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Objective·To analyze the differences and classify hypertrophic cardiomyopathy (HCM) patients and healthy controls (HC) using short-axis cine cardiac magnetic resonance (CMR) images-derived radiomics features. Methods·One hundred HCM subjects were included, and fifty HC were randomly selected at 2∶ 1 ratio during January 2018 to December 2021 in the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine. The CMR examinations were performed by experienced radiologists on these subjects. CVI 42 post-processing software was used to obtain left ventricular morphology and function measurements, including left ventricular ejection fraction (LVEF), left ventricular end-diastolic volume (LVEDV) and left ventricular end-diastolic mass (LVEDM). The 3D radiomic features of the end-diastolic myocardial region were extracted from short-axis images CMR cine. The distribution of the radiomic features in the two groups was analysed and machine learning models were constructed to classify the two groups. Results·One hundred and seven 3D radiomic features were selected and extracted. After exclusion of highly correlated features, least absolute shrinkage and selection operator (LASSO) was used, and a 5-fold cross-validation was performed. There were still 11 characteristics with non-zero coefficients. The K-best method was used to decide the top 8 features for subsequent analysis. Among them, four features were significantly different between the two groups (all P<0.05). Support vector machine (SVM) and random forest (RF) models were constructed to discriminate the two groups. The results showed that the maximum area under the curve (AUC) for the single-feature model (first order grayscale: entropy) was 0.833 (95%CI 0.685‒0.968) and the maximum accuracy for the multi-feature model was 83.3% with an AUC of 0.882 (95%CI 0.705‒ 0.980). Conclusion·There are significant differences in both left ventricular function and left ventricular morphology between HCM and HC. The 3D myocardial radiomic features of the two groups are also significantly different. Although single feature is able to distinguish the two groups, the combination of multi-features show better classification performance. [ABSTRACT FROM AUTHOR]

Objective·To assess the feasibility of using 3D imaging features extracted from cardiac magnetic resonance (CMR) short-axis cine images to predict left ventricular ejection fraction (LVEF). Methods·A total of 100 left ventricular hypertrophy (LVH) patients who visited the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021, as well as 100 healthy control (HC) subjects during the same period, were included. All subjects completed CMR examinations under the supervision of experienced cardiologists and radiologists. The endocardial and epicardial contours were then manually delineated by cardiologists. Measurements of cardiac function and morphology were completed and data was recorded, including LVEF, left ventricular end-diastolic volume (LVEDV), and left ventricular enddiastolic mass (LVEDM). Myocardial 3D radiomic features of CMR-cine sequences were extracted by the Pyradiomics package, and selected and sorted by using correlation coefficient and K-best method. The LVEF prediction was performed with linear regression (LR), random forest (RF) and gradient boost (GB) methods. Results were also compared with LVEF prediction based on clinical information and CMR parameters. Results·In terms of clinical indicators, there were significant differences between the LVH and HC groups, such as LVEDV and LVEDM (all P<0.05); after extracting 3D radiomic features, the top 10 features were selected for further analysis. LR regression model, GB regression model and RF regression model were constructed for predicting the LVEF, and RF regression models showed the best results with seven features, in which the mean absolute error (MAE) was 0.066±0.002. Further comparison results showed that the model using radiomic information with CMR parameters (MAE=0.056±0.001) had the best performance and it was significantly better than the model using radiomic features (MAE= 0.066±0.002) or CMR parameters (MAE=0.060±0.001) alone (both P<0.05). Conclusion·The use of radiomic features for LVEF prediction has certain feasibility, and combining radiomic features with CMR parameters can further improve the prediction accuracy of the model. [ABSTRACT FROM AUTHOR]

Left ventricular mechanical dyssynchrony (LVMD) is one of the manifestations of abnormal left ventricular motion. And the measured indexes related to LVMD are the indexes derived from left ventricular strain, which can predict the response to cardiac resynchronization therapy and the prognosis of the patients with acute myocardial infarction. The premise of LVMD diagnosis is to measure segmental strains of left ventricle accurately. As an emerging cardiac imaging technology, cardiac magnetic resonance (CMR) can accurately measure the strain of each left ventricle segment, which makes it valuable in both clinic and scientific research. In this article, the mechanism of LVMD, the measurement by CMR and its clinical application to heart diseases are reviewed. [ABSTRACT FROM AUTHOR]

