Mitral Geometry on the Mechanism of Left Ventricular Outflow Tract Obstruction in Hypertrophic Cardiomyopathy.

OBJECTIVE: The mechanism of left ventricular outflow tract obstruction (LVOTO) is complex in hypertrophic cardiomyopathy (HCM). We aimed to evaluate the impact of mitral valve geometry on LVOTO by echocardiography. MATERIALS AND METHODS: The study population comprised 177 consecutive patients with HCM. Morphological findings of left ventricular hypertrophy and LVOTO-related abnormalities were assessed by comprehensive transthoracic echocardiography. Aortomitral angle, mitral leaflet length, and coaptation height were measured and analyzed at rest. Multivariable stepwise forward logistic regression analysis was performed to identify geometric predictors of LVOTO. RESULTS: One hundred thirty-seven patients had an LVOT gradient ≥30 mm Hg. Multivariable logistic regression showed that aortomitral angle (odds ratio [OR], 0.89; 95% CI, 0.83-0.95, P < .001), coaptation height (OR, 1.96; 95% CI, 1.41-2.72, P < .001), and accessory mitral valve chordae tendineae (OR, 13.1; 95% CI, 4.32-39.95; P < .001) were independently associated with LVOTO. Receiver operating characteristic analysis showed that the area under the curve of mitral coaptation height was higher (area under the curve = 0.815) than the other 2 indicators (P < .05). CONCLUSION: Mitral coaptation height, aortomitral angle, and accessory mitral valve chordae tendineae were important predictors of SAM and LVOTO in HCM independent of septal hypertrophy.

Nomogram Based on CT Radiomics Features Combined With Clinical Factors to Predict Ki-67 Expression in Hepatocellular Carcinoma.

Objectives: The study developed and validated a radiomics nomogram based on a combination of computed tomography (CT) radiomics signature and clinical factors and explored the ability of radiomics for individualized prediction of Ki-67 expression in hepatocellular carcinoma (HCC). Methods: First-order, second-order, and high-order radiomics features were extracted from preoperative enhanced CT images of 172 HCC patients, and the radiomics features with predictive value for high Ki-67 expression were extracted to construct the radiomic signature prediction model. Based on the training group, the radiomics nomogram was constructed based on a combination of radiomic signature and clinical factors that showed an independent association with Ki-67 expression. The area under the receiver operating characteristic curve (AUC), calibration curve, and decision curve analysis (DCA) were used to verify the performance of the nomogram. Results: Sixteen higher-order radiomic features that were associated with Ki-67 expression were used to construct the radiomics signature (AUC: training group, 0.854; validation group, 0.744). In multivariate logistic regression, alfa-fetoprotein (AFP) and Edmondson grades were identified as independent predictors of Ki-67 expression. Thus, the radiomics signature was combined with AFP and Edmondson grades to construct the radiomics nomogram (AUC: training group, 0.884; validation group, 0.819). The calibration curve and DCA showed good clinical application of the nomogram. Conclusion: The radiomics nomogram developed in this study based on the high-order features of CT images can accurately predict high Ki-67 expression and provide individualized guidance for the treatment and clinical monitoring of HCC patients.

Factors associated with left ventricular diastolic dysfunction in patients with septic shock.

PURPOSE: To investigate risk factors associated with left ventricular diastolic dysfunction (LVDD) of patients with septic shock. MATERIALS AND METHODS: Patients with septic shock concomitant with or without LVDD were retrospectively enrolled and divided into the LVDD group (n = 17) and control without LVDD (n = 85). The clinical and ultrasound data were analyzed. RESULTS: A significant (P < 0.05) difference existed between the two groups in serum creatinine, APACHE II score, serum glucose, triglyceride, BUN, FT4, LAVI, mitral E, average e', E/average e', septal e', septal e'/septal s', E/septal e', lateral s', lateral e', and E/lateral e'. LAVI > 37 mL/m2, septal e' < 7 cm/s (OR 11.04, 95% CI 3.38-36.05), septal e'/septal s' < 0.8 (OR 4.09, 95% CI 1.37-12.25), E/septal e' > 15 (OR 22.86, 95% CI 6.09-85.79), lateral e' < 8 cm/s (OR 9.16, 95% CI 2.70-31.07), E/lateral e' > 13 (OR 52, 95% CI 11.99- 225.55), lateral s' < 10 (OR 3.36, 95% CI 1.13-9.99), average e' > 10, E/average e' > 10 (OR 9.53, 95% CI 2.49-36.46), APACHE II score > 16 (OR 3.33, 95% CI 1.00-11.03), SOFA > 5 (or 3.43, 95% CI 1.11-10.60), BUN > 12 mmol/L (OR 3.37, 95% CI 1.15-9.87), serum creatinine > 146 µmol/L (OR 5.08, 95% CI 1.69-15.23), serum glucose > 8 mmol/L (OR 3.36, 95% CI 1.09-10.40), and triglyceride > 1.8 mmol/L were significant (P < 0.05) risk factors for LVDD. LAVI > 37 ml/m2, lateral e' < 8 cm/s, E/lateral e' > 13, and SOFA > 5 were significant (P < 0.05) independent risk factors for LVDD. ROC curve analysis demonstrated that the cut-off value and AUC were 37.09 mL/m2 and 0.85 for LAVI, 8.00 cm/s and 0.89 for lateral e', 12.86 and 0.82 for E/lateral e', and 5.00 and 0.69 for SOFA, respectively. CONCLUSION: Left atrial volume index, mitral lateral e', E/lateral e', and SOFA score are significant independent risk factors for predicting left ventricular diastolic dysfunction in patients with septic shock.

The Emerging Role of Ultrasonic Nanotechnology for Diagnosing and Treatment of Diseases.

Nanotechnology has been commonly used in a variety of applications in recent years. Nanomedicine has also gotten a lot of attention in the medical and treatment fields. Ultrasonic technology is already being used in research as a powerful tool for manufacturing nonmaterial and in the decoration of catalyst supports for energy applications and material processing. For the development of nanoparticles and the decoration of catalytic assisted powders with nanoparticles, low or high-frequency Ultrasonic are used. The Ultrasonic is frequently used in joint venture with the nanotechnology from the past few years and bring tremendous success in various diseases diagnosing and treatment. Numerous kinds of nanoparticles are fabricated with desired capabilities and targeted toward different targets. This review first highlights the Ultrasonic Treatment and processing of Nanoparticles for Pharmaceuticals. Next, we explain various nanoparticles with ultrasonic technology for different diagnosing and treatment of various diseases. Finally, we explain the challenges face by current approaches for their translation in clinics.