Diagnostic value of CEM and MRI in differentiating benign and malignant breast lesions based on the 2013 BI-RADS lexicon and the supplement on CEM / 中华放射学杂志

Objective:To explore the diagnostic value of contrast-enhanced mammography (CEM) and MRI in differentiating benign and malignant breast lesions based on the 2013 breast imaging reporting and data system (BI-RADS) lexicon and the supplement on CEM.Methods:The clinical and imaging data of 83 patients with breast lesions from March 2019 to April 2022 in the Third Affiliated Hospital of Soochow University were retrospectively analyzed. Totally 100 breast lesions from 83 female patients aged 28 to 78 (49±14) years, were divided into benign lesions (50 lesions) and malignant lesions (50 lesions) according to the pathological results. The t-test, χ 2 test and Fisher′s exact test were used to compare the differences of clinical and imaging features between benign and malignant lesions, and these imaging features which had statistical differences were established CEM and MRI models by multivariate logistic regression analysis respectively. The receiver operating characteristic curves and the area under the curve (AUC) were used to assess the diagnostic efficacy of two models in differentiating benign and malignant breast lesions. Using the DeLong test compared the AUC. Results:Multivariate logistic regression analysis showed that associated features (OR=9.075,95%CI 1.430-57.570, P=0.019), lesion conspicuity (OR=6.180,95%CI 2.608-14.646, P<0.001), mass margin (OR=2.193,95%CI 1.405-3.422, P=0.001) and calcification distribution (OR=2.147,95%CI 1.157-3.986, P=0.015) were independent predictors of differentiating benign and malignant breast lesions in CEM, and then the predictive model of CEM was constructed. Time-signal intensity curve (OR=9.230, 95%CI 3.178-26.805, P<0.001), associated features (OR=5.289,95%CI 1.343-20.831, P=0.017) and mass margin (OR=2.192,95%CI 1.336-3.597, P=0.002) were independent predictors of differentiating benign and malignant breast lesions in MRI, and the predictive model of MRI was constructed. The AUC of CEM and MRI models for differentiating benign and malignant breast lesions were 0.947 and 0.930 respectively, and two models were no significant difference ( Z=0.68, P=0.494). Conclusion:The diagnostic efficacy of CEM and MRI in differentiating benign and malignant breast lesions is comparable based on the 2013 BI-RADS lexicon and the supplement on CEM.

The value of radiomics based on contrast-enhanced spectral mammography of internal and peripheral regions combined with clinical factors in predicting benign and malignant breast lesions of breast imaging reporting and data system category 4 / 中华放射学杂志

Objective:To evaluate the value of radiomics based on contrast-enhanced spectral mammography (CESM) of internal and peripheral regions combined with clinical factors in predicting benign and malignant breast lesions of breast imaging reporting and data system category 4 (BI-RADS 4).Methods:A retrospective analysis was performed on the clinical and imaging data of patients with breast lesions who were treated in Yantai Yuhuangding Hospital (Center 1) Affiliated to Qingdao University from July 2017 to July 2020 and in Fudan University Cancer Hospital (Center 2) from June 2019 to July 2020. Center 1 included 835 patients, all female, aged 17-80 (49±12) years, divided into training set (667 cases) and test set (168 cases) according to the "train-test-split" function in Python software at a ratio of 8∶2; and 49 patients were included from Center 2 as external validation set, all female, aged 34-70 (51±8) years. The radiomics features were extracted from the intralesional region (ITR), the perilesional regions of 5, 10 mm (PTR 5 mm, PTR10 mm) and the intra-and perilesional regions of 5, 10 mm (IPTR 5 mm, IPTR 10 mm) and were selected by variance filtering, SelectKBest algorithm, and least absolute shrinkage and selection operator. Then five radiomics signatures were constructed including ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, IPTR 10 mm signature. In the training set, univariable and multivariable logistic regressions were used to construct nomograms by selecting radiomics signatures and clinical factors with significant difference between benign and malignant BI-RADS type 4 breast lesions. The efficacy of nomogram in predicting benign and malignant BI-RADS 4 breast lesions was evaluated by the receiver operating characteristic curve and area under the curve (AUC). Decision curve and calibration curve were used to evaluate the net benefit and calibration capability of the nomogram.Results:The nomogram included ITR signature, PTR 5 mm signature, PTR 10 mm signature, IPTR 5 mm signature, age, and BI-RADS category 4 subclassification for differentiating malignant and benign BI-RADS category 4 breast lesions and obtained AUCs of 0.94, 0.92, and 0.95 in the training set, test set, and external validation set, respectively. The calibration curve showed good agreement between the predicted probabilities and actual results and the decision curve indicated a good net benefit of the nomogram for predicting malignant BI-RADS 4 lesions in the training set, test set, and external validation set.Conclusion:The nomogram constructed from the radiomics features of the internal and surrounding regions of CESM breast lesions combined with clinical factors is attributed to differentiate benign from malignant BI-RADS category 4 breast lesions.

