2 and 90%, respectively, when the threshold value was greater than 164.4 msec; for PFT, the sensitivity and specificity were 87.5 and 95.0%, respectively (criterion >166.0 msec). Higher sensitivity (87.5%) and specificity (100.0%) were obtained for PFR/EDV (criterion ≤3.7EDV/s).Conclusions: Parameters that are derived from the volume-time curve on CMR, including PET, PFT and PFR/EDV, allow clinicians to predict left ventricular dysfunction in diabetic CAD subjects with a high degree of sensitivity and specificity. [ABSTRACT FROM AUTHOR]

Purpose: As an extremely rare abnormity, type IIA pulmonary artery sling (PAS) tracheobronchial anomalies should be differentiated from normal airway for therapeutic decision-making. This study aimed to investigate the quantitative characteristics of type IIA PAS tracheobronchial anomalies using dual-source computed tomography (DSCT).Materials and Methods: From January 2009 to December 2016, there were 11 type IIA PAS patients enrolled for analysis and compared with 32 controls. The areas of the trachea, right upper lobar bronchus, left main bronchus, right intermediate bronchus [bridging bronchus (BB) in patients], and subcarinal angle [subpseudocarinal angle in patients] were measured. Measurements other than that for the angle were standardized with body surface area.Results: Significant differences were found between the type IIA PAS patients and controls in terms of DSCT measurements in the trachea (0.51 ± 0.32 cm2/m2 vs. 0.92 ± 0.18 cm2/m2, P < 0.001); left main bronchus (0.29 ± 0.14 cm2/m2 vs. 0.43 ± 0.18 cm2/m2, P = 0.01); right intermediate bronchus [BB in patients] (0.36 ± 0.13 cm2/m2 vs. 0.47 ± 0.12 cm2/m2, P = 0.02); and subcarinal angle [subpseudocarinal angle in patients] (116.27 ± 16.45° vs. 79.41 ± 15.71°, P < 0.001). Receiver operating characteristic analysis further revealed that these parameters may be indicators to differentiate tracheobronchial anomalies due to type IIA PAS from controls (AUC, 0.88-0.98; sensitivity, 81.7%-100%; specificity, 91.7%-100%).Conclusions: DSCT is an alternative technique to detect tracheobronchial anomalies in pediatric patients with type IIA PAS. It can provide accurate anatomic details for surgeons to determine therapeutic strategies. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to clarify the feasibility of myocardial strain using cardiovascular magnetic resonance (CMR) for the evaluation of left ventricular (LV) deformation in patients with Ebstein's anomaly (EA).Materials and Methods: We recruited 32 patients with EA and 30 controls for CMR examination and measured LV function, dimension and tissue tracking parameters (the global and regional radial, circumferential and longitudinal peak strain), together with the right ventricle (RV) dimension. LV strain parameters were compared among the controls, patients with preserved LV ejection fraction (LVEF; ≥55%), and patients with reduced LVEF (<55%). Pearson's correlation was used to evaluate relationships between tissue tracking parameters with the RVEDD/LVEDD index and LVEF. An ROC analysis was also performed to determine whether the cut-off values for PS could be used to differentiate LV dysfunction between patients with EA and controls. The intraclass correlation coefficient (ICC) was used to assess the inter- and intra-observer variability.Results: The global strain parameters all decreased significantly in the EA group compared with the control group (all P<0.05). Furthermore, the global radial and circumferential peak strain (PS) were obviously even lower in the reduced LVEF group than the strain measured in preserved LVEF groups (28.64% vs. 37.39%, p<0.05; and -8.20% vs. -17.89%; p<0.05; respectively). The regional strain abnormalities in EA patients were mainly involved in basal and middle segments. The results also demonstrated a significant correlation between the ratio of the RV end-diastolic dimension to the LV end-diastolic dimension (RVEDD/LVEDD index) with the global circumferential PS (r=0.508) and the longitudinal PS (r=0.474), as well as a good correlation between radial PS and LVEF (r=0.465). The ICCs for intra- and inter-observer variability were 0.797-0.904 and 0.701-0.896.Conclusions: LV strain serves an earlier and more comprehensive measurement of LV dysfunction than LVEF in EA, which could potentially be included as a supplementary diagnostic procedure in the evaluation of EA. [ABSTRACT FROM AUTHOR]

