Cost analysis of radical resection of malignant breast tumors under the China Healthcare Security Diagnosis Related Groups payment system

BACKGROUND Breast cancer is one of the most common malignant tumors in women worldwide and poses a severe threat to their health.Therefore,this study examined patients who underwent breast cancer surgery,analyzed hospitalization costs and structure,and explored the impact of China Healthcare Security Diagnosis Related Groups(CHS-DRG)management on patient costs.It aimed to provide medical institutions with ways to reduce costs,optimize cost structures,reduce patient burden,and improve service efficiency.AIM To study the CHS-DRG payment system’s impact on breast cancer surgery costs.METHODS Using the CHS-DRG(version 1.1)grouping criteria,4073 patients,who underwent the radical resection of breast malignant tumors from January to December 2023,were included in the JA29 group;1028 patients were part of the CHS-DRG payment system,unlike the rest.Through an independent sample t-test,the length of hospital stay as well as total hospitalization,medicine and consumables,medical,nursing,medical technology,and management expenses were compared.Pearson’s correlation coefficient was used to test the cost correlation.RESULTS In terms of hospitalization expenses,patients in the CHS-DRG payment group had lower medical,nursing,and management expenses than those in the diagnosis-related group(DRG)non-payment group.For patients in the DRG payment group,the factors affecting the total hospitalization cost,in descending order of relevance,were medicine and consumable costs,consumable costs,medicine costs,medical costs,medical technology costs,management costs,nursing costs,and length of hospital stay.For patients in the DRG nonpayment group,the factors affecting the total hospitalization expenses in descending order of relevance were medicines and consumable expenses,consumable expenses,medical technology expenses,the cost of medicines,medical expenses,nursing expenses,length of hospital stay,and management expenses.CONCLUSION The CHS-DRG system can help control and reduce unnecessary medical expenses by controlling medicine costs,medical consumable costs,and the length of hospital stay while ensuring medical safety.

Proposed Framework for Detection of Breast Tumors

Computer vision is one of the significant trends in computer science.It plays as a vital role in many applications,especially in the medical field.Early detection and segmentation of different tumors is a big challenge in the medical world.The proposed framework uses ultrasound images from Kaggle,applying five diverse models to denoise the images,using the best possible noise-free image as input to the U-Net model for segmentation of the tumor,and then using the Convolution Neural Network(CNN)model to classify whether the tumor is benign,malignant,or normal.The main challenge faced by the framework in the segmentation is the speckle noise.It’s is a multiplicative and negative issue in breast ultrasound imaging,because of this noise,the image resolution and contrast become reduced,which affects the diagnostic value of this imaging modality.As result,speckle noise reduction is very vital for the segmentation process.The framework uses five models such as Generative Adversarial Denoising Network(DGAN-Net),Denoising U-Shaped Net(D-U-NET),Batch Renormalization U-Net(Br-UNET),Generative Adversarial Network(GAN),and Nonlocal Neutrosophic ofWiener Filtering(NLNWF)for reducing the speckle noise from the breast ultrasound images then choose the best image according to peak signal to noise ratio(PSNR)for each level of speckle-noise.The five used methods have been compared with classical filters such as Bilateral,Frost,Kuan,and Lee and they proved their efficiency according to PSNR in different levels of noise.The five diverse models are achieved PSNR results for speckle noise at level(0.1,0.25,0.5,0.75),(33.354,29.415,27.218,24.115),(31.424,28.353,27.246,24.244),(32.243,28.42,27.744,24.893),(31.234,28.212,26.983,23.234)and(33.013,29.491,28.556,25.011)forDGAN,Br-U-NET,D-U-NET,GANand NLNWF respectively.According to the value of PSNR and level of speckle noise,the best image passed for segmentation using U-Net and classification usingCNNto detect tumor type.The experiments proved the quality ofU-Net and CNN in segmentation and classification respectively,since they achieved 95.11 and 95.13 in segmentation and 95.55 and 95.67 in classification as dice score and accuracy respectively.

Clinical utility of proton magnetic resonance spectroscopy in the diagnosis of breast tumors

Proton magnetic resonance spectroscopy (1H MRS) can provide specific biochemical information within breast lesions and the elevated composite choline concentration as a useful diagnostic tool has been used to distinguish malignant from benign breast lesions, early evaluate response to therapy and predict prognosis. However, several obstacles including poor spatial resolution, low signal-to-noise ratio (SNR), long acquisition time and the difficulty of "extra" lipid suppression may have a negative impact on the routine application of in vivo 1H MRS for human breast cancer. At present, optimization H MRS methodology for breast studies has been performed.

