The Utility of the Fifth Edition of the BI-RADS Ultrasound Lexicon in Category 4 Breast Lesions: A Prospective Multicenter Study in China.

RATIONALE AND OBJECTIVES: The objective of this study was to evaluate the utility of the fifth edition of the Breast Imaging-Reporting and Data System (BI-RADS) in clinical breast radiology by using prospective multicenter real-time analyses of ultrasound (US) images. MATERIALS AND METHODS: We prospectively studied 2049 female patients (age range, 19-86 years; mean age 46.88 years) with BI-RADS category 4 breast masses in 32 tertiary hospitals. All the patients underwent B-mode, color Doppler US, and US elastography examination. US features of the mass and associated features were described and categorized according to the fifth edition of the BI-RADS US lexicon. The pathological results were used as the reference standard. The positive predictive values (PPVs) of subcategories 4a-4c were calculated. RESULTS: A total of 2094 masses were obtained, including 1124 benign masses (54.9%) and 925 malignant masses (45.1%). For BI-RADS US features of mass shape, orientation, margin, posterior features, calcifications, architectural distortion, edema, skin changes, vascularity, and elasticity assessment were significantly different for benign and malignant masses (p< 0.05). Typical signs of malignancy were irregular shape (PPV, 57.2%), spiculated margin (PPV, 83.7%), nonparallel orientation (PPV, 63.9%), and combined pattern of posterior features (PPV, 60.6%). For the changed or newly added US features, the PPVs for intraductal calcifications were 80%, 56.4% for internal vascularity, and 80% for a hard pattern on elastography. The associated features such as architectural distortion (PPV, 89.3%), edema (PPV, 69.2%), and skin changes (PPV, 76.2%) displayed high predictive value for malignancy. The rate of malignant was 7.4% (72/975) in category 4a, 61.4% (283/461) in category 4b, and 93.0% (570/613) in category 4c. The PPV for category 4b was higher than the likelihood ranges specified in BI-RADS and the PPVs for categories 4a and 4c were within the acceptable performance ranges specified in the fifth edition of BI-RADS in our study. CONCLUSION: Not only the US features of the breast mass, but also associated features, including vascularity and elasticity assessment, have become an indispensable part of the fifth edition of BI-RADS US lexicon to distinguish benign and malignant breast lesions. The subdivision of category 4 lesions into categories 4a, 4b, and 4c for US findings is helpful for further assessment of the likelihood of malignancy of breast lesions.

Risk-predicted dual nomograms consisting of clinical and ultrasound factors for downgrading BI-RADS category 4a breast lesions - A multiple centre study.

Purpose: To develop and to validate a risk-predicted nomogram for downgrading Breast Imaging Reporting and Data System (BI-RADS) category 4a breast lesions. Patients and Methods: We enrolled 680 patients with breast lesions that were diagnosed as BI-RADS category 4a by conventional ultrasound from December 2018 to June 2019. All 4a lesions were randomly divided into development and validation groups at the ratio of 3:1. In the development group consisting of 499 cases, the multiple clinical and ultrasound predicted factors were extracted, and dual-predicted nomograms were constructed by multivariable logistic regression analysis, named clinical nomogram and ultrasound nomogram, respectively. Patients were twice classified as either "high risk" or "low risk" in the two nomograms. The performance of these dual nomograms was assessed by an independent validation group of 181 cases. Receiver Operating Characteristic (ROC) curve and diagnostic value were calculated to evaluate the applicability of the new model. Results: After multiple logistic regression analysis, the clinical nomogram included 2 predictors: age and the first-degree family members with breast cancer. The area under the curve (AUC) value for the clinical nomogram was 0.661 and 0.712 for the development and validation groups, respectively. The ultrasound nomogram included 3 independent predictors (margins, calcification and strain ratio), and the AUC value in this nomogram was 0.782 and 0.747 in the development and validation groups, respectively. In the development group of 499 patients, approximately 50.90% (254/499) of patients were twice classified "low risk", with a malignancy rate of 1.18%. In the validation group of 181 patients, approximately 47.51% (86/181) of patients had been twice classified as "low risk", with a malignancy rate of 1.16%. Conclusions: A dual-predicted nomogram incorporating clinical factors and imaging characteristics is an applicable model for downgrading the low-risk lesions in BI-RADS category 4a and shows good stability and accuracy, which is useful for decreasing the rate of invasive examinations and surgery.

Can Combined Screening of Ultrasound and Elastography Improve Breast Cancer Identification Compared with MRI in Women with Dense Breasts-a Multicenter Prospective Study.