Application value of S-Detect combined with contrast-enhanced ultrasound in the Breast Imaging Reporting and Data System 4 breast lesions / 中华超声影像学杂志

Objective:To assess the value of S-Detect and contrast-enhanced ultrasound (CEUS) in the differential diagnosis of Breast Imaging Reporting and Data System(BI-RADS) 4 breast lesions.Methods:A total of 104 breast lesions in 100 patients diagnosed as BI-RADS category 4 by conventional ultrasound were prospectively enrolled, and all of them were received S-Detect and CEUS examination at the same time. Taking pathology as the gold standard, ROC curve was constructed to compare the diagnostic efficacy of conventional ultrasound, S-Detect, CEUS and their combination.Results:Among the 104 BI-RADS category 4 breast lesions, 63 were benign and 41 were malignant. The sensitivities of conventional ultrasound, S-Detect, CEUS and S-Detect combined with CEUS were 73.17%, 87.80%, 87.80%, 90.24%; the specificities were 57.14%, 60.32%, 68.25%, 77.78%; the positive predictive values were 52.63%, 59.02%, 64.29% and 72.55%; the negative predictive values were 76.60%, 88.37%, 89.59% and 92.45%; the accuracies were 63.46%, 71.15%, 75.96% and 82.69%; and the areas under the ROC curve (AUC) were 0.652, 0.741, 0.780 and 0.840. The sensitivity, specificity, positive predictive value, negative predictive value and accuracy of S-Detect and CEUS diagnosis were improved compared with conventional ultrasound. The AUC of combined diagnosis was higher than that of S-Detect, CEUS alone, and the differences were statistically significant(all P<0.05). The AUC of CEUS was higher than that of conventional ultrasound, and the difference was statistically significant ( P<0.05). There were no significant differences in AUC between any two of other groups (all P>0.05). Conclusions:The combined application of S-Detect and CEUS could achieve complementary advantages, which is of great significance for the differential diagnosis of benign and malignant in BI-RADS 4 breast lesions.

Best Practice Guidelines for Breast Imaging, Breast Imaging Society, India: Part—2

Breast imaging is a prerequisite for providing high quality breast health care. Choosing the appropriate investigation is central to diagnosing breast disease in patients who present to health professionals for treatment. These patients present to doctors of different subspecialties as well as to general practitioners in our country. It is important, therefore, to provide uniform guidance to doctors in different healthcare setups of our country, urban and rural, government and private, for optimal management of breast diseases. These guidelines framed by the task group set up by the Breast Imaging Society, India, have been formulated focusing primarily on the Indian patients and health care infrastructures. They aim to provide a framework for the referring doctors and practicing radiologists to enable them to choose the appropriate investigation for patients with breast symptoms and signs. The aim has been to keep this framework simple and practical so that it can guide not only subspecialists in breast care but also help doctors who do not routinely deal with breast diseases, so that breast cancer is not missed. Overall, the aim of this document is to provide a holistic approach to standardize breast care imaging services in India. Part 2 of these guidelines focuses on the best practice principles for breast interventions and provides algorithms for the investigation of specific common breast symptoms and signs. Ultrasound is the preferred imaging modality for image-guided breast interventions due to real-time needle visualization, easy availability, patient comfort and absence of radiation. Stereotactic mammography guided procedures are performed if the lesion is visualized on mammography but not visualized on ultrasound. 14-gauge automated core biopsy device is preferred for breast biopsies although vacuum assisted biopsy devices are useful for biopsy of certain abnormalities as well as for imaging guided excision of some pathologies. MRI guided biopsy is reserved for suspicious lesions seen only on MRI. Algorithms for investigation of patients presenting with mastalgia, breast lumps, suspicious nipple discharge, infections and inflammation of the breast have been provided. For early breast cancers routine use of investigations to detect occult distant metastasis is not advised. Metastatic work up for advanced breast cancer is required for selection of appropriate treatment options.