Application of T2~*-weighted first-pass perfusion imaging in the diagnosis of breast tumors

Objective:To study the diagnostic value of T2*-weighted first-pass perfusion imaging in breast tumors.Methods: We analyzed the magnetic resonance imaging(MRI)information along with the pathological and immunohistochemistry re- sults.Magnetic resonance imaging was performed in 28 patients with breast tumor.The time to signal intensity curves were generated according to the T2*-weighted first-pass perfusion imaging.The curve’s maximal signal intensity drop rate and maximal signal intensity decrease time were analyzed and compared with the pathological diagnoses after surgery.Results: Malignant breast lesions showed higher maximal signal intensity drop rate(44.69%±17.07 vs.17.22%±7.49,P<0.001) than benign lesions,but there was no significant difference of maximal signal decrease time between those two lesions(23.94 s±4.92 vs.20.02 s±6.83,P>0.05).Conclusion:The T2*-weighted first-pass perfusion imaging has enough sensitivity and specificity in breast tumor diagnosis.

Two Stages Segmentation Algorithm of Breast Tumor in DCE-MRI Based on Multi-Scale Feature and Boundary Attention Mechanism

Nuclearmagnetic resonance imaging of breasts often presents complex backgrounds.Breast tumors exhibit varying sizes,uneven intensity,and indistinct boundaries.These characteristics can lead to challenges such as low accuracy and incorrect segmentation during tumor segmentation.Thus,we propose a two-stage breast tumor segmentation method leveraging multi-scale features and boundary attention mechanisms.Initially,the breast region of interest is extracted to isolate the breast area from surrounding tissues and organs.Subsequently,we devise a fusion network incorporatingmulti-scale features and boundary attentionmechanisms for breast tumor segmentation.We incorporate multi-scale parallel dilated convolution modules into the network,enhancing its capability to segment tumors of various sizes through multi-scale convolution and novel fusion techniques.Additionally,attention and boundary detection modules are included to augment the network’s capacity to locate tumors by capturing nonlocal dependencies in both spatial and channel domains.Furthermore,a hybrid loss function with boundary weight is employed to address sample class imbalance issues and enhance the network’s boundary maintenance capability through additional loss.Themethod was evaluated using breast data from 207 patients at RuijinHospital,resulting in a 6.64%increase in Dice similarity coefficient compared to the benchmarkU-Net.Experimental results demonstrate the superiority of the method over other segmentation techniques,with fewer model parameters.

Value of ultrasound elastography in detecting small breast tumors

Background Detecting small breast tumors is difficult for conventional ultrasound. The goal of this study was to assess the value of ultrasound elastography in characterizing small breast tumors and to compare its sensitivity, specificity and accuracy with conventional ultrasound. Methods A total of 308 breast tumors less than 2 cm in size from 283 in-hospital patients examined with both conventional ultrasound and ultrasound elastography were retrospectively analyzed. The results were compared to surgical pathology. Results There were 104 malignant and 204 benign lesions. The sensitivities of sonography and sonoelastography were similar （P 〈0.05）, and the sensitivity of the two modalities combined improved remarkably to 97.1%. The mean elastic score of malignant and benign tumors less than 2 cm were 3.76±1.01 and 1.73±0.99, respectively （P 〈0.05）, and the mean elastic score of the false-negative lesions on conventional ultrasound was 3.61±1.14. Conclusions Ultrasound elastography in combination with conventional ultrasound can improve the sensitivity for detecting small breast tumors. It is also valuable in detecting small malignant tumors which are difficult to diagnose with conventional ultrasound. Ultrasound elastography can be a useful adjunct to conventional ultrasound in diagnosing small breast tumors.

