Objectives To analyze the risk factors of sulfur hexafluoride microbubble contrast agent intravasation during hysterosalpingo‐contrast sonography (HyCoSy), and to explore a simple prediction model by the obvious clinical history. Methods This was a retrospective study included 299 infertility women who had undergone HyCoSy examination from July 1, 2018 to June 31, 2019. The factors were recorded, including age, endometrial thickness, balloon length, infertility type, history of intrauterine surgery, history of pelvic surgery, and tubal patency. The method of multivariate logistic regression analysis was adopted to analyze the risk factors affecting the contrast agent intravasation, and the receiver operating characteristic curves were plotted to test their efficacy. Results Secondary infertility, a history of intrauterine surgery, thin endometrial thickness, and tubal obstruction were all risk factors of the occurrence of intravasation (P < .05). And the area under the receiver operating characteristic curves of the multifactor‐combined prediction model of the intravasation was significantly larger than that of single‐factor. Conclusions Sonographers and gynecologists should be familiar with the risk factors of intravasation and select the appropriate timing of HyCoSy toward reducing the occurrence of intravasation and other complications after thoroughly explaining and communicating with the patients.
BackgroundUltrasonography, the preferred adjunct examination method and the differential diagnostic tool for gynecologic emergency, can reflect the change pattern of gynecological diseases in daytime and at night. The purpose of this study was to analyze the diseases through gynecological emergency ultrasound in daytime and at night and to evaluate the day–night difference in the accuracy of ultrasound diagnosis.Materials and methodsRetrospective analysis was performed on the 2016 clinical data of the patients who had undergone gynecological emergency ultrasound at The First Affiliated Hospital of Guangxi Medical University, and the results of the ultrasound diagnosis were compared with the clinical diagnosis.ResultsThe following categories of gynecologic emergency diseases during the daytime and at night have significant statistical differences in the constituent ratio (P<0.001); ectopic pregnancy, intrauterine pregnancy, acute pelvic inflammatory disease, no organic lesion in uterine and adnexa; while the constituent ratio of abortion and trophoblastic diseases, ovarian tumor, uterine and endometrial lesions, was no statistical difference during the daytime and at night (P>0.05). The overall coincidence rate of ultrasound diagnosis was 96.3% (daytime, 97.9%; night, 86.4%). The coincidence rates of ectopic pregnancy ultrasonography diagnosis in daytime and at night were 96.4 and 75.4%, respectively; the difference was statistically significant (P<0.001).ConclusionSince the different constituent ratio of disease between daytime and night gynecological emergency ultrasound was significantly different, and the diagnostic accuracy of ultrasound at night was low; hence, the ultrasound doctor at night should pay attention to improve the accuracy of diagnosis and the ability of differential diagnosis of ectopic pregnancy, and it is suggested that some suspected cases during the night should be reexamined again in the daytime to eliminate the errors resulted from subjective factors.
Objective To analyze the risk factors of the operators on contrast agent intravasation during hysterosalpingo-contrast sonography (HyCoSy). Methods We retrospectively collected 399 infertile women who underwent HyCoSy by the same sonographer. These patients were divided into two groups according to the way how the assistants connected the syringe to the uterus radiography catheter to inject the contrast agent. We analyzed whether the use of different contrast bolus injection methods had any influence on the incidence of intravasation during HyCoSy. Results There was no significant difference between the two groups with different cross-sectional areas of the syringe outflow tract in the risk variables for intravasation, but the intravasation rates of the two groups were different, 26.4% in group A and 17.1% in group B, P <0.05. The primary manifestation was that when both fallopian tubes were unobstructed, the intravasation rate of group B with smaller cross-sectional area of the outflow tract of the syringe was lower, and the difference was statistically significant. The inferences drawn from our physics model were also in line with the clinical results. Conclusion The influence of different operators on the contrast agent intravasation rate of HyCoSy cannot be ignored. The assistants of HyCoSy examination should inject the contrast agent slowly and steady, and a needle can be used as a flow restrictor to control the flow into the uterine cavity per unit time, slow down the rising speed of intrauterine pressure, and avoid the accumulation of contrast agent in the uterine cavity, so as to reduce the intravasation caused by operator factors.
Objective To evaluate the value of ultrasound-based radiomics in the preoperative prediction of type I and type II epithelial ovarian cancer. Methods A total of 154 patients with epithelial ovarian cancer were enrolled retrospectively. There were 102 unilateral lesions and 52 bilateral lesions among a total of 206 lesions. The data for the 206 lesions were randomly divided into a training set (53 type I + 71 type II) and a test set (36 type I + 46 type II) by random sampling. ITK-SNAP software was used to manually outline the boundary of the tumor, that is, the region of interest, and 4976 features were extracted. The quantitative expression values of the radiomics features were normalized by the Z-score method, and the 7 features with the most differences were screened by using the Lasso regression tenfold cross-validation method. The radiomics model was established by logistic regression. The training set was used to construct the model, and the test set was used to evaluate the predictive efficiency of the model. On the basis of multifactor logistic regression analysis, combined with the radiomics score of each patient, a comprehensive prediction model was established, the nomogram was drawn, and the prediction effect was evaluated by analyzing the area under the receiver operating characteristic curve (AUC), calibration curve and decision curve. Results The AUCs of the training set and test set in the radiomics model and comprehensive model were 0.817 and 0.731 and 0.982 and 0.886, respectively. The calibration curve showed that the two models were in good agreement. The clinical decision curve showed that both methods had good clinical practicability. Conclusion The radiomics model based on ultrasound images has a good predictive effect for the preoperative differential diagnosis of type I and type II epithelial ovarian cancer. The comprehensive model has higher prediction efficiency.
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