Objective To investigate the diagnostic value of cystic pilocytic astrocytoma by MRI.Methods MRI features of cysticpilocytic astrocytoma proved pathologically in 26 patients were reviewed retrospectively.The location,morphology and signal characteristics of the tumors were analyzed.Results Among 26 cases the tumors localized in cerebellum(n=20) and cerebrum(n=6).This tumor could be divided into simple cystic and cystic type with node on the wall.Conclusion Cystic pilocytic astrocytoma usually occur in children andadolescents with typical MRI features.MRI features in combination with clinical manifestation,it is possible to diagnose cystic pilocyticastrocytoma correctly before operation.

DNA Mutational Analysis ; Diagnosis, Differential ; Humans ; Lymphohistiocytosis, Hemophagocytic ; diagnosis ; genetics ; therapy ; Mutation ; genetics ; Perforin ; Pore Forming Cytotoxic Proteins ; genetics ; Qa-SNARE Proteins ; genetics

Objective To investigate the applied value of computed radiography(CR) system in intravenous pyelography in children.Methods Intravenous pyelography were carried out by CR and traditional intensifying screen/film in 45 children respectively.The diagnostic specificity between CR and traditional intensifying screen/film was compared.Results Urinary system in children could be displayed well by CR,the quality of CR films was ensured.The diagnostic corresponding rate was 86.7% and 59.1% by CR and traditional intensifying screen/film respectively.Conclusion CR is of significance value in diagnosis of urologic diseases in children.

Objective To study the CT diagnosis of cerebral infarction after subarachnoid hemorrhage.Methods Clinical and CT findings of cerebral infarction after subarachnoid hemorrhage were analyzed 16 cases.Results Cerebral infarctions occurred in 7～13 d(average 10.5 d)after subarachnod hemorrhage.Multiple and bilaterial low densities in basal ganglia or/and brain lobes were characteristic of cerebral infarction after subarachnoid hemorrhage.Conclusion CT is an effect method for evaluation and diagnosis of cerebral infarction after subarachnoid hemorrhage.It is important to prevent its occurrence because it have high dead rate and bad prognosis.

Anti-seizure medications (ASMs) are the main therapy for epilepsy.There are many kinds of ASMs with complex mechanism of action, so it is difficult for pharmacists to examine prescriptions.This paper put forward some suggestions on the indications, dosage forms/routes of administration, appropriateness of usage and dosage, combined medication and drug interaction, long-term prescription review, individual differences in pathophysiology of children, and drug selection when complicated with common epilepsy, for the reference of doctors and pharmacists.

Objective:To explore the effect of fully automatic image segmentation of adenoid and nasopharyngeal airway by deep learning model based on U-Net network. Methods:From March 2021 to March 2022, 240 children underwent cone beam computed tomography（CBCT） in the Department of Otolaryngology, Head and Neck Surgery, General Hospital of Shenzhen University. 52 of them were selected for manual labeling of nasopharynx airway and adenoid, and then were trained and verified by the deep learning model. After applying the model to the remaining data, compare the differences between conventional two-dimensional indicators and deep learning three-dimensional indicators in 240 datasets. Results:For the 52 cases of modeling and training data sets, there was no significant difference between the prediction results of deep learning and the manual labeling results of doctors（P>0.05）. The model evaluation index of nasopharyngeal airway volume: Mean Intersection over Union（MIOU） s （86.32±0.54）%; Dice Similarity Coefficient（DSC）: （92.91±0.23）%; Accuracy: （95.92±0.25）%; Precision: （91.93±0.14）%; and the model evaluation index of Adenoid volume: MIOU: （86.28±0.61）%; DSC: （92.88±0.17）%; Accuracy: （95.90±0.29）%; Precision: （92.30±0.23）%. There was a positive correlation between the two-dimensional index A/N and the three-dimensional index AV/（AV+NAV） in 240 children of different age groups（P<0.05）, and the correlation coefficient of 9-13 years old was 0.74. Conclusion:The deep learning model based on U-Net network has a good effect on the automatic image segmentation of adenoid and nasopharynx airway, and has high application value. The model has a certain generalization ability.
Child ; Humans ; Adolescent ; Adenoids/diagnostic imaging* ; Image Processing, Computer-Assisted/methods* ; Pharynx ; Cone-Beam Computed Tomography ; Nose