Objective To explore the application of high-frequency color Doppler in the diagnosis of infant intussusception and the selection of reduction mode according tO the hemodynamic situations of intussusception intestine tube and blood vessel in mesentery.Methods A total of 377 cases of doubtful intussusception infants wete checked by high-frequency color Doppler.After they had been diagnosed,the hemodynamic situations of intussuscepiton intestine tube and blood vessel in mesentery were carefully observed and the ultra-sound had 3 types and then the hydrostatic enema reduction was chosen as treatment method.Results A total of 263 cases was diagnosed by highfrequency colot Doppler with rate of coincidence of 100%.Among them are 253 successful cases reduced by hydrostatic enema.The successful rate of reduction was 96.2%and the 10 failed cases were changed to be treated bv operation.The intestinal wall of intussusception tube in failure group had serious dropsy without blood flow shown.Conclusions It is accurate that the infant intussusception is diagnosed by high-frequency color Doppler.According to the hemodynamic situations of intussusceptin intestine tube and blood vessel in mesentery,the infant intussusception can be divided into 3 types as follows:type Ⅰ:the blood signal of intestinal tube and wall is up or normal,which shall be reduced by hydrostatic enema;type Ⅱ:the blood signal of intestinal tube and wall is small with high obstruction index,which shall be reduced by hydrostatic enema as possible as it can;type Ⅲ:the intestinal wall has serious dropsy with rather high obstruction index and without blood flow shown,in which the hydrostatic enema redHetion shall bebanned and the operation shall be carried out as soon as possible.

Objective To explore the ultrasonographical characteristics of placental abruption, especially the light placental abruption that was diagnosed by color Doppler ultrasonic combining with enhancement Doppler E-flow imaging, providing diagnosis data for clinical treatment. Methods With color Doppler ultrasonic and enhancement Doppler E-flow imaging, an analysis was made on the ultrasonography and clinical result of 50 patients with heavy placental abruption and 23 patients with light placental abruption. Results The diagnosis and clinical treatment of 50 patients with heavy placental abruption who had been diagnosed by color Doppler ultrasonic combining with enhancement Doppler E-flow imaging were in conformity with the postnatal pathological diagnosis. The coincidence rate in diagnosis was 100%. Of 23 patients with light placental abruption who had been diagnosed by color Doppler ultrasonic combining with enhancement E-flow Doppler imaging, 19 cases' diagnosis and clinical treatment were in accordance with their postnatal pathological diagnosis and the coincidence rate was 83%, 4 cases were misdiagnosis and missed diagnosis. Of 73 patients with placental abruption, 60 cases were carried out caesarean birth and 13 cases performed natural labor. Conclusion The enhancement Doppler E-flow imaging combining with color Doppler ultrasonic can accurately diagnose the heavy placental abruption and also provide a new method for the diagnosis of light placental abruption and perform a dynamic monitoring for the treatment transfer result of it.

Purpose To explore the value of deep learning ultrasound radiomics nomogram in assessing the biological characteristics of invasive metastases in invasive breast cancer.Materials and Methods A retrospective collection of ultrasound imaging data from 180 pathologically confirmed invasive breast cancer between January 2021 to December 2022 in Maoming People's Hospital was conducted,with pathological reports indicating the status of lymph node metastasis(LNM),lymphovascular space invasion(LVSI)or perineural invasion(PNI),according to the LNM/LVSI/PNI status,the three indexes were divided into the training cohort and the verification cohort by 8∶2.Based on Pyradiomics and ResNet50 deep learning extractor,1 316 radiomic features and 2 048 deep learning features were extracted,respectively.The random forest machine learning algorithm was employed to develop evaluation models,and the model scores were calculated.The deep learning radiomics nomograms were developed based on the radiomic and deep learning model scores.The receiver operating characteristic curve was used to assess the performance of the models.The Delong test was applied to analyze the performance differences between different models.Results In the evaluation of LNM,LVSI and PNI status,the area under the curve of all the nomogram in the cohorts demonstrated moderate or above assessment performance(≥0.73),with accuracies all greater than 0.70.Specifically,in the LNM evaluation,the area under the curve of the training cohort was 0.97,the accuracy was 0.93,the sensitivity was 0.88 and the specificity was 0.96.Through the Delong test,the assessment performance of the nomograms was superior to the radiomics models(LNM,Z=2.04,P=0.04;LVSI,Z=2.80,P=0.01;PNI,Z=3.52,P<0.01),and was superior to or similar to the deep learning models(LNM,Z=4.52,P<0.01;LVSI,Z=1.86,P=0.06;PNI,Z=0.31,P=0.76)in the training cohort.Conclusion The deep learning radiomics nomogram can effectively evaluate the biological characteristics of invasion and metastasis in invasive breast cancer.The nomogram improves the assessment performance by integrating the radiomic and deep learning feature information.