Objective To explore the diagnostic value of axial diffusion tensor imaging(DTI) for gliomas grading at 3 .0T MRI , analyze the characteristics of different grades gliomas of axial DTI in order to improve diagnostic accuracy .Methods A retrospec‐tive analysis was performed involving a group of 37 cases of high grade glioma and 26 cases of low grade glioma confirmed by the pathological results in affiliated hospital of Luzhou medical college ,observation analysis was obtained in axial DTI ,peritumoral neu‐rofibrillary was divided into three types :displacement ,interruption and neurofibrillary tangles(NFT) .Results among the 26 cases of low grade glioma ,there were 18 cases of displacement ;8 cases of interruption ,no NFT ;among the 37 cases of high grade glio‐mas ,there were 9 cases of displacement ,21 cases of interruption ,and 7 cases of NFT (1 case of frontal lobe ,6 cases of temporal lobe);ordinal variables rank sum test in two independent samples between high grade glioma group and low grade glioma showed significant differences(Z= -3 .756 ,P<0 .05);χ2 test showed no significant difference(P>0 .05) ,frontal lobe appeared NFT in 1 case ,accounting for 2 .7% (1/37) ,temporal lobe appeared NFT in 6 cases ,accounting for 16 .2% (6/37) .Conclusion Peritumoral neurofibrillary of the low grade gliomas more performed displacement ,the high grade gliomas show more interrupts and NFT at 3 .0T MRI ,NFT in high grade gliomas is often seen in the temporal and frontal lobe .

BACKGROUND:Digital three-dimensional model which can reflect the fine structure of the chambers inside heart not only enhances the understanding of cardiac physiology, but also provides basic medical data for the study of cardiac electrophysiology simulation and endocardial electrophysiological mapping navigation. OBJECTIVE:To construct the digital three-dimensional model of cardiac cavity from sectional data and in conformity with the actual anatomical structure. METHODS:Image segmentation was accomplished in MATLAB environment. Firstly, registration of human cardiac cavity slice dataset was realized. Secondly, classifying each composition was achieved by clustering method according to color characteristics of the image. Then, both cardiac cavity and related connected region was distinguished by region growing method. At last, the processed image was reconstructed through dedicated medical processing software into three-dimensional model of the cardiac cavity. RESULTS AND CONCLUSION:The proposed method could reconstruct quite exquisite three-dimensional model of the cardiac cavity. In models, left and right atrial and ventricular structure was clear. Aorta and superior vena cava were visible. Three tricuspid and mitral valve were also observed. Results indicated that reconstructed model can reflect the anatomical characteristics of cardiac cavity accurately, and provide basic medical data for the study on electrophysiological simulation and endocardial electric mapping.