Objective·To investigate the predictive value of myocardial strain in left ventricular remodeling (LVR) after acute ST-segment elevation myocardial infarction (STEMI). Methods·Forty-seven patients with STEMI who were admitted to Department of Cardiology of Shanghai Sixth People's Hospital, Shanghai Jiao Tong University from December 2018 to December 2019 and successfully received emergency primary percutaneous coronary intervention were included. Cardiac magnetic resonance (CMR) was performed at the acute stage of STEMI and 1 year later. Left ventricular stroke volume(LVSV), left ventricular mass index (LVMI), global longitudinal strain (GLS), global circumferential strain (GCS) and global radial strain (GRS) were analyzed. Biochemical indexes such as peak hypersensitive serum cardiac troponin I (hs-cTnI) and peak brain natriuretic peptide precursor (proBNP) and clinical data such as age, sex, blood pressure, heart rate (HR) were collected. LVR was defined as the following 2 models. The first one was that the left ventricular end diastolic volume (LVEDV) increased by ≥20% after 1 year of STEMI compared with the baseline. The second one was that the left ventricular end systolic volume (LVESV) increased by ≥15% after 1 year of STEMI compared with the baseline. Patients with STEMI were divided into LVR group and non-LVR group according to the above two models. The differences of CMR index, biochemical index and clinical data between the two groups were compared. Logistic regression was performed and receiver operating characteristic curve was drawn. Results·In the model where LVEDV increased by ≥20% 1 year after the acute stage of STEMI, the LVR group and the non-LVR group had statistically significant differences in baseline HR (P=0.003), LVSV (P=0.034), LVMI (P=0.029), GLS (P=0.003), GCS (P=0.016) and GRS (P=0.019). Logistic regression analysis showed that baseline HR and GLS were significantly correlated with LVR ( β=-0.070, OR=0.932, P=0.043; β=-0.334, OR=0.716, P=0.031). When the cut-off value of GLS was -9.835, the sensitivity and specificity of LVR prediction were 75.0% and 71.0%, respectively. In the model where LVESV increased by ≥15% 1 year after the acute stage of STEMI, there were statistically significant differences in peak hs-cTnI (P=0.035), peak proBNP (P=0.044), LVMI (P=0.034) and GLS (P=0.010) between the LVR group and the non-LVR group. Logistic regression analysis showed that peak hs-cTnI and baseline GLS were significantly correlated with LVR ( β=-0.017, OR=0.982, P=0.024; β=-0.304, OR=0.738, P=0.041). When the cut-off value of GLS was -11.145, the sensitivity and specificity for LVR prediction were 94.1% and 50.0%, respectively. Conclusion·In patients with STEMI, baseline GLS has a good predictive value for LVR, while GCS and GRS have no significant predictive value. [ABSTRACT FROM AUTHOR]

Objective·To explore the association between body mass index (BMI) and myocardial involvement in patients with systemic lupus erythematosus (SLE). Methods·Fifty-four healthy participants and sixty-one patients with SLE who were admitted to the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine were prospectively recruited from July 2014 to November 2016 and then underwent cardiac magnetic resonance (CMR) and echocardiography examination. SLE patients were grouped according to the quartile of the BMI index, and then CMR morphology, function and histology indicators of each group were compared. The relationship between BMI and extracellular volume fraction (ECV) was explored by using multivariate linear analysis. Results·Compared with normal BMI group (18.73‒23.00 kg/m2) and high BMI group (>23.00 kg/m2), low BMI group (≤18.72 kg/m2) had higher median ECV (34.33% vs 30.52% vs 31.44%, P=0.007) after being adjusted for age and disease duration. The incidences of right ventricular hypertrophy (33.3%), pulmonary hypertension (26.7%) and edema (6.7%) were lower in low normal BMI group (18.73‒ 20.20 kg/m2) than those in the low BMI group, high normal BMI group (20.21‒23.00 kg/m2) and high BMI group. There was a strong correlation between BMI and ECV in long standing SLE patients. When BMI was less than 23.00 kg/m2, it showed a negative correlation (r=-0.597, P=0.009), and a positive correlation (r=0.739, P=0.023) when over 23.00 kg/m2. However, there was no significant correlation between ECV, left ventricular (LV) ejection fraction, LV end-systolic volume and BMI in control group. In the multivariable linear regression, BMI in patients with SLE was associated with elevated ECV independently after being adjusted for age, usage of immunosuppressor and pulmonary artery pressure (BMI>23.00 kg/m2: β=-0.457, P=0.006. BMI≤ 23.00 kg/m2: β=0.766, P=0.001). Conclusion·Cardiac involvement in SLE is closely related to BMI. Low BMI patients should be careful with the cardiac injury. Maintaining BMI at normal low level (18.73‒20.20 kg/m2) and avoiding overweight (≤23.00 kg/m2) may be necessary to myocardial protection. [ABSTRACT FROM AUTHOR]

Objective·To investigate the effect of microvascular obstruction (MVO) on left ventricle function and prognosis in patients with ST-segment elevation myocardial infarction (STEMI) by using cardiac magnetic resonance (CMR) technique. Methods·A total of 124 patients with STEMI in the Department of Cardiology of Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2016 to December 2017 were enrolled. The percentage of myocardial infarction size, the percentage of myocardial MVO size and left ventricle function after reperfusion were evaluated by CMR technique. According to the percentage of myocardial MVO size, the patients were divided into MVO (+) group and MVO (-) group. The baseline characteristics, blood biochemical indexes and CMR indexes of the two groups were compared. The MVO (+) group was further divided into 4 subgroups according to the quartiles of the percentage of myocardial infarction size. Pearson correlation analysis was used to explore the correlation between the percentage of myocardial MVO size and left ventricular ejection fractions (LVEF) in each subgroup. The incidence of adverse events within 30 days was observed. Receiver operating characteristic curve (ROC curve) was used to analyze the predictive value of the percentage of myocardial MVO size for adverse events. Results·The white blood cell count, creatine phosphokinase, creatine kinase MB, cardiac troponin I and total cholesterol in the MVO (+) group were significantly higher than those in the MVO (-) group (all P<0.05), while baseline characteristics showed no significant difference. LVEF in the MVO (+) group was lower than that in the MVO (-) group (P=0.000). Pearson correlation analysis showed that the percentage of myocardial MVO size was negatively correlated with LVEF (all P<0.05). ROC curve showed that the area under the curve of the percentage of myocardial MVO size in the prediction of adverse events within 30 days was 0.889 (95%CI 0.823‒0.975), and the sensitivity and specificity of the percentage of myocardial MVO size were more higher than that of the percentage of myocardial infarction size. Conclusion·The left ventricle function and prognosis in STEMI patients with MVO are worse, suggesting that more attention should be paid to the clinical intervention for such patients. [ABSTRACT FROM AUTHOR]