A cadaveric breast cancer tissue phantom for phase-contrast X-ray imaging applications

Background:As mammography X-ray imaging technologies advance and provide elevated contrast in soft tissues,a need has developed for reliable imaging phantoms for use in system design and component calibration.In advanced imaging modalities such as refraction-based methods,it is critical that developed phantoms capture the biological details seen in clinical precancerous and cancerous cases while minimizing artifacts that may be caused due to phantom production.This work presents the fabrication of a breast tissue imaging phantom from cadaveric breast tissue suitable for use in both transmission and refraction-enhanced imaging systems.Methods:Human cancer cell tumors were grown orthotopically in nude athymic mice and implanted into the fixed tissue while maintaining the native tumor/adipose tissue interface.Results:The resulting human–murine tissue hybrid phantom was mounted on a clear acrylic housing for absorption and refraction X-ray imaging.Digital breast tomosynthesis was also performed.Conclusion:Both attenuation-based imaging and refraction-based imaging of the phantom are presented to confirm the suitability of this phantom's use in both imaging modalities.

Structurally defined tandem-responsive nanoassemblies composed of dipeptide-based photosensitive derivatives and hypoxia-activated camptothecin prodrugs against primary and metastatic breast tumors

Substantial progress in the use of chemo-photodynamic nano-drug delivery systems(nanoDDS) for the treatment of the malignant breast cancer has been achieved. The inability to customize precise nanostructures, however, has limited the therapeutic efficacy of the prepared nano-DDS to date. Here,we report a structurally defined tandem-responsive chemo-photosensitive co-nanoassembly to eliminate primary breast tumor and prevent lung metastasis. This both-in-one co-nanoassembly is prepared by assembling a biocompatible photosensitive derivative(pheophorbide-diphenylalanine peptide, PPADA) with a hypoxia-activated camptothecin(CPT) prodrug [(4-nitrophenyl) formate camptothecin, NCPT]. According to computational simulations, the co-assembly nanostructure is not the classical core-shell type, but consists of many small microphase regions. Upon exposure to a 660 nm laser,PPA-DA induce high levels of ROS production to effectively achieve the apoptosis of normoxic cancer cells. Subsequently, the hypoxia-activated N-CPT and CPT spatially penetrate deep into the hypoxic region of the tumor and suppress hypoxia-induced tumor metastasis. Benefiting from the rational design of the chemo-photodynamic both-in-one nano-DDS, these nanomedicines exhibit a promising potential in the inhibition of difficult-to-treat breast tumor metastasis in patients with breast cancer.

THE CORRELATIONS OF RETINOIC ACID RECEPTOR-α AND ESTROGEN RECEPTOR EXPRESSION IN HUMAN BREAST CANCER CELL LINES AND TUMORS

Retinoic acid receptor-α (RAR α) plays a major role in the growth inhibitory effect of retinoic acid on human breast cancer cells, may be it could serve as an indicator to guide the treatment and prevent of breast cancer with retinoic acid in clinic. All previous researchs were based on observing the changes of RAR α mRAN expression. In this study, the expression of RAR α in human breast cell lines was studied by Northern Blot, Western Blot and Immunohistochemistry in mRNA level and protein level. Results showed that RAR α protein expression was correlated with RAR α mRNA expression. RAR α mRNA ex- pression was higher in estrogen receptor (ER)-positive human breast cancer cell lines than in ER-negative ones. So was RAR a protein expression. Both RAR α mRNA amd RAR α protein expression were associ- ated with ER status. The expression of RAR α and the relationship between RAR a and ER status were al- so determined by immunohistochemistry in 58 human primary breast cancer tumors. 37 (63. 8% ) tumors were ER-positive and of these 28 (75. 7% ) were also RAR α -positive. The coexpression of ER and RAR a was statistically significant (P＜0. 01, by X^2 contingency analysis). It was reported that RAR α expres- sion in cultured breast cancer cells was regulated by estrogen acting via the ER. Our study demonstrated that RAR α expression may be modulated in breast cancer in vivo by estrogen via ER.

A RETROSPECTIVE ANALYSIS OF SURGICAL TREATMENT FOR BREAST MALIGNANT TUMORS

Objective: To review the evolution of the current surgical treatment for breast malignant tumors over the past twenty years in the First Hospital of Jilin University (the former Bethune University of Medical Sciences). Methods: 1195 eligible patients with primary breast malignant tumor diagnosed and surgically treated at the First Teaching Hospital from January 1980 and December 2000 were retrospectively analyzed. Results: The peak frequency was in 40–49 years of age (40.00%), the age of the patients with breast malignant tumors trends to become young. The most common pTNM classification was Stage II. The most common histological type was infiltrating ductal carcinoma (398 patients, 33.31%), and simple carcinoma (279 patients, 23.53%). Modified radical mastectomy was the most common operation procedure performed (779 patients, 65.19%), and was increasingly used while radical mastectomy was adopted decreasingly in recent decade. Conclusion: The variation of operation procedures performed on patients with breast malignant tumors reflected the advance of our understanding of the biology of cancer and the progression of new treatment principles.