Objectives: To assess the performance of elastography (ES) and ultrasound (US) in predicting the malignancy of breast lesions and to compare their combined diagnostic value with that of magnetic resonance imaging (MRI). Materials and Methods: The study prospectively enrolled 242 female patients with dense breasts treated in 35 heath care facilities in China between November 2018 and October 2019. Based on conventional US and elastography, radiologists classified the degree of suspicion of breast lesions according to the US Breast Imaging Reporting and Data System (BI-RADS) criteria. The diagnostic value was compared between US BI-RADS and MRI BI-RADS, with pathological results used as the reference standard. Results: The results demonstrated that irregular tumor shape, a nonparallel growth orientation, indistinct margins, angular contours, microcalcifications, color Doppler flow and ES score on US imaging were significantly related to breast cancer in dense breasts (P=0.001; P=0.001; P=0.008; P<0.001; P=0.019; P=0.008; P=0.002, respectively). The sensitivity, specificity, PPV, NPV, accuracy and AUC of US BI-RADS category were 94.7%, 90.7%, 95.8%, 88.0%, 93.4% and 0.93 (95%CI, 0.88-0.97), respectively, while those of MRI BI-RADS category were 98.2%, 57.5%, 84.3%, 83.3%, 86.0% and 0.78 (95%CI, 0.71-0.85), respectively. MRI BI-RADS showed a significantly higher sensitivity than US BI-RADS (98.2% vs 94.7%, P=0.043), whereas US BI-RADS showed significantly higher specificity (90.7% vs 57.5%, P<0.001). US BI-RADS showed better diagnostic efficiency in differentiating nodules in dense breasts than MRI BI-RADS (AUC 0.93 vs 0.78, P<0.001). Conclusion: By combining the use of ES and conventional US, US BI-RADS had better diagnostic efficiency in differentiating nodules in dense breasts than MRI. For the diagnosis of malignant tumors in patients with dense breasts, MRI and US BI-RADS can be used as supplemental diagnostic tools to detect lesions, with US BI-RADS considered the preferred adjunctive resource.

Association between the sonographer's experience and diagnostic performance of IOTA simple rules.

BACKGROUND: To validate the clinical value of simple rules in distinguishing malignant adnexal masses from benign ones and to explore the effect of simple rules for experienced and less-experienced sonographers. METHODS: Patients with persistent adnexal masses were enrolled between November 2013 and December 2015. All masses were proven through histological examinations. Five sets of diagnoses were made and compared with one another. Diagnosis 1 was made, according to the simple rules, by a trainee with little clinical diagnostic experience. Diagnoses 2 and 3 were made by experienced and less-experienced sonographers, respectively, according to their clinical experiences. With diagnosis 1 as a reference, the two sonographers were asked to provide a second diagnosis, which were diagnoses 4 and 5. The efficiency of the five sets of diagnoses was compared using ROC curves. RESULTS: In total, 75 malignant (37.7%) and 124 benign lesions (62.3%) were enrolled in this study. The mean diameter of the benign masses was obviously smaller than that of the malignant ones (6.8 ± 3.4 cm vs. 9.3 ± 4.9 cm, p < 0.01). The malignant ratio in postmenopausal women was much higher (66.1%) than that in the premenopausal population (25.7%) (p < 0.0001). Totally, 156 of the 199 cases (79.4%) resulted in conclusive diagnoses. Sensitivity and specificity were 98.4% and 73.9%, respectively, among the conclusive cases. The area under the ROC curve (Az) for the simple rule diagnosis was significantly lower than that for the experienced sonographer diagnosis (0.85 vs. 0.96, p < 0.0001); compared with the less-experienced sonographer, this difference was not significant (0.85 vs. 0.86, p = 0.9776). No significant difference was found in the comparison between the diagnoses made by the experienced sonographer before and after referencing the simple rule diagnosis (Az, 0.96 vs. 0.97, p = 0.2055). Using diagnosis 1 as a reference, the diagnostic performance of the less-experienced sonographer increased (from 0.86 to 0.92, p = 0.012); however, it was still lower than that of the experienced sonographer (Az, 96% vs. 92%, p = 0.0241). CONCLUSIONS: The simple rules was an appealing method for discriminating malignant masses from benign ones, particularly for a less-experienced sonographer.

Distribution patterns of microcalcifications in suspected thyroid carcinoma: a classification method helpful for diagnosis.

PURPOSE: The aim of this study was to compare the distribution patterns of microcalcifications in thyroid cancers with benign cases. METHODS: In total, 358 patients having microcalcifications on ultrasonography were analysed. Microcalcifications were categorised according to the distribution patterns: (I) microcalcifications inside one (a) or more (b) suspected nodules, (II) microcalcifications not only inside but also surrounding a suspected single (a) or multiple (b) nodules, and (III) focal (a) or diffuse (b) microcalcifications in the absence of any suspected nodule. Differences in distribution patterns of microcalcifications in benign and malignant thyroid lesions were compared. RESULTS: We found that the distribution patterns of microcalcifications differed between malignant (n = 325) and benign lesions (n = 117) (X 2 = 9.926, p < 0.01). Benign lesions were classified as type Ia (66.7%), type Ib (29.1%) or type IIIa (4.3%). The specificity of type II and type IIIb in diagnosing malignant cases was 100%. Among malignant lesions, 172 locations were classified as type Ia, 106 as type Ib, 12 as type IIa, 7 as IIb, 7 as type IIIa and 19 as type IIIb. Accompanying Hashimoto thyroiditis was most frequent in type III (51.6%). CONCLUSIONS: Types II and IIIb are highly specific for cancer detection. Microcalcifications outside a nodule and those detected in the absence of any nodule should therefore be reviewed carefully in clinical practice. KEY POINTS: • A method to classify distribution patterns of thyroid microcalcifications is presented. • Distribution features of microcalcifications are useful for diagnosing thyroid cancers. • Microcalcifications outside a suspicious nodule are highly specific for thyroid cancers. • Microcalcifications without suspicious nodules should also alert the physician to thyroid cancers.