Best Practice Guidelines for Breast Imaging, Breast Imaging Society, India: Part—1

Breast imaging is one of the prerequisites for providing high quality breast health care. Choosing the appropriate investigation is central to diagnosing breast disease in women and men who present to health professionals for treatment. Patients with breast disease present to doctors of different subspecialties as well as general practitioners in our country. It is important therefore to provide uniform guidance to doctors in different health care setups of our country, urban and rural, government and private, for breast diseases to be diagnosed and treated optimally. These guidelines framed by the task group set up by the Breast Imaging Society, India have been formulated focusing primarily on the Indian patients and health care infrastructures. These guidelines aim to provide a framework for the referring doctors and practicing radiologists, to enable them to choose the appropriate investigation for patients with breast symptoms and signs. The aim has been to keep this framework simple and practical so that it can guide not only subspecialists in breast care but also help doctors who do not routinely deal with breast diseases, so that breast cancer is not missed. Overall, the aim of this document is to provide a holistic approach to standardize breast care imaging services in India. Part 1 of these guidelines focuses on the best practice principles for mammography, breast ultrasound and breast magnetic resonance imaging. In the absence of a population-based screening program in India, the guidelines to be followed for those women who wish to be screened by mammography have been provided. The key points of these guidelines include the recommendations that mammography is the modality of choice for breast screening and investigation of symptomatic women aged over forty years. Screening is advised annually from the age of forty. Ultrasound is the investigation of choice for pregnant and lactating women and women less than thirty years of age. For women between thirty to thirty-nine years of age, ultrasound can be used initially followed by mammography in presence of clinical or sonographic suspicion of breast cancer. All women diagnosed with breast cancer should have ultrasound and mammography. Breast MRI is useful for assessment of disease extent, problem solving, evaluation of response to neo-adjuvant chemotherapy, identifying occult breast primary and evaluation of augmented breasts.

The value of conventional ultrasound combined with contrast-enhanced ultrasound in the diagnosis of BI-RADS category 4 small breast nodules / 中华超声影像学杂志

Objective:To evaluate the value of conventional ultrasound(US) combined with contrast-enhanced ultrasound(CEUS) in the diagnosis of Breast Imaging Reporting and Data System( BI-RADS) category 4 small(≤ 2 cm) breast nodules.Methods:A total of 175 breast nodules in 175 patients from Fujian Cancer Hospital between September 2015 and August 2018 classified as BI-RADS category 4 breast nodules with maximum diameter ≤2 cm were evaluated by US and CEUS examinations. All nodules were examined by core-needle biopsy or surgical pathology.The collected ultrasound images and videos were analyzed by blind method. Stepwise Logistic regression was used to analyze the odds ratio of malignant nodules in ultrasound images, and the risk prediction score model was constructed according to OR value. The BI-RADS category was readjusted, and the diagnostic efficiencies before and after adjustment were compared with the ROC curve. Results:Multivariate Logistic regression analysis showed that the odds ratios of breast malignant nodules were non-circumscribed margin ( OR=3.32, P=0.052), calcification in the mass ( OR=7.42, P=0.002), architectural distortion ( OR=38.58, P<0.001), ductal dilatation ( OR=0.01, P=0.010), suspicious or abnormal axillary lymph nodes ( OR=10.92, P=0.003), enlarged lesion scope ( OR=3.38, P=0.040), penetrating vessels ( OR=10.79, P=0.006), and non-circumscribed margin after enhancement( OR=6.24, P=0.003). When the cut-off value was 3.5, the area under ROC curve, sensitivity, specificity and accuracy were 0.951, 87.80%, 89.20% and 88.57%, respectively. After adjusting BI-RADS classification and taking the adjusted BI-RADS category 4a as the biopsy threshold, the biopsy rate decreased from 100% to 58.86%, the cancer detection rate increased from 46.86% to 75.73%, and the risk of missed diagnosis was 2.29%. The area under ROC curve before and after BI-RADS classification adjustment was 0.838 and 0.937, respectively. Conclusions:US combined with CEUS can improve the diagnostic efficiency of BI-RADS category 4 small breast nodules and reduce unnecessary biopsy.

