Objiective To observe the changes of angioarchitecture of the optic disc in cats eyes after radial optic neurotomy (RON). Methods Ten healthy adult cats underwent unilateral RON randomly in 10 eyes as an operative group in this trial, and the fellow eyes (10 eyes) were as the control group. The colophony samples of vascular angioarchitecture of 20 eyes were made 90 days after RON and scanning electron microscope was used for the observation. Results In the control group, the blood supply of optic disc mainly came from the short posterior ciliary artery, pial artery, and retinal ciliary artery; the choroidal capillary vessels around the optic disc didnprime;t take part in the blood supply in the anterior area; retinal central vascular system and complete arterial circle around the optic nerves were not seen. In the operative group, a V-shaped defect of the optic disc, retinal blood vessels and choroidal capillary vessels was found at the surgical incision; no injury of retinal blood vessels and choroidal large vascular layer was seen, and neovascularization at the incision were not found. Conclusions RON may cause the vascular defect of the optic disc and the peripheral local tissues. The depth of the incision doesnprime;t reach the Zinn-Hallers circle. (Chin J Ocul Fundus Dis, 2007, 23: 170-172)
There are various examination methods for cardiovascular diseases. Non-invasive diagnosis and prognostic information acquisition are the current research hotspots of related imaging examinations. Positron emission tomography (PET)/magnetic resonance imaging (MRI) is a new advanced fusion imaging technology that combines the molecular imaging of PET with the soft tissue contrast function of MRI to achieve their complementary advantages. This article briefly introduces several major aspects of cardiac PET/MRI in the diagnosis of cardiovascular disease, including atherosclerosis, ischemic cardiomyopathy, nodular heart disease, and myocardial amyloidosis, in order to promote cardiac PET/MRI to be more widely used in precision medicine in this field.
Detection and classification of malignant arrhythmia are key tasks of automated external defibrillators. In this paper, 21 metrics extracted from existing algorithms were studied by retrospective analysis. Based on these metrics, a back propagation neural network optimized by genetic algorithm was constructed. A total of 1,343 electrocardiogram samples were included in the analysis. The results of the experiments indicated that this network had a good performance in classification of sinus rhythm, ventricular fibrillation, ventricular tachycardia and asystole. The balanced accuracy on test dataset reached up to 99.06%. It illustrates that our proposed detection algorithm is obviously superior to existing algorithms. The application of the algorithm in the automated external defibrillators will further improve the reliability of rhythm analysis before defibrillation and ultimately improve the survival rate of cardiac arrest.