Pre-Trained Deep Neural Network-Based Computer-Aided Breast Tumor Diagnosis Using ROI Structures

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.

Breast Cancer Hyperthermia Treatment Based on Slotted Patch Antenna at 2.45 GHz

The present work proposed a simple model for breast cancer hyperthermia treatment at 2.45 GHz. The proposed model involves nine-element antennas alongside a numerical breast comprising multiple tumors. Using a coupled EM-Thermal simulation in the CST suite, the simulated results for a single antenna showed a reflection coefficient (S11) better than -47 dB and demonstrated a bandwidth of 78 MHz. The specific absorption rate (SAR) as a function of input powers was examined inside the breast tissues, where it exhibited a promising performance higher than 3 W/kg at the tumor volume when the applied power was at a reasonable level of 1.5 W whereas it was well attained under the recommend IEEE level of 1.6 W/kg through the surrounded health tissues. Taking into consideration nine-element antennas covering the breast containing two different located tumors, the maximum temperature as a function of treatment time was presented at which a resulting temperature of 43°C was obtainable within 10 minutes, favored for hyperthermia purposes. Considering the maximum power level of 1.5 W, the potential use of applying three-element antennas, simultaneously with 0.5 W, could be achieved.

Dermatofibrosarcoma Protuberans—An Atypical Breast Tumor

A 49-year-old woman was referred to the Department of Plastic and Breast Surgery under suspicion of breast cancer after a mammogram revealed a self-discovered tumor in the lower part of her left breast. Clinical examination, mammography, and histopathological examination revealed that the original tumor in the left breast was benign, and an incidental malignant tumor, a dermatofibrosarcoma protuberans (DFSP), was found in the contralateral breast. DFSP is a rare and highly malignant entity that is often silent and difficult to diagnose, making a biopsy essential. Surgical treatment must be aggressive due to the high risk of recurrence, which constitutes a technical challenge. The patient underwent surgery using an oncoplastic approach with a volume-reducing technique to achieve the best possible therapeutic and aesthetic results. Therapeutic breast reduction was performed on the right breast and the tumor was removed within the resected tissue. A contralateral symmetrizing mammoplasty was also performed simultaneously. The patient was discharged without major complications, and no recurrence of the tumor was seen during the 30-month follow-up period. The surgical approach included alternative solutions in addition to conventional lumpectomy or mastectomy. A multidisciplinary, open-minded, and creative approach resulted in a satisfying outcome for this patient.

Is chronic hepatitis C virus infection a risk factor for breast cancer?

AIM:To evaluate the prevalence of breast tumors in adult females with chronic hepatitis C virus(HCV) infection.METHODS:Prospective,single-center study,based on female outpatients consulting in a liver unit,for 1 year.The study group included females with present and/or past history of chronic infection by HCV.Patients with spontaneous recovery were excluded.Chronic hepatitis had been proved by liver biopsy in the majority of cases and/or biological markers of inflammation and fibrosis.The control group included female patients with other well documented chronic liver diseases:chronic hepatitis B,alcoholic liver disease,autoimmune hepatitis,hemochromatosis,non alcoholic liver disease,chronic cholangitis.Participating patients were prospectively questioned during consultation about past breast history and follow-up by mammography.RESULTS:Breast carcinoma was recorded in 17/294 patients with HCV infection(5.8%,95% CI:3.1-8.4) vs 5/107 control patients(4.7%,95% CI:0.67-8.67).Benign tumors of the breast(mastosis,nodules,cysts) were recorded in 75/294 patients with HCV infection(25.5%,95% CI:20.5-30.5) vs 21/107(19.6%,95% CI:12.1-27.1) in the control group.No lesion was noted in 202 patients with HCV(68.7%,95% CI:63.4-74) vs 81 control patients(75.7%,95% CI:67.6-83.8).Despite a trend to an increased prevalence in the group with HCV infection,the difference was not significant compared to the control group(P=NS).In patients over 40 years,the results were,respectively,as follows:breast cancer associated with HCV:17/266 patients(6.3%,95% CI:3.4-9.3) vs 5/95 patients(5.2%,95% CI:0.7-9.7) in the control group;benign breast tumors:72/266 patients with HCV infection(27%,95% CI:21.7-32.4) vs 18/95 patients(18.9%,95% CI:11-26.8) in the control group;no breast lesion 177/266(66.5%,95% CI:60.9-72.2) in patients with HCV infection vs 72/95(75.7%,95% CI:67.1-84.4) in the control group.The differences were not significant(P=NS).CONCLUSION:These results suggest that chronic HCV infection is not a strong promoter of breast carcinoma in adult females of any age.