The qualitative and quantitative features of contrast-enhanced ultrasound in biomarker expression of breast cancer / 中华超声影像学杂志

Objective:To evaluate the relationships among contrast-enhanced ultrasound (CEUS) features, molecular type, and biomarker expression of breast cancer.Methods:A retrospectively analysis of breast cancer patients confirmed by pathology were performed using Breast Imaging Report And Data System (BI-RADS) ultrasound category lesions in the Second Affiliated Hospital Zhejiang University School of Medicine from May 2020 to April 2021. All patients underwent conventional ultrasound and CEUS before biopsy and/or surgery. The relationships among BI-RADS category, quantitative and qualitative CEUS features and biomarker expression of breast cancer were evaluated.Results:All 149 patients with 149 breast lesions were included. The numbers of BI-RADS category 4A, 4B, 4C, and 5 were 8, 60, 49, and 32, respectively. Among them, the numbers of Luminal A like, Luminal B like (human epidermal growth factor receptor-2 (HER-2) positive), Luminal B like (HER-2 negative), HER-2 overexpression and triple negative type were 81, 29, 17, 15, and 7. No significant correlations were found among BI-RADS category, molecular types, and biomarker estrogen receptor (ER), progesterone receptor (PR), HER-2, and antigen Ki-67 (Ki-67) expression (all P>0.05). There were no correlations between quantitative or qualitative CEUS features and molecular types of breast cancer (all P>0.05). There were no correlations between qualitative CEUS variables and ER, PR, HER-2, and Ki-67 expression (all P>0.05). Ascending slope (AS) were negatively correlated with ER and PR expression( r=-0.40, P=0.01; r=-0.35, P=0.03). Descending slope (DS) were positively correlated with ER and PR expression( r=0.42, P=0.01; r=0.36, P=0.03). Arrive time (AT) were positively correlated with HER-2 expression( r=0.37, P=0.02). Conclusions:AS and DS are correlated with ER and PR expression.Arrive time (AT) is correlated with HER-2 expression. The quantitative variables of CEUS are helpful for evaluation of biomarker expression in breast cancer.

Diagnosis of breast lumps based on breast imaging reporting and data system score and histopathological examination: a comparative study

Background: Breast cancer incidence in India is increasing and has now become the most common cancer among women. Preoperative pathology diagnosis and mammography (using breast imaging reporting and data system      (BI-RADS) scoring system) constitute an essential part of the workup of breast lesions. The present study was aimed to compare the diagnostic accuracy of BI-RADS score with histopathological finding in diagnosis of benign and malignant lesions of breast.Methods: This is a cross-sectional study. The present study was conducted on 100 randomly selected newly diagnosed cases of breast lump attending the General Surgery Department (OPD).Results: Considering histopathological examination as gold standard, the sensitivity and specificity of BI-RADS score is 93.9% and 82.3% respectively. The positive predictive value, negative predictive value and diagnostic accuracy of BI-RADS score is 91.1%, 87.5% and 90.0% respectively.Conclusions: Author conclude from the present study that BI-RADS score being non-invasive, it may become a very useful test for evaluating Breast lump lesions. However, BI-RADS score cannot be considered as gold standard and thus cannot be used as an alternative to histopathology in diagnosis of breast lumps.

