B-mode ultrasound diagnostic flowchart for solid breast masses: JABTS BC-01 study.

PURPOSE: Breast ultrasound has been widely used as an essential examination for diagnosing breast cancer. However, standardized diagnostic criteria are as yet lacking. This study aimed to develop a simple diagnostic flowchart for beginners learning breast ultrasonography. The diagnostic flowchart was developed based on the recall criteria widely used in Japan. METHODS: We conducted a multicenter study to examine recall criteria usefulness in the diagnostic phase of breast disease. Women with ultrasound-visible breast masses who underwent B-mode breast ultrasound examination were recruited from 22 hospitals in Japan between September 2009 and January 2010. B-mode images were evaluated by members of the centralized image interpretation committee. We developed the new diagnostic flowchart based on the results. The usefulness of the diagnostic flowchart was assessed by employing datasets from the current study and another study which we conducted (BC-04 study). RESULTS: We evaluated 1045 solid masses (malignant: 495, benign: 550). Multivariate analysis showed that shape, margin, echogenic halo, interruption of the mammary gland interface, and depth width ratio were significant findings for distinguishing between benign and malignant masses. We modified the recall criteria and developed our novel diagnostic flowchart using these findings. The sensitivity and specificity of the new flowchart (current study: 0.97, 0.45; BC-04 study dataset: 0.95, 0.45) were similar to those of experts (current study: 0.96, 0.54; BC-04 study dataset: 0.98, 0.38). CONCLUSION: We developed a simple diagnostic flowchart for breast ultrasound. This flowchart is anticipated to be applicable to educating beginners learning breast ultrasound.

Characteristics of ultrasonographic images of ductal carcinoma in situ with abnormalities of the ducts.

PURPOSE: Although the number of ductal carcinoma in situ (DCIS) cases has increased with the spread of breast cancer screening in Japan, there are very few reports that summarize ultrasound image features of DCIS. The Japan Association of Breast and Thyroid Sonology (JABTS) investigated the incidence of DCIS with masses and non-mass abnormalities and the characteristics of US images in a retrospective, multicenter, observational study (JABTS BC-02 study). The purpose of this report is to clarify the proportion of DCIS with abnormalities of the ducts with each ultrasound finding and the characteristics of US images. METHODS: The JABTS BC-02 study population was comprised of patients who were examined by ultrasonography, underwent surgery, and were histopathologically diagnosed with DCIS at each study site between January 2008 and December 2012. The US images of DCIS and pathology and clinical information were retrospectively collected from 16 institutions in Japan. The US images were evaluated by 22 experts on the Central Image Interpretation Committee of JABTS. RESULTS: Abnormalities of the ducts were noted in 78 (10.5%) of 705 US images of DCIS. Of the 78 cases, the distribution of abnormalities of the ducts was focal or segmental. The second characteristic was the presence of internal echoes in dilated ducts. All cases were accompanied by intraductal solid echoes, and 40 cases (51.3%) were accompanied by echogenic foci. In addition, intraductal solid echoes were continuous or multiple in 72 cases (92.4%), and the shape of the solid echoes was broad-based and/or irregular in 62 cases (79.5%). CONCLUSION: DCIS cases with duct abnormalities on ultrasound were investigated in this study. The important characteristics were as follows: (1) the distribution of ductal dilatation was focal or segmental, (2) solid parts were present in the dilated ducts, (3) the distribution of internal echoes was continuous or multiple, (4) the shape of solid echoes was broad-based and/or irregular, and (5) internal echoes were sometimes accompanied by echogenic foci. Accurate evaluation of these findings may be useful for diagnosing DCIS. Although the duct abnormalities are included in "ASSOCIATED FEATURES" in ACR BI-RADS ATLAS (USA), we emphasize that this concept is very important for understanding US characteristics of DCIS.

Computer-aided diagnosis system for breast ultrasound images using deep learning.

The purpose of this study was to develop a computer-aided diagnosis (CAD) system for the classification of malignant and benign masses in the breast using ultrasonography based on a convolutional neural network (CNN), a state-of-the-art deep learning technique. We explored the regions for the correct classification by generating a heat map that presented the important regions used by the CNN for human malignancy/benign classification. Clinical data was obtained from a large-scale clinical trial previously conducted by the Japan Association of Breast and Thyroid Sonology. Images of 1536 breast masses (897 malignant and 639 benign) confirmed by pathological examinations were collected, with each breast mass captured from various angles using an ultrasound (US) imaging probe. We constructed an ensemble network by combining two CNN models (VGG19 and ResNet152) fine-tuned on balanced training data with augmentation and used the mass-level classification method to enable the CNN to classify a given mass using all views. For an independent test set consisting of 154 masses (77 malignant and 77 benign), our network showed outstanding classification performance with a sensitivity of 90.9% (95% confidence interval 84.5-97.3), a specificity of 87.0% (79.5-94.5), and area under the curve (AUC) of 0.951 (0.916-0.987) compared to that of the two CNN models. In addition, our study indicated that the breast masses themselves were not detected by the CNN as important regions for correct mass classification. Collectively, this CNN-based CAD system is expected to assist doctors by improving the diagnosis of breast cancer in clinical practice.

Multicenter Prospective Study of Color Doppler Ultrasound for Breast Masses: Utility of Our Color Doppler Method.

The use of color Doppler ultrasound (CD) for distinguishing between benign and malignant breast lesions remains controversial. This study