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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

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 end-diastolic 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

Objective·To explore the association of somatizatic symptoms, anxiety and depression with clinical prognosis in the patients with chronic heart failure (CHF).Methods·The patients with CHF who visited the Department of Cardiology, Renji Hospital, Shanghai Jiao Tong University School of Medicine from January 2018 to December 2021 were included. Demographic data and clinical features of the patients were collected. The Self-reported Somatic Symptom Scale of China (SSS-CN), the Patient Health Questionnaire-9 (PHQ-9), and the Generalized Anxiety Disorder-7 (GAD-7) were used to evaluate the patients′ conditions. Telephone follow-up was conducted at the 12th month after the first visit, and the specific information of the patients′ end-point events (including death, re-hospitalization, causes of death and re-hospitalization) was collected. Survival curve and Cox regression analysis were used to evaluate the clinical prognosis of the patients.Results·A total of 195 patients were included. The SSS-CN scores in CHF patients were different between the two genders, among the different heart rate groups and the different cardiac function grades of New York Heart Association (NYHA), also between the patients with anxiety/depression or not (all P

We presented an unreported T96R mutation induced transthyretin cardiac amyloidosis (ATTR). The biochemical and biophysical properties were explored to support its pathogenicity. Understanding the biochemical and biophysical nature of genetically mutated transthyretin (TTR) proteins is key to provide precise medical cares for ATTR patients. Genetic testing showed heterozygosity for the T96R pathogenic variant c.347C > G (ATTR p.T116R) after myocardial biopsy confirmed amyloid deposition. Biochemical characterizations revealed slight perturbation of its thermodynamic stability (Cm=3.7 M for T96R, 3.4 M for WT and 2.3 M for L55P (commonly studied TTR mutant)) and kinetic stability (t1/2=39.8 h for T96R, 42 h for WT and 4.4 h in L55P). Crosslinking experiment demonstrated heterozygous subunit exchange between wild-type and TTR T96R protein destabilized the tetramer. Inhibitory effect of tafamidis and diflunisal on TTR T96R fibril formation was slightly less effective compared to WT and L55P. A novel T96R mutation was identified for TTR protein. Biochemical and biophysical analyses revealed slightly destabilized kinetic stability. T96R mutation destabilized heterozygous protein but not proteolytic degradation, explaining its pathogenicity. Inhibitory effect of small molecule drugs on T96R mutation was different, suggesting personalized treatment may be required. [ABSTRACT FROM AUTHOR]