Objective: To explore the value of percutaneous ultrasonography combined with transvenous ultrasonography for accurate localization of sentinel lymph nodes and diagnosis of metastatic lymph nodes in patients with brea...Objective: To explore the value of percutaneous ultrasonography combined with transvenous ultrasonography for accurate localization of sentinel lymph nodes and diagnosis of metastatic lymph nodes in patients with breast cancer. Methods: 18 cases of patients with breast cancer attending the Hainan General Hospital from May 2022 to June 2024 who were proposed to undergo axillary lymph node dissection were selected, and the ultrasonographic agent was injected subcutaneously through the areola on the 1st day before the operation, and the marker localization of the manifestation of the Sentinel lymph nodes and draw the lymphatic vessel alignment for drainage on the body surface, and record the manifestation of SLN by conventional ultrasound and dual ultrasonography. At the time of surgery, intraoperative melphalan localization was used to identify the SLN, the difference between the number of ultrasound and melphalan localization was observed, and resection was performed for pathological examination to determine whether they were metastatic or not. Results: There were 8 metastatic lymph nodes and 18 non-metastatic lymph nodes among 31 SLN. A total of 62 SLN were localized by intraoperative melphalan, of which 31 were consistent with ultrasound localization and 31 were not identified by ultrasound. The diagnostic sensitivity of SLN metastasis diagnosed by transcutaneous ultrasonography was 62.50%, specificity was 91.30%, positive predictive value was 71.43%, negative predictive value 87.50%, accuracy was 83.87%, and the AUC was 0.769;the diagnostic sensitivityof transvenous ultrasonography diagnosed was 75.00%, specificity was 75.00%, and the accuracy was 83.87%, 75.00%, specificity 91.30%, positive predictive value 75.00%, negative predictive value 91.30%, accuracy 87.10%, AUC 0.832;dual ultrasonography diagnostic sensitivity 87.50%, specificity 91.30%, positive predictive value 77.78%, negative predictive value 95.45%, accuracy 90.32%. The AUC was 0.894. Conclusion: Transcutaneous ultrasonography combined with transvenous ultrasonography can accurately localize sentinel lymph nodes and improve the sensitivity and accuracy of the diagnosis of metastatic SLN.展开更多
Breast cancer is a malignant tumor with the highest incidence in women. In recent years, the incidence of breast cancer has shown an increasing trend, especially in younger patients, which seriously threatens the life...Breast cancer is a malignant tumor with the highest incidence in women. In recent years, the incidence of breast cancer has shown an increasing trend, especially in younger patients, which seriously threatens the life and health of women. In order to improve the treatment effect of breast cancer, neoadjuvant chemotherapy has become a reliable strategy to cooperate with surgical treatment and improve the prognosis of advanced breast cancer, which is conducive to quickly and accurately curbing the growth of cancer cells, controlling the patients’ condition, reducing their pain, and improving the cure rate of breast cancer patients. This paper analyzes the development history of ultrasound radiomics, explores its application in the evaluation and prediction of neoadjuvant chemotherapy for breast cancer, and clarifies the research results of multimodal ultrasound radiomics in the analysis of high-order characteristics of breast cancer tumors and the evaluation of tumor heterogeneity, so as to provide references for the clinical treatment of breast cancer.展开更多
BACKGROUND Breast non-mass-like lesions(NMLs)account for 9.2%of all breast lesions.The specificity of the ultrasound diagnosis of NMLs is low,and it cannot be objectively classified according to the 5th Edition of the...BACKGROUND Breast non-mass-like lesions(NMLs)account for 9.2%of all breast lesions.The specificity of the ultrasound diagnosis of NMLs is low,and it cannot be objectively classified according to the 5th Edition of the Breast Imaging Reporting and Data System(BI-RADS).Contrast-enhanced ultrasound(CEUS)can help to differentiate and classify breast lesions but there are few studies on NMLs alone.AIM To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography(US),color Doppler flow imaging(CDFI)and CEUS,and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.METHODS A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019.All lesions were examined by US,CDFI and CEUS,and their features from those examinations were analyzed.With pathology as the gold standard,binary logic regression was used to analyze the independent risk factors for malignant breast NMLs,and a regression equation was established to calculate the efficiency of combined diagnosis.Based on the regression equation,the combined diagnostic efficiency of US combined with CEUS(US+CEUS)was determined.The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS,and the diagnostic efficiency of CEUS combined with BI-RADS(CEUS+BI-RADS)was calculated based on the results.ROC curves were drawn to compare the diagnostic values of the three methods,including US,US+CEUS,and CEUS+BI-RADS,for benign and malignant NMLs.RESULTS Microcalcification,enhancement time,enhancement intensity,lesion scope,and peripheral blood vessels were significantly different between benign and malignant NMLs.Among these features,microcalcification,higher enhancement,and lesion scope were identified as independent risk factors for malignant breast NMLs.When US,US+CEUS,and CEUS+BI-RADS were used to identify the benign and malignant breast NMLs,their sensitivity rates were 82.6%,91.3%,and 87.0%,respectively;their specificity rates were 71.4%,89.2%,and 92.9%,respectively;their positive predictive values were 70.4%,87.5%,and 90.9%,respectively;their negative predictive values were 83.3%,92.6%,and 89.7%,respectively;their accuracy rates were 76.5%,90.2%,and 90.2%,respectively;and their corresponding areas under ROC curves were 0.752,0.877 and 0.903,respectively.Z tests showed that the area under the ROC curve of US was statistically smaller than that of US+CEUS and CEUS+BI-RADS,and there was no statistical difference between US+CEUS and CEUS+BI-RADS.CONCLUSION US combined with CEUS can improve diagnostic efficiency for NMLs.The adjustment of the BI-RADS classification according to the features of contrastenhanced US of NMLs enables the diagnostic results to be simple and intuitive,facilitates the management of NMLs,and effectively reduces the incidence of unnecessary biopsy.展开更多
Objective The aim of our study was to analyze the characters of breast pure mucinous carcinomas on highfrequency ultrasonography with virtual touch tissue quantification (VTQ).
Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives train...Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives training feature samples that make closer isolation toward the infection part.Hence,it is expensive due to a metaheuristic search of features occupying the global region of interest(ROI)structures of input images.Thus,it may lead to the high computational complexity of the pre-trained DNN-based CABTD method.This paper proposes a novel ensemble pretrained DNN-based CABTD method using global-and local-ROI-structures of B-mode ultrasound images.It conveys the additional consideration of a local-ROI-structures for further enhan-cing the pretrained DNN-based CABTD method’s breast tumor diagnostic performance without degrading its visual quality.The features are extracted at various depths(18,50,and 101)from the global and local ROI structures and feed to support vector machine for better classification.From the experimental results,it has been observed that the combined local and global ROI structure of small depth residual network ResNet18(0.8 in%)has produced significant improve-ment in pixel ratio as compared to ResNet50(0.5 in%)and ResNet101(0.3 in%),respectively.Subsequently,the pretrained DNN-based CABTD methods have been tested by influencing local and global ROI structures to diagnose two specific breast tumors(Benign and Malignant)and improve the diagnostic accuracy(86%)compared to Dense Net,Alex Net,VGG Net,and Google Net.Moreover,it reduces the computational complexity due to the small depth residual network ResNet18,respectively.展开更多
文摘Objective: To explore the value of percutaneous ultrasonography combined with transvenous ultrasonography for accurate localization of sentinel lymph nodes and diagnosis of metastatic lymph nodes in patients with breast cancer. Methods: 18 cases of patients with breast cancer attending the Hainan General Hospital from May 2022 to June 2024 who were proposed to undergo axillary lymph node dissection were selected, and the ultrasonographic agent was injected subcutaneously through the areola on the 1st day before the operation, and the marker localization of the manifestation of the Sentinel lymph nodes and draw the lymphatic vessel alignment for drainage on the body surface, and record the manifestation of SLN by conventional ultrasound and dual ultrasonography. At the time of surgery, intraoperative melphalan localization was used to identify the SLN, the difference between the number of ultrasound and melphalan localization was observed, and resection was performed for pathological examination to determine whether they were metastatic or not. Results: There were 8 metastatic lymph nodes and 18 non-metastatic lymph nodes among 31 SLN. A total of 62 SLN were localized by intraoperative melphalan, of which 31 were consistent with ultrasound localization and 31 were not identified by ultrasound. The diagnostic sensitivity of SLN metastasis diagnosed by transcutaneous ultrasonography was 62.50%, specificity was 91.30%, positive predictive value was 71.43%, negative predictive value 87.50%, accuracy was 83.87%, and the AUC was 0.769;the diagnostic sensitivityof transvenous ultrasonography diagnosed was 75.00%, specificity was 75.00%, and the accuracy was 83.87%, 75.00%, specificity 91.30%, positive predictive value 75.00%, negative predictive value 91.30%, accuracy 87.10%, AUC 0.832;dual ultrasonography diagnostic sensitivity 87.50%, specificity 91.30%, positive predictive value 77.78%, negative predictive value 95.45%, accuracy 90.32%. The AUC was 0.894. Conclusion: Transcutaneous ultrasonography combined with transvenous ultrasonography can accurately localize sentinel lymph nodes and improve the sensitivity and accuracy of the diagnosis of metastatic SLN.
