Anatomic characteristics and novel transplantation model of the canine uterus.

Background: In Vietnam, the rate of absolute uterine factor infertility is increasing, but no study has been published on uterine transplantation. The present study was designed to comprehensively observe the canine uterine anatomy and to examine the possibility of using a living canine donor for uterine transplantation training and further research.

Methods: Ten female Vietnamese mixed-breed dogs were sacrificed for anatomical research, and 15 additional pairs were used to evaluate the novel uterine transplant model.

Primary cardiac epithelioid angiosarcoma: A case report.

Primary cardiac angiosarcoma is an extremely rare, high-grade malignancy. Here, we describe the case of a 44-year-old male patient with a heart tumor in the left atrium wall, which caused a large amount of pericardial effusion that invaded the surrounding area and is visible on transthoracic echocardiography, computed tomography, and magnetic resonance imaging. The postoperative histopathological results confirmed this case as a primary cardiac epithelioid angiosarcoma.

The Association Between Femoral Artery Intima-Media Thickness and Serum Glucagon-Like Peptide-1 Levels Among Newly Diagnosed Patients with Type 2 Diabetes Mellitus.

Introduction: Endothelium dysfunction and decrease of incretin effects occur early in type 2 diabetes mellitus and these changes contribute to diabetic cardiovascular complications such as atherosclerosis, thick intima-media, coronary, and peripheral arterial diseases. In patients with diabetes, the femoral artery is a site of a high incidence of injury in peripheral vascular diseases, and atherosclerotic changes may appear earlier in the femoral artery compared to the carotid artery. This study was conducted to determine the prevalence of increased femoral artery intima-media thickness (IMT) and atherosclerotic plaque and their correlation with serum glucagon-like peptide-1 (GLP-1) levels in newly-diagnosed patients with type 2 diabetes mellitus.

Combining deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance.

We introduce a new methodology that combines deep learning and level set for the automated segmentation of the left ventricle of the heart from cardiac cine magnetic resonance (MR) data. This combination is relevant for segmentation problems, where the visual object of interest presents large shape and appearance variations, but the annotated training set is small, which is the case for various medical image analysis applications, including the one considered in this paper. In particular, level set methods are based on shape and appearance terms that use small training sets, but present limitations for modelling the visual object variations.