Functional Imaging of Breast Tissue and Clinical Application

A novel approach to image hemoglobin concentration（△Dhb） and oxygen saturation （△Doxy） of breast tissue is presented. The scenograph of dual-wavelength （760 and 850 nm） near infrared lights through breast tissue is acquired by high sensitive charge coupled device （CCD） camera. The evaluation criterion of the difference of △Dhh and △Doxy between detected and referenced breast tissue can be obtained by a calculation formula without complicate caculation. This approach is applied to clinic detection in breast tissue. The ongoing clinical experiments indicate that malignant tumor usually exhibits characterize of ＂higher △Dhb and lower △Doxy＂, while benign lesion often shows ＂lower △Dhb and higher △Doxy＂ or other characters. So it is useful to assist the diagnosis of breast disease.

Evaluation of internal and shell stiffness in the differential diagnosis of breast non-mass lesions by shear wave elastography

BACKGROUND The diagnostic specificity of conventional ultrasound for breast non-mass lesions(NMLs)is low at approximately 21%-43%.Shear wave elastography(SWE)can distinguish benign from malignant lesions by evaluating the internal and peripheral stiffness.SWE has good reproducibility and high diagnostic efficacy.However,there are very few independent studies on the diagnostic value of SWE in breast NMLs.AIM To determine the value of SWE in the differential diagnosis of breast NMLs.METHODS This study enrolled a total of 118 patients with breast NMLs who underwent SWE examinations in the Beijing Shijitan Hospital Affiliated to Capital Medical University and The Second Hospital of Shandong University from January 2019 to January 2020.The internal elastic parameters of the lesions were recorded,including maximum(Emax),mean(Emean)and minimum elastic values and the standard deviation.The following peripheral parameters were noted:Presence of a“stiff rim”sign;Emax,and Emean elasticity values within 1 mm,1.5 mm,2 mm,2.5 mm and 3 mm from the edge of NMLs.The receiver operating characteristic curve of each parameter was drawn,and the areas under the curve were calculated.RESULTS Emax,Emean and elastic values,and the standard deviation of the internal elastic values in malignant NMLs were significantly higher than those in benign NMLs(P<0.05).The percentage with the“stiff rim”sign in malignant NMLs was significantly higher than that in the benign group(P<0.05),and Emax and Emean at the shell of 1 mm,1.5 mm,2 mm,2.5 mm and 3 mm in the malignant group were all higher than those in the benign group(P<0.05).Of the surrounding elasticity values,Emax of the shell at 2.5 mm in malignant NMLs had maximum areas under the curve of 0.900,and the corresponding sensitivity and specificity were 94.57%and 85.86%,respectively.CONCLUSION The“stiff rim”sign and multiple quantitative elastic values within and around the lesion had good diagnostic performance in the differential diagnosis of breast NMLs.Emax in peripheral tissue had better diagnostic efficiency than other parameters.

Breast non-mass-like lesions on contrast-enhanced ultrasonography: Feature analysis, breast image reporting and data system classification assessment

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.

