The digitallization of field medical equipment for the modern troop is an important sign on military logistics modernization.The use of CR technology on the existing field X-ray equipment for digitallization upgrading can be combined with CR and PASC system,which is an effective channel on achieving digitalization of our military field X-ray image system.So the design plan of field CR and micro-PACS system combination is advanced.

Objective To evaluate the value of calcium-based quantitative spectral CT imaging in differential diagnosis of benign and malignant thyroid nodules.Methods Totally 82 patients with 98 thyroid nodules confirmed by pathology underwent unenhanced and dual-phase enhanced spectral CT scans before operation.Thyroid nodules were divided into malignant group (61 nodules) and benign group (37 nodules),according to histopathologic results.Besides,contralateral normal thyroid tissue of 50 patients was selected as normal group.The calcium concentration of malignant,benign and normal group in non-enhanced scanning was analysed.The optimal threshold to predict malignancy and the corresponding diagnostic sensitivity and specificity were obtained by ROC curve.Results The calcium concentrations for malignant, benign and normal group in non-enhanced scanning were (5.52±2.72) mg/cm3, (10.72±4.68) mg/cm3 and (24.66±7.58) mg/cm3 respectively.There were significant differences statistically in any two groups (P<0.001).For malignant thyroid nodules, the best diagnostic threshold of calcium concentration was 6.065 mg/cm3,and the diagnostic sensitivity and specificity were 65.6% and 91.9% respectively.Conclusion Spectral CT imaging can quantitatively assess the calcium concentration of thyroid nodules,which provides promising quantitative approach for distinguishing malignant thyroid nodules from benign nodules.

Objective To discuss the establishment and application of PACS of our hospital, and its significance for the digitization of the radiology department. Methods PACS was adopted to store and transmission of images by CR, CT, MRI, DSA. The radiologist used PACS workstation to perform post-processing of the images. Results With PACS, filmless viewing, improved diagnosis quality, accelerated generation of diagnosis report could all be implemented. Conclusion With the application of PACS to digital and filmless imaging, the patient service by the hospital can be highly improved.

Objective To analyze the adverse reactions of hysterosalpingography and prevention measures. Methods Totally 6 352 patients who underwent hysterosalpingography in our hospital between January 2006 and December 2013 were analyzed. Results Totally 836 cases had adverse reactions of different degrees including 312 cases of drug reactions and 626 cases of non?drug reactions. The adverse drug reactions were mainly hy?pogastralgia,laryngopharyngeal malaise,irritating cough,nausea,vomiting,shortness of breath,flush of the face,and pruritus. The non?drug reac?tions were mainly hypogastralgia,nausea,vomiting,pallor,speeding up of heart?beat,decreased blood pressure,dizziness,and blur version. Con?clusion Among patients who were negative for iodine anaphylactic test,there were still some who had adverse reactions of different degrees during HSG. Targeting at different conditions of reactions,corresponding prevention measures should be adopted to ensure the smooth progress of hysterosal?pingography.

Objective:To investigate the predictive value of MRI radiomics model in assessing the early response to concurrent chemoradiotherapy for locally advanced cervical squamous cell carcinoma.Methods:A total of 367 patients with pathologically proven locally advanced cervical squamous cell carcinoma (International Federation of Gynecology and Obstetrics stage ⅡB-ⅣA) in Liaoning Cancer Hospital & Institute from January 2013 to June 2019 were retrospectively collected. The patients were unable to undergo surgery and received complete concurrent chemoradiotherapy. Pelvic plain MRI, DWI and dynamic contrast-enhanced MRI were performed within 2 weeks before treatment and at the end of the 4th week of treatment. Patients were divided into complete response (CR) group ( n=247) and non-CR group ( n=120) according to response evaluation criteria in solid tumors 1.1. The patients were divided into a training set ( n=256) and a validation set (n=111) via a randomized split method at a ratio of 7∶3. Two radiologists drew the region of interest on the DWI, T 2WI and contrast-enhanced T 1WI (delayed phase) images before treatment to form the volume of interest finally. Totally 1 906 radiomics features were extracted from 3 single sequence images, respectively. Feature correlation analysis and tree model were used for feature selection. Three classifier learning algorithms, namely logistic regression (LR), support vector machine and random forest, were used for machine learning and the best classifier was selected. Based on the best classifier, 3 single sequence radiomics models were built, and a multi-sequence combined model was obtained by multivariate LR analysis. The differences in the area under the receiver operating characteristic curve (AUC) of the 3 single sequence models and the multi-sequence combined model were compared by DeLong test. The clinical application value of the multi-sequence combined model was evaluated by decision analysis curve. Results:In the training set and validation set, the LR classifier model had the best performance. Based on the LR classifier, AUCs of DWI, T 2WI, contrast-enhanced T 1WI and combined sequences in the training set were 0.77, 0.74, 0.79 and 0.86, respectively, and AUCs in the validation set were 0.71, 0.66, 0.75 and 0.77, respectively. In the training set, the AUC of multi-sequence combined model was higher than those of DWI, T 2WI and contrast-enhanced T 1WI sequence models, and the differences were statistically significant ( Z=3.01, 3.56, 2.83; P=0.003, 0.001, 0.005). In the validation set, the AUC of multi-sequence combined model and T 2WI model had significant difference ( Z=2.46, P=0.015). The decision analysis curve showed that when the threshold probability was in the range of 0.44 to 0.88, the multi-sequence combined model yielded a net benefit. Conclusion:Based on the LR classifier, the combined model built by radiomics features of multi-sequence MRI images has predictive value for assessing the early response of concurrent chemoradiotherapy for locally advanced cervical squamous cell carcinoma.