S-DetectTM classification technique in diagnosis of BI-RADS 4 breast masses / 中国医学影像技术

Objective: To explore the diagnostic value of S-DetectTM classification technique for benign and malignant breast imaging reporting and data system (BI-RADS) 4 breast masses. Methods: Totally 94 patients with 104 two-dimensional ultrasound diagnosed BI-RADS 4 breast masses were examined using S-DetectTM classification technique. Taken pathological results as the gold standards, the diagnostic values of S-DetectTM classification technology, BI-RADS classification alone and the combination of them of benign and malignant breast BI-RADS 4 masses were observed. Results: There were 41 benign and 63 malignant ones among all 104 BI-RADS 4 breast masses. The sensitivity (SE) of S-DetectTM classification technique for diagnosing breast BI-RADS 4a mass was 66.67%, specificity (SP) was 89.29%, positive predictive value (PPV) was 57.14%, negative predictive value (NPV) was 92.59%, of BI-RADS 4b masses was 90.91%, 60.00%, 88.24% and 66.67%, of breast BI-RADS 4c mass was 95.83%, 66.67%, 95.83% and 66.67%, respectively. SE, SP and accuracy of combination of S-DetectTM classification and BI-RADS classification for diagnosing breast masses were significantly higher than those of BI-RADS classification and S-DetectTM classification technique alone (all P<0.05). Conclusion: S-DetectTM classification technique was valuable for judging BI-RADS 4a benign masses as well as BI-RADS 4b and BI-RADS 4c malignant masses. S-DetectTM classification technology combined with BI-RADS classification could significantly improve the diagnostic value of identifying benign and malignant BI-RADS 4 breast masses.

Large axillary accessory breast hamartoma: a rare entity

Hamartomas are uncommon benign tumours of axilla and breast. They show varied imaging appearances depending upon the proportion of various tissue elements present. The mammographic, ultrasound and elastographic appearances of a case of left axillary hamartoma is described in a 49 years old Indian patient.

Diagnostic performance of contrast-enhanced spectral mammography for breast imaging reporting and data system 4 calcifications / 中国医学影像技术

Objective To assess the diagnostic performance of contrast-enhanced spectral mammography (CESM) for breast imaging reporting and data system (BI-RADS) 4 calcifications comparing with full-field digital mammography (FFDM). Methods Patients with mammographic calcifications without associated mass or distortions, which were originally reported as BI-RADS 4 were enrolled, and the lesions were divided into FFDM group (n=48) or CESM group (n=31) according to the examination they received. The diagnosis of benign or malignant calcifications was made based on distribution and morphology on FFDM and the presence of enhancement on CESM. Taking pathology results as golden standards, the diagnostic efficacy was assessed and compared between FFDM and CESM. Results The diagnostic sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV) and accuracy were 69.23% (9/13), 77.14% (27/35), 52.94% (9/17), 87.10% (27/31) and 75.00%(36/48) for FFDM group, and 90.00% (9/10), 95.24% (20/21), 90.00% (9/10), 95.24% (20/21) and 93.55% (29/31) for CESM group, respectively. PPV and accuracy of CESM were significantly higher than those of FFDM (χ2=3.891, 4.444, P=0.049, 0.035). Conclusion Compared with FFDM, CESM can improve diagnostic performance on BI-RADS 4 mammographic calcifications.

CEUS in evaluation of malignant risk of BI-RADS 4 levels of breast lesions with different sizes / 中国医学影像技术

Objective: To evaluate the value of CEUS in evaluating of malignant risk of breast imaging report and data system (BI-RADS) 4 levels of breast lesions with different sizes. Methods: The CEUS characteristics of BI-RADS 4 levels of the benign and malignant breast lesions with diameter ≤2 cm (n=120) and diameter >2 cm (n=63) were analyzed retrospectively. Binary Logistic regression analysis was used to screen CEUS characteristic parameters that could predict malignant lesions. Results: There were differences of enhanced shape, enhanced intensity, homogeneity, perfusion pattern, nourishing vessels, enhanced area expansion, initial rates and fading rates between the benign and malignant lesions with diameter ≤2 cm (all P2 cm (all P<0.05); regression analysis showed that nourishing vessels, centripetal enhancement pattern and enhanced area expansion were independently correlated with malignant breast lesions of BI-RADS 4 levels (all P<0.05). Conclusion: CEUS can be used to evaluate the malignant risk of BI-RADS 4 levels of breast lesions with different sizes.