Purpose: The aim of this study was to assess the correlations of functional and dimensional parameters with the severity of tricuspid regurgitation in patients with Ebstein's anomaly (EA) by using cardiac magnetic resonance (CMR) imaging. Materials and Methods: Thirty-three patients with EA without previous cardiac surgery and 25 normal individuals were recruited and underwent both cardiac MR imaging and preoperative transthoracic echocardiography. The left ventricular (LV) functional parameters and dimensions of the right ventricle (RV) and LV were measured using 3.0-T cardiac MR imaging. Tricuspid regurgitation severity grading was estimated by echocardiography. The functional and dimensional parameters were compared between EA patients and controls using independent sample t-tests. Spearman's rank correlation was used to determine the correlations between the functional and dimensional parameters and tricuspid regurgitation. Receiver operating characteristic (ROC) analysis was used to predict tricuspid regurgitation severity using individual functional and dimensional parameters. Results: Statistical analysis revealed significant differences in the functional and dimensional parameters between EA patients and controls. Within the EA group, tricuspid valve regurgitation negatively correlated well with the left ventricular ejection fraction (LVEF) (r=-0.558, p=0.001). The ratio of the right ventricular (functional right ventricle) end-diastolic dimension to the left ventricle end-diastolic dimension (RVEDD/LVEDD) in EA patients also correlated well with the severity of tricuspid valve regurgitation (r=0.492, p=0.004). Moreover, ROC analysis revealed that high sensitivity and specificity were obtained for predicting the severity of tricuspid valve regurgitation with LVEF (78.3%, 90.0%) and RVEDD/LVEDD (78.3%, 94.3%). Conclusion: In EA patients, the left and right ventricular functional and dimensional parameters from MRI correlated well with tricuspid regurgitation, which helped predict the severity of EA. [ABSTRACT FROM AUTHOR]

• We made an innovative attempt to apply artificial intelligence (AI) techniques in the diagnosis of congenital heart disease and associated pulmonary arterial hypertension based on a large-scale chest radiograph dataset (n = 3255). • AI achieved promising performance in diagnosing congenital heart disease and associated pulmonary arterial hypertension, outperforming radiologists. • The utilization of AI improved the performance of radiologists in diagnosing congenital heart disease and associated pulmonary arterial hypertension. To explore the possibility of automatic diagnosis of congenital heart disease (CHD) and pulmonary arterial hypertension associated with CHD (PAH-CHD) from chest radiographs using artificial intelligence (AI) technology and to evaluate whether AI assistance could improve clinical diagnostic accuracy. A total of 3255 frontal preoperative chest radiographs (1174 CHD of any type and 2081 non-CHD) were retrospectively obtained. In this study, we adopted ResNet18 pretrained with the ImageNet database to establish diagnostic models. Radiologists diagnosed CHD/PAH-CHD from 330/165 chest radiographs twice: the first time, 50% of the images were accompanied by AI-based classification; after a month, the remaining 50% were accompanied by AI-based classification. Diagnostic results were compared between the radiologists and AI models, and between radiologists with and without AI assistance. The AI model achieved an average area under the receiver operating characteristic curve (AUC) of 0.948 (sensitivity: 0.970, specificity: 0.982) for CHD diagnoses and an AUC of 0.778 (sensitivity: 0.632, specificity: 0.925) for identifying PAH-CHD. In the 330 balanced (165 CHD and 165 non-CHD) testing set, AI achieved higher AUCs than all 5 radiologists in the identification of CHD (0.670–0.858) and PAH-CHD (0.610–0.688). With AI assistance, the mean ± standard error AUC of radiologists was significantly improved for CHD (ΔAUC + 0.096, 95 % CI: 0.001–0.190; P = 0.048) and PAH-CHD (ΔAUC + 0.066, 95 % CI: 0.010–0.122; P = 0.031) diagnosis. Chest radiograph-based AI models can detect CHD and PAH-CHD automatically. AI assistance improved radiologists' diagnostic accuracy, which may facilitate a timely initial diagnosis of CHD and PAH-CHD. [ABSTRACT FROM AUTHOR]