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.

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.

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.

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.

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.

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.

Combined use of the ultrasound elastography and the automated breast volume scanner in differentiation of benign and malignant breast imaging reporting and data system 4 breast lesions / 中华医学超声杂志（电子版）

Objectives To investigate the diagnostic performance of the combination of ultrasound elastography and automated breast volume scanner (ABVS) in differentiation of benign and malignant breast imaging reporting and data system (BI-RADS) 4 breast lesions. Methods Data from 137 breast cancer patients (147 tumors) confirmed pathologically were analyzed. Each tumor was examined by ABVS and ultrasound elastography. All tumors were diagnosed as BI-RADS 4 by ABVS. With final pathology results as the gold standard, the predictive value in differentiating BI-RADS 4 breast lesions between ultrasound elastography and the combination of ultrasound elastography and ABVS were compared. Results There were 54 benign nodules and 93 malignant nodules in this study. The diagnostic sensitivity of ultrasound elastography and the combination of ultrasound elastography and ABVS were 94.6% and 98.9%,the specificity were 57.4% and 57.4%, the accuracy were 81.0% and 83.7%, the area under the curve were 0.858 and 0.965, respectively. The diagnostic performance of ultrasound elastography combined with ABVS was better than that of ultrasound elastography. Conclusions Ultrasound elastography have certain value in differential diagnosis of BI-RADS 4 breast lesions, especially when combining with ABVS, which will improve its diagnostic accuracy. Ultrasound elastography combined with ABVS can improve the detection rate of malignant lesions in BI-RADS 4 breast lesions and reduce the rate of preoperative biopsy, and it has a good application prospect.

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.

Cysts within Otherwise Probably Benign Solid Breast Masses and the Risk of Malignancy / Cistos no interior de nódulo mamários benignos: risco de malignidade

Abstract Objective The objective of this study is to assess whether the largest cyst diameter is useful for BI-RADS ultrasonography classification of predominantly solid breast masses with an oval shape, circumscribed margins, and largest axis parallel to the skin, which, except for the cystic component, would be likely classified as benign. Methods This study received approval from the local institutional review board. From March 2009 to August 2014, we prospectively biopsied 170 breast masses from 164 women. We grouped the largest cyst and mass diameters according to histopathological diagnoses. We used Student's t-test, linear regression, and the area under the receiver operating characteristic curve (AUC) for statistical assessment. Results Histopathological examination revealed 143 (84%) benign and 27 (16%) malignant masses. The mean largest mass diameter was larger among malignant (mean standard deviation, 34.1 16.6 mm) than benign masses (24.7 16.7 mm) (P < 0.008). The mean largest cyst diameter was also larger among malignant (9.9 7.1 mm) than benign masses (4.6 3.6 mm) (P < 0.001). Agreement between measurements of the largest mass and cyst diameters was low (R2 = 0.26). AUC for the largest cyst diameter (0.78) was similar to the AUC for the largest mass diameter (0.69) ( p = 0.2). A largest cyst diameter < 3, 3 to < 11, and 11 mm had a positive predictive value of 0, 15, and 52%, respectively. Conclusion A largest cystic component < 3 mm identified within breast masses that show favorable characteristics may be considered clinically inconsequential in ultrasonography characterization. Conversely, masses with a largest cystic component 3 mm should be classified as BI-RADS-US category 4.