Combination of BI-RADS for ultrasound and shear wave elastography in differential diagnosis of benign and malignant breast lesions / 上海交通大学学报（医学版）

Objective • To explore the value of the 2013 version of the ultrasound breast imaging reporting and data system (BI-RADS) classification diagnostic criteria combined with ultrasound shear wave elastography (SWE) to identify benign and malignant breast lesions. Methods • A total of 175 solid breast masses in 155 women were examined with ultrasound, and were judged to be benign or malignant by BI-RADS classification criteria. Then all the masses were examined with shear wave elastography (SWE), to obtain shear wave quantitative parameters of benign and malignant breast lesions, the pathological results were used as the gold standard to construct the receiver operating characteristic (ROC) curve of the subjects, which were used to compare the diagnostic value of the two methods alone and in combination. Results • The area under curve (AUC) of the BI-RADS classification diagnostic criteria, the Emax value, and the combination of the two methods to differential diagnosis of benign and malignant breast nodules were 0913, 0.884 and 0.957, respectively. Through pairwise comparison, there was significant difference in AUC between the two methods alone and their combination (BI-RADS classification vs. combination: Z=2.883, P=0.002; SWE vs. combination: Z=4.081, P=0.000). Conclusion • The combination of BI-RADS classification and SWE technology can improve the diagnostic accuracy of breast lesions.

Automatic extraction of imaging observation and assessment categories from breast magnetic resonance imaging reports with natural language processing / 中华医学杂志(英文版)

Background@#Structured reports are not widely used and thus most reports exist in the form of free text. The process of data extraction by experts is time-consuming and error-prone, whereas data extraction by natural language processing (NLP) is a potential solution that could improve diagnosis efficiency and accuracy. The purpose of this study was to evaluate an NLP program that determines American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) descriptors and final assessment categories from breast magnetic resonance imaging (MRI) reports.@*Methods@#This cross-sectional study involved 2330 breast MRI reports in the electronic medical record from 2009 to 2017. We used 1635 reports for the creation of a revised BI-RADS MRI lexicon and synonyms lists as well as the iterative development of an NLP system. The remaining 695 reports that were not used for developing the system were used as an independent test set for the final evaluation of the NLP system. The recall and precision of an NLP algorithm to detect the revised BI-RADS MRI descriptors and BI-RADS categories from the free-text reports were evaluated against a standard reference of manual human review.@*Results@#There was a high level of agreement between two manual reviewers, with a κ value of 0.95. For all breast imaging reports, the NLP algorithm demonstrated a recall of 78.5% and a precision of 86.1% for correct identification of the revised BI-RADS MRI descriptors and the BI-RADS categories. NLP generated the total results in <1 s, whereas the manual reviewers averaged 3.38 and 3.23 min per report, respectively.@*Conclusions@#The NLP algorithm demonstrates high recall and precision for information extraction from free-text reports. This approach will help to narrow the gap between unstructured report text and structured data, which is needed in decision support and other applications.

