Objective:To investigate the quality control of magnetic resonance enterography(MRE)in the diagnosis of intestine diseases,and analyze the factors that affected the imaging quality of MRE,and enhance the imaging quality of MRE through adopted the measures of quality control.Methods:The documents of MRE examinations of 167 patients with intestinal disease who admitted to the 900th Hospital of People's Liberation Army Joint Service Support Force from May 2018 to March 2023 were retrospectively analyzed.The image qualities of all patients were evaluated after they completed clinical and image examinations.The reasons that image quality could not meet the requirement of diagnosis were analyzed.And then,the measures of quality control were proposed.Results:In 167 patients with intestinal disease,the MRE images of 153 patients(91.62%)could meet the requirement of diagnosis.In 14 patients(8.38%)whose MRE images could not meet the requirement of diagnosis,the reason of 3 cases(1.80%)was poor respiratory coordination,and that of 2 cases(1.20%)was there were more severe magnetic sensitive artifacts in images,and that of 1 case(0.60%)was severe intestinal peristalsis leaded to blurred images,and that of 2 cases(1.20%)was the flow void effect from intestinal peristalsis inside of intestinal cavity could not meet the requirement of diagnosis,and that of 4 cases(2.40%)was the intestinal tube without incomplete dilation caused by poor oral filling contrast agent,and that of 2 cases(1.20%)was many residues in intestine due to poor preparation for intestine.Aimed at the factors that MRE images could not meet requirement of diagnosis,we proposed the following quality control measures:①the biphasic contrast agents with favorable safety,without severe adverse reactions,which can fully dilate intestinal cavity,should be selected.②we should do well for the dilation of intestinal tube,and inhibit the intestinal peristalsis and conduct respiratory training.③we should conduct scan with wide field at coronal site,so as to display panorama image of intestine.④The scans of conventionally anatomical sequence and functional imaging sequence on axis position were performed on lesions.Conclusion:MRE technique should choose appropriate contrast agent in the quality control of the diagnosis of intestine diseases,and do well the preparation for patients before examination.Using intraluminal contrast agents,conducting intestinal dilation and optimal imaging technique are essential for obtaining intestinal MRE images with high quality.

Objective : To evaluate the prognostic value of a radiomics model based on the peritumoral region of gli- oma． Methods : 138 patients with glioma were retrospectively analyzed ，medical imaging interaction toolkit ( MITK) software was used to obtain the magnetic resonance imaging (MRI) images of peritumoral area 5 mm，10 mm and 20 mm from the tumor edge and extract texture features．The texture features were screened the radiomics model was established and the radiomic score was calculated．A clinical prediction model and a combined predic- tion model along with Rad-score and clinical risk factors were established．The combined prediction model was dis- played as a nomogram，and the predictive performance of the model for survival in glioma patients was evaluated. Results : In the validation set，the C-index value of the radiomics model based on the peritumoral region 10 mm a- way from the tumor edge based on T2 weighted image (T2WI) images was 0. 663 (95% CI = 0. 72－0. 78) ，resul- ting in the best prediction performance．On the training set and validation set，the C-index of the nomogram was 0. 770 and 0. 730，respectively，indicating that the prediction performance of nomogram was better than those of the radiomics model and clinical prediction model．The model had the highest prediction effect on the 3-year survival rate of glioma patients (training set area under curve (AUC) = 0. 93，95% CI = 0. 83 － 0. 98 ; validation set AUC = 0. 88，95% CI = 0. 76 －0. 99) ．The calibration curve showed that the joint prediction nomogram in both the training set and the validation set had good performance． Conclusion The combined prediction model based on the preoperative T2WI images in the peritumoral region 10 mm from the tumor edge and the clinicopathological risk factors can accurately predict the prognosis of glioma，providing the best effect of prediction on the 3-year survival rate of glioma.