Diagnostic value of artificial intelligence automatic detection systems for breast BI-RADS 4 nodules

BACKGROUND The incidence rate of breast cancer has exceeded that of lung cancer,and it has become the most malignant type of cancer in the world.BI-RADS 4 breast nodules have a wide range of malignant risks and are associated with challenging clinical decision-making.AIM To explore the diagnostic value of artificial intelligence(AI)automatic detection systems for BI-RADS 4 breast nodules and to assess whether conventional ultrasound BI-RADS classification with AI automatic detection systems can reduce the probability of BI-RADS 4 biopsy.METHODS A total of 107 BI-RADS breast nodules confirmed by pathology were selected between June 2019 and July 2020 at Hwa Mei Hospital,University of Chinese Academy of Sciences.These nodules were classified by ultrasound doctors and the AI-SONIC breast system.The diagnostic values of conventional ultrasound,the AI automatic detection system,conventional ultrasound combined with the AI automatic detection system and adjusted BI-RADS classification diagnosis were statistically analyzed.RESULTS Among the 107 breast nodules,61 were benign(57.01%),and 46 were malignant(42.99%).The pathology results were considered the gold standard;furthermore,the sensitivity,specificity,accuracy,Youden index,and positive and negative predictive values were 84.78%,67.21%,74.77%,0.5199,66.10%and 85.42%for conventional ultrasound BI-RADS classification diagnosis,86.96%,75.41%,80.37%,0.6237,72.73%,and 88.46%for automatic AI detection,80.43%,90.16%,85.98%,0.7059,86.05%,and 85.94%for conventional ultrasound BI-RADS classification with automatic AI detection and 93.48%,67.21%,78.50%,0.6069,68.25%,and 93.18%for adjusted BI-RADS classification,respectively.The biopsy rate,cancer detection rate and malignancy risk were 100%,42.99%and 0%and 67.29%,61.11%,and 1.87%before and after BI-RADS adjustment,respectively.CONCLUSION Automatic AI detection has high accuracy in determining benign and malignant BI-RADS 4 breast nodules.Conventional ultrasound BI-RADS classification combined with AI automatic detection can reduce the biopsy rate of BI-RADS 4 breast nodules.

miR-21 Targets Fas Ligand-mediated Apoptosis in Breast Cancer Cell Line MCF-7

Over-expression of Fas ligand （FasL） on tumor cell surface can induce the apoptosis of spe- cific activated tumor infiltrating lymphocytes （TILs） via the Fas/FasL pathway, leading to the formation of a site of immune privilege surrounding the tumor mass for escaping immune surveillance and pro- moting tumor proliferation, invasion and metastasis. The blocking effect of miR-21 on FasL-mediated apoptosis in breast cancers was investigated in this study. The expression levels of miR-21 and FasL in human breast carcinoma cell lines were detected by using RT-PCR and Western blotting. FasL as a tar- get gene of miR-21 was identified by Luciferase assay. The apoptosis of Jurkat T lymphocytes induced by MCF-7 cells was determined by flow cytometry. It was found that in four human breast cancer cell lines, FasL expression level in MCF-7 cells was the highest, while miR-21 was down-regulated the most notably. After miR-21 expression in MCF-7 cells was up-regulated, FasL was identified as a target gene of miR-21. When the effector/target （E/T） ratio of MCF-7 cells and Jurkat cells was 10：1, 5：1 and 1：1, the inhibitory rate of apoptosis of Jurkat T lymphocytes induced by MCF-7 cells was 95.81%, 93.16% and 91.94%, respectively. It is suggested that in breast cancers miR-21 expression is negatively associ- ated with FasL expression, and FasL is a target gene of miR-21, miR-21 targeting and regulating FasL-mediated apoptosis will bring us the possibility of a new tumor immunotherapy via breaking tu- mor immune privilege.

Adenomyoepithelioma of the breast with malignant transformation and repeated local recurrence:A case report

BACKGROUND Adenomyoepithelioma(AME)of the breast is a rare type of benign breast tumor.Many AMEs show benign behavior,but reports of the malignant type are rare.We present the case of a patient with AME with repeated local recurrences and further malignant transformation.CASE SUMMARY A 53-year-old woman visited our hospital with a 16-mm palpable mass in the right breast.A core needle biopsy was performed.The pathological diagnosis was AME.Lumpectomy with a safety margin was performed without axillary lymph node dissection(ALND).Two years later,local recurrence developed,and the patient again underwent lumpectomy with a safety margin.The pathology showed malignant AME,and the margin was negative.Eight months later,local recurrence developed again in the same location,and a total mastectomy was performed without ALND.The pathological diagnosis was malignant AME.The patient was disease-free for three years posttreatment.CONCLUSION The treatment of AME requires caution,as it may exhibit repeated recurrences after local excision as well as malignant transformation.