Reliability of automated versus handheld breast ultrasound examinations of suspicious breast masses

PURPOSE: The purpose of this study was to assess the reliability of automated breast ultrasound (ABUS) examinations of suspicious breast masses in comparison to handheld breast ultrasound (HHUS) with regard to Breast Imaging Reporting and Data System (BI-RADS) category assessment, and to investigate the factors affecting discrepancies in categorization. METHODS: A total of 135 masses that were assessed as BI-RADS categories 4 and 5 on ABUS that underwent ultrasound (US)-guided core needle biopsy from May 2017 to December 2017 were included in this study. The BI-RADS categories were re-assessed using HHUS. Agreement of the BI-RADS categories was evaluated using kappa statistics, and the positive predictive value of each examination was calculated. Logistic regression analysis was performed to identify the mammography and US findings associated with discrepancies in the BI-RADS categorization. RESULTS: The overall agreement between ABUS and HHUS in all cases was good (79.3%, kappa=0.61, P<0.001). Logistic regression analysis revealed that accompanying suspicious microcalcifications on mammography (odds ratio [OR], 4.63; 95% confidence interval [CI], 1.83 to 11.71; P=0.001) and an irregular shape on US (OR, 5.59; 95% CI, 1.43 to 21.83; P=0.013) were associated with discrepancies in the BI-RADS categorization. CONCLUSION: The agreement between ABUS and HHUS examinations in the BI-RADS categorization of suspicious breast masses was good. The presence of suspicious microcalcifications on mammography and an irregular shape on US were factors associated with ABUS yielding a lower level of suspicion than HHUS in terms of the BI-RADS category assessment.

Combination of BI-RADS for ultrasound and shear wave elastography in differential diagnosis of benign and malignant breast lesions / 上海交通大学学报（医学版）

Objective · To explore the value of the 2013 version of the ultrasound breast imaging reporting and data system (BI-RADS) classification diagnostic criteria combined with ultrasound shear wave elastography (SWE) to identify benign and malignant breast lesions. Methods · A total of 175 solid breast masses in 155 women were examined with ultrasound, and were judged to be benign or malignant by BI-RADS classification criteria. Then all the masses were examined with shear wave elastography (SWE), to obtain shear wave quantitative parameters of benign and malignant breast lesions, the pathological results were used as the gold standard to construct the receiver operating characteristic (ROC) curve of the subjects, which were used to compare the diagnostic value of the two methods alone and in combination. Results · The area under curve (AUC) of the BI-RADS classification diagnostic criteria, the Emax value, and the combination of the two methods to differential diagnosis of benign and malignant breast nodules were 0913, 0.884 and 0.957, respectively. Through pairwise comparison, there was significant difference in AUC between the two methods alone and their combination (BI-RADS classification vs. combination: Z=2.883, P=0.002; SWE vs. combination: Z=4.081, P=0.000). Conclusion · The combination of BI-RADS classification and SWE technology can improve the diagnostic accuracy of breast lesions.

The value of ultrasound classification in BI-RADS category 4 of breast complex cystic masses / 中华肿瘤杂志

Objective@#To analyze the feature of breast complex cystic masses and to classify it at ultrasonography (US), which applied to the Breast Imaging Reporting and Data System (BI-RADS) categories 4a to 4c with pathological results as the golden standards.@*Methods@#The ultrasonographic data and clinical features of 78 patients with complex cystic masses confirmed by pathology in Cancer Hospital from July 2014 to June 2017 were retrospectively reviewed. The complex cystic breast masses were divided into four classes on the basis of their US features: type 1 [thick wall and (or) thick septa (> 0.5 mm)], type 2 (one or more intra-cystic masses), type 3 (mixed cystic and solid components with cystic components more than 50%) and type 4 (mixed cystic and solid components with solid components more than 50%). Positive values (PPVs) were calculated for each type. Multiple linear regression analysis was used to analyze the ultrasonographic features of the masses (lesion size, margins, blood flow resistance index, calcification, and axillary lymph nodes, etc.) with malignant correlation.@*Results@#There were 81 lesions in 78 patients. Among the 81 masses based on US appearance, 14 (17.3%) were classified as type Ⅰ, 18 (22.2%) as type Ⅱ, 18 (22.2%) as type Ⅲ, and 31 (38.3%) as type Ⅳ. The positive predictive values of the malignant lesions of type Ⅰ, type Ⅱ, Ⅲ and Ⅳ were 7.1%, 16.7%, 61.1% and 48.3%, respectively (P=0.040). In all the 81 masses, 14 were BI-RADS categories 4a, 18 were BI-RADS categories 4b and 49 were BI-RADS categories 4c. Masses with maximum diameter equal to or larger than 2.0 cm, unclear margins, RI≥0.7 and presence of abnormal axillary nodes assessment had a high probability of malignancy (P=0.030, 0.038, <0.001 and 0.025, respectively).@*Conclusion@#Ultrasound typing is helpful for differentiating benign and malignant breast complex cysts and classifying BI-AIDS 4a to 4c, thus providing clearer treatment for clinical practice.