文摘Breast cancer is a malignant tumor with the highest incidence in women. In recent years, the incidence of breast cancer has shown an increasing trend, especially in younger patients, which seriously threatens the life and health of women. In order to improve the treatment effect of breast cancer, neoadjuvant chemotherapy has become a reliable strategy to cooperate with surgical treatment and improve the prognosis of advanced breast cancer, which is conducive to quickly and accurately curbing the growth of cancer cells, controlling the patients’ condition, reducing their pain, and improving the cure rate of breast cancer patients. This paper analyzes the development history of ultrasound radiomics, explores its application in the evaluation and prediction of neoadjuvant chemotherapy for breast cancer, and clarifies the research results of multimodal ultrasound radiomics in the analysis of high-order characteristics of breast cancer tumors and the evaluation of tumor heterogeneity, so as to provide references for the clinical treatment of breast cancer.
文摘BACKGROUND Breast non-mass-like lesions(NMLs)account for 9.2%of all breast lesions.The specificity of the ultrasound diagnosis of NMLs is low,and it cannot be objectively classified according to the 5th Edition of the Breast Imaging Reporting and Data System(BI-RADS).Contrast-enhanced ultrasound(CEUS)can help to differentiate and classify breast lesions but there are few studies on NMLs alone.AIM To analyze the features of benign and malignant breast NMLs in grayscale ultrasonography(US),color Doppler flow imaging(CDFI)and CEUS,and to explore the efficacy of the combined diagnosis of NMLs and the effect of CEUS on the BI-RADS classification of NMLs.METHODS A total of 51 breast NMLs verified by pathology were analyzed in our hospital from January 2017 to April 2019.All lesions were examined by US,CDFI and CEUS,and their features from those examinations were analyzed.With pathology as the gold standard,binary logic regression was used to analyze the independent risk factors for malignant breast NMLs,and a regression equation was established to calculate the efficiency of combined diagnosis.Based on the regression equation,the combined diagnostic efficiency of US combined with CEUS(US+CEUS)was determined.The initial BI-RADS-US classification of NMLs was adjusted according to the independent risk factors identified by CEUS,and the diagnostic efficiency of CEUS combined with BI-RADS(CEUS+BI-RADS)was calculated based on the results.ROC curves were drawn to compare the diagnostic values of the three methods,including US,US+CEUS,and CEUS+BI-RADS,for benign and malignant NMLs.RESULTS Microcalcification,enhancement time,enhancement intensity,lesion scope,and peripheral blood vessels were significantly different between benign and malignant NMLs.Among these features,microcalcification,higher enhancement,and lesion scope were identified as independent risk factors for malignant breast NMLs.When US,US+CEUS,and CEUS+BI-RADS were used to identify the benign and malignant breast NMLs,their sensitivity rates were 82.6%,91.3%,and 87.0%,respectively;their specificity rates were 71.4%,89.2%,and 92.9%,respectively;their positive predictive values were 70.4%,87.5%,and 90.9%,respectively;their negative predictive values were 83.3%,92.6%,and 89.7%,respectively;their accuracy rates were 76.5%,90.2%,and 90.2%,respectively;and their corresponding areas under ROC curves were 0.752,0.877 and 0.903,respectively.Z tests showed that the area under the ROC curve of US was statistically smaller than that of US+CEUS and CEUS+BI-RADS,and there was no statistical difference between US+CEUS and CEUS+BI-RADS.CONCLUSION US combined with CEUS can improve diagnostic efficiency for NMLs.The adjustment of the BI-RADS classification according to the features of contrastenhanced US of NMLs enables the diagnostic results to be simple and intuitive,facilitates the management of NMLs,and effectively reduces the incidence of unnecessary biopsy.
文摘Objective The aim of our study was to analyze the characters of breast pure mucinous carcinomas on highfrequency ultrasonography with virtual touch tissue quantification (VTQ).
文摘Deep neural network(DNN)based computer-aided breast tumor diagnosis(CABTD)method plays a vital role in the early detection and diagnosis of breast tumors.However,a Brightness mode(B-mode)ultrasound image derives training feature samples that make closer isolation toward the infection part.Hence,it is expensive due to a metaheuristic search of features occupying the global region of interest(ROI)structures of input images.Thus,it may lead to the high computational complexity of the pre-trained DNN-based CABTD method.This paper proposes a novel ensemble pretrained DNN-based CABTD method using global-and local-ROI-structures of B-mode ultrasound images.It conveys the additional consideration of a local-ROI-structures for further enhan-cing the pretrained DNN-based CABTD method’s breast tumor diagnostic performance without degrading its visual quality.The features are extracted at various depths(18,50,and 101)from the global and local ROI structures and feed to support vector machine for better classification.From the experimental results,it has been observed that the combined local and global ROI structure of small depth residual network ResNet18(0.8 in%)has produced significant improve-ment in pixel ratio as compared to ResNet50(0.5 in%)and ResNet101(0.3 in%),respectively.Subsequently,the pretrained DNN-based CABTD methods have been tested by influencing local and global ROI structures to diagnose two specific breast tumors(Benign and Malignant)and improve the diagnostic accuracy(86%)compared to Dense Net,Alex Net,VGG Net,and Google Net.Moreover,it reduces the computational complexity due to the small depth residual network ResNet18,respectively.
