Preliminary results of acoustic radiation force impulses (ARFI) ultrasound imaging of solid suspicious breast lesions

Objective： The aim of our study was to make the qualitative and quantitative analysis to breast lesions using acoustic radiation force impulses （ARFI）, and assess the diagnostic value of ARFI for differentiation between benign and malignant solid breast masses, meanwhile evaluate the influences of ARFI with breast imaging reporting and data system （BI-RADS） of suspicious masses. Methods： Seventy-five women with 86 breast lesions underwent conventional breast ultra- sound examination. Then B-mode BI-RADS features and assessments were recorded and standard breast US supplemented by ARFI elastographic examination were repeated. The data were recorded and analyzed as following： area ratio of breast lesion, the shear-wave velocity, the ratio of the shear-wave velocity between lesions and surrounding normal tissues, and according to the elastographic data reconsidered the BI-RADS category, all the results have been correlated with pathological results and make statistical evaluations of ARFI for differentiation between benign and malignant solid breast masses. Meantime our study has correlated the adjusted BI-RADS category of suspicious breast lesions with the pathological results and made assessment. Results： Thirty-eight patients were malignant breast carcinoma （31 invasive ductal carcinoma, 5 intraductal carcinoma in situ, 2 medullary carcinoma, 2 invasive Iobular carcinoma）, 48 patients were benign breast lesions （23 fibroadenoma, 12 benign nodular hyperplasia, 5 phyllodes tumor, 6 adenosis, 2 intraductal papilloma）. Underwent conventional breast ultrasound exam, 42 cases were BI-RADS category 3, 23 cases were BI-RADS category 4. When adding elastographic data, 46 cases were BI-RADS category 3 and 20 cases were BI-RADS category 4. Compared with pathological results showed for both the specificity of BIRADS features and the area under ROC curve has risen. Virtual touch tissue imaging （VTI） and virtual touch tissue quantification （VTQ） data showed the area ratio （AR） between elastographic lesions area and B-mode lesions area, SWV （maximal shear-wave velocity of lesions）, R-SWV （shear-wave velocity ratio between lesions and surrounding normal tissues） in benign breast lesions were lower than those in malignant lesions which has statistical significance and the cut-off point were 1.1,4.65 m/s, 5.18 respectively. Conclusion： The ARFI elastography can provide the reliable qualitative and quantitative analysis about hardness of breast lesions, supply the new BI-RADS category features to suspicious breast masses and serve as an effective diagnostic tool for differentiation between benign and malignant solid masses.

Simply Fine-Tuned Deep Learning-Based Classification for Breast Cancer with Mammograms

A lump growing in the breast may be referred to as a breast mass related to the tumor.However,not all tumors are cancerous or malignant.Breast masses can cause discomfort and pain,depending on the size and texture of the breast.With an appropriate diagnosis,non-cancerous breast masses can be diagnosed earlier to prevent their cultivation from being malignant.With the development of the artificial neural network,the deep discriminative model,such as a convolutional neural network,may evaluate the breast lesion to distinguish benign and malignant cancers frommammogram breast masses images.This work accomplished breastmasses classification relative to benign and malignant cancers using a digital database for screening mammography image datasets.A residual neural network 50(ResNet50)model along with an adaptive gradient algorithm,adaptive moment estimation,and stochastic gradient descent optimizers,as well as data augmentations and fine-tuning methods,were implemented.In addition,a learning rate scheduler and 5-fold cross-validation were applied with 60 training procedures to determine the best models.The results of training accuracy,p-value,test accuracy,area under the curve,sensitivity,precision,F1-score,specificity,and kappa for adaptive gradient algorithm 25%,75%,100%,and stochastic gradient descent 100%fine-tunings indicate that the classifier is feasible for categorizing breast cancer into benign and malignant from the mammographic breast masses images.

Simultaneous Paragonimus infection involving the breast and lung:A case report

BACKGROUND Paragonimiasis is a food-borne parasitic infection caused by lung flukes of the genus Paragonimus. Although the most common site of infection is the pleuropulmonary area, the parasite can also reach other parts of the body on its journey from the intestines to the lungs, ending up in locations such as the brain,abdomen, skin, and subcutaneous tissues. Ectopic paragonimiasis is difficult to diagnose due to the rarity of this disease.CASE SUMMARY Here, we report a rare case of simultaneous breast and pulmonary paragonimiasis in a woman presenting painless breast mass and lung nodule with a history of eating raw trout. To confirm the diagnosis, serologic testing and tissue confirmation of the breast mass were performed. The patient was treated with surgical resection of the mass and praziquantel medication.CONCLUSION Ectopic paragonimiasis is difficult to diagnose due to the rarity of this disease.Thus, thorough history-taking and clinical suspicion of parasitic infection are important.

THE CLINICAL SIGNIFICANCE OF ^(99m)Tc-MIBI BREAST IMAGING IN THE DIAGNOSIS OF EARLY BREAST CANCER

Objective: To find an effective, sensitive, specific and noninvasive diagnostic method of breast cancer. Methods: 109 masses of 102 patients with breast lesions smaller than 2 cm in diameter were divided into three groups to undergo 99mTc-MIBI imaging and compared with the results of pathology examination. 20 cases without breast lesions were selected as control. Abnormal condensation of 99mTc-MIBI in the breast reaching 10% higher than that in the counterpart of the healthy breast was regarded as positive. Results: Of 32 breast cancers, positive imaging appeared in 25. Negative imaging were found in 31 of 38 benign breast lesions. Of 39 occult breast lesions, positive imaging appeared in 6 and 3 of them were breast cancer, 2 of 3 patients with slightly increased 99mTc-MIBI imaging threshold were breast cancer also. No positive imaging was found in the control group. The diagnostic accuracy, sensitivity, specificity, positive predictive value, negative predictive value of 99mTc-MIBI was 88.4%, 89.2%, 88.0%, 75.0% and 95.3%, respectively. Conclusion: 99mTc-MIBI imaging had higher sensitivity and accuracy in the diagnosis of breast cancer and differentiation between benign and malignant breast lesions. It could provide useful information for the diagnosis of clinically suspected breast cancer.

Surrounding electroacupuncture needling for breast mass after acute mastitis

Objective： To observe the clinical efficacy of surrounding electroacupuncture needling for breast mass after acute mastitis.Methods： Thirty patients with breast mass after acute mastitis who conformed to the inclusion criteria were given surrounding electroacupuncture needling. Acupoint selection： 4-8 needles were needled around the mass and at Zusanli（足三里ST 36）,Sanyinjiao（三阴交SP 6）,Fengl6 ng（丰隆 ST 40） and Rugen（乳根 ST 18）. Electroacupuncture was performed at ST 36, SP 6 and ST 40. The above treatment was once a day. Treatment for 7 times was considered as 1 course of treatment, and 3 weeks were free from treatment between courses. Color ultrasound in breast was used to examine the breast mass before the next course of treatment, treatment can be terminated if the mass disappeared, otherwise, treatment should be continued. Three courses at most were needed.Results： After 1-3 courses of treatment, 16 patients were cured, accounting for 53.3%（16/30）; markedly effective： 8 cases, accounting for 26.7%（8/30）; effective： 4 cases, accounting for 13.3%（4/30）; ineffective：2 cases, accounting for 6.7%（2/30）.Conclusion： Surrounding electroacupuncture needling for breast mass after acute mastitis was effective clinically.