Evaluation of contrast-enhanced ultrasonography breast predictive model in optimizing breast lesions BI-RADS classification / 中华超声影像学杂志

Objective To explore the value of contrast-enhanced ultrasonography ( CEUS ) breast predictive model in the optimization of BI-RADS classification of breast lesions . Methods A total of 1049 BI-RADS 4 ,5 breast lesions were obtained from 1039 patients in 8 centers . CEUS examination was performed prior to biopsy or surgery . According to the classification of the model ,class 3 ,4A ,4B and 4C were selected as biopsy thresholds ,and the ROC curve was drawn . The diagnostic sensitivity ,specificity , accuracy ,positive predictive value ,negative predictive value and Jordanian index were calculated for the biopsy threshold . The biopsy rate of breast lesions before and after angiography ,cancer detection rate , follow-up cases of malignant risk were compared . Results There were benign lesions 586 ( 55 .9％ ) , malignant lesions 463 (44 .1％ ) in the 1049 breast lesions . The area of ROC with thresholds of 3 ,4A ,4B and 4C were 0 .695 ,0 .838 ,0 .847 and 0 .757 ,respectively ( all P < 0 .01) . Ultrasonography had a certain diagnostic effect on benign and malignant breast lesions . The diagnostic sensitivity ,specificity ,accuracy , positive predictive value and negative predictive value with class 4A after CEUS set as the biopsy threshold were 93 .32％ ,75 .65％ ,82 .75％ ,75 .57％ and 93 .35％ ,respectively ,and the Jordanian index was 0 .690 . When chass 3 after CEUS was set as the biopsy threshold ,the biopsy rate was reduced from 100％ to 76 .74％ ,the detection rate was increased from 44 .23％ to 56 .77％ ,and the risk of cancer was only 0 .67％ in the follow-up cases . When class 4A was set as the biopsy threshold ,the biopsy rate was reduced from 100％ to 55 .58％ after CEUS . The detection rate of cancer increased from 44 .23％ to 74 .44％ . The risk of cancer was 2 .96％ . Conclusions The biopsy rate of breast lesions in category 4 and 5 would be reduced and cancer detection rate of them would be increased after CEUS ,however ,the risk of malignancy in the follow -up cases would be controlled as low as category 3 and 4A in previous BI-RADS . Thus ,CEUS has a good prospect of in optimizing BI-RADS and reducing biopsy rate in unnecessary lesions .

Status of new ultrasonic technology combined with breast imaging-reporting and data system for ultrasound in evaluating breast lesions / 中国介入影像与治疗学

Nowadays,breast imaging-reporting and data system for ultrasound (BI-RADS-US) is widely used in the clinic.With the rapid development of ultrasound technology,such as elastography,CEUS,three-dimensional ultrasonography and MicroPure technology,the combination of new ultrasonic technology with BI-RADS-US plays a more important role in improving the ability of ultrasound in diagnosis of small breast lesions and the diagnosis efficiency for breast cancer.The status of new ultrasonic technology combined with BI-RADS-US in evaluating benign and malignant breast lesions were reviewed in this article.

Clinical applications of breast imaging reporting and data system / 中国医学影像技术

Breast imaging reporting and data system (BI-RADS) is a standardized system for reporting breast pathology covered mammography,ultrasound and MRI.BI-RADS improves the standardization in interpretation of medical imaging and reduces the confusion of breast imaging interpretation.It is a widely accepted risk assessment and quality assurance tool in mammography,ultrasound and MRI.The development history,clinical applications,limitations of BI-RADS,as well as the clinical applications combined with other imaging techniques were reviewed in this article.