Resumo Objetivo Avaliar se o maior diâmetro do cisto é útil para a classificação ultrassonográfica BI-RADS de nódulos mamários predominantemente sólidos, com forma oval, margens circunscritas e maior eixo paralelo à pele que, exceto pela presença do componente cístico, seriam classificados como provavelmente benignos. Métodos Este estudo foi aprovado pelo Comitê de Ética local. De março de 2009 a agosto de 2014, 170 nódulos mamários de 164 mulheres foram prospectivamente biópsiados. As medidas do maior diâmetro do maior cisto e do maior diâmetro do nódulo foram agrupados de acordo com os diagnósticos histopatológicos. O teste t de Student, a regressão linear e a área sob a curva ROC (AUC) foram utilizados para a avaliação estatística. Resultados O exame histopatológico revelou 143 (84%) nódulos benignos e 27 (16%) nódulos malignos. A média da medida do maior diâmetro dos nódulos foi maior entre os nódulos malignos (média desvio padrão, 34,1 16,6 mm) do que nos nódulos benignos (24,7 16,7 mm) (p < 0,008). A média do maior diâmetro do maior cisto também foi maior entre os nódulos malignos (9,9 7,1 mm) do que nos nódulos benignos (4,6 3,6 mm) (p < 0,001). A concordância entre as medidas dos maiores diâmetros dos nódulos e do maior diâmetro do maior cisto foi baixa (R2 = 0,26). A AUC do maior diâmetro do maior cisto (0,78) foi semelhante à AUC do maior diâmetro do nódulo (0,69) (p = 0,2). Os maiores diâmetros dos maiores cistos medindo < 3; 3 e < 11; e 11 mm tiveram um valor preditivo positivo de 0, 15 e 52%, respectivamente. Conclusão Componentes císticos < 3 mm identificados dentro de nódulos mamários que apresentam as demais características provavelmente benignas podem ser considerados clinicamente irrelevantes na caracterização ultrassonográfica. Por outro lado, nódulos que apresentam um componente cístico medindo 3 mm devem ser classificadas na categoria BI-RADS-US 4.

Validation of the fifth edition BI-RADS ultrasound lexicon with comparison of fourth and fifth edition diagnostic performance using video clips

PURPOSE: The aim of this study was to evaluate the positive predictive value (PPV) and the diagnostic performance of the ultrasonographic descriptors in the fifth edition of BI-RADS, comparing with the fourth edition using video clips. METHODS: From September 2013 to July 2014, 80 breast masses in 74 women (mean age, 47.5±10.7 years) from five institutions of the Korean Society of Breast Imaging were included. Two radiologists individually reviewed the static and video images and analyzed the images according to the fourth and fifth edition of BI-RADS. The PPV of each descriptor was calculated and diagnostic performances between the fourth and fifth editions were compared. RESULTS: Of the 80 breast masses, 51 (63.8%) were benign and 29 (36.2%) were malignant. Suspicious ultrasonographic features such as irregular shape, non-parallel orientation, angular or spiculated margins, and combined posterior features showed higher PPV in both editions (all P0.05). The area under the receiver operating characteristics curve was higher in the fourth edition (0.708 to 0.690), without significance (P=0.416). CONCLUSION: The fifth edition of the BI-RADS ultrasound lexicon showed comparable performance to the fourth edition and can be useful in the differential diagnosis of breast masses using ultrasonography.

Comparative study between automated breast volume scanner and conventional ultrasound in differentiation of benign and malignant breast imaging reporting and data system 4 breast lesions / 中华医学超声杂志（电子版）

Objective To evaluate the value of automated breast volume scanner (ABVS) and conventional ultrasound in differentiation of benign and malignant breast imaging reporting and data system (BI-RADS) 4 breast lesions. Methods Totally 239 breast lesions from 217 patients, with diagnosing of BI-RADS 4 by conventional ultrasound and automatically breast volume imaging, were analyzed retrospectively, using postoperative pathology as golden standard. The sensitivity, specificity, accuracy and area under the curve of ABVS and conventional ultrasound were calculated separately. Results There were 154 benign breast lesions, 83 malignant lesions and 2 borderline lesions. The statistical analysis results of ABVS and conventional ultrasound were 96.10% and 91.80% in sensitivity, 84.30% and 80.20% in specificity,89.30% and 84.10% in accuracy, and 0.952 and 0.833 in area under the curve. Therefore, ABVS was superior to the conventional ultrasound. Conclusion Compared with conventional ultrasound, ABVS could improve the diagnostic efficacy for BI-RADS 4 breast lesions in the aspects of sensitivity, specificity, accuracy, which was useful in detection of small and atypical breast cancer and could be used as a noninvasive and reliable complement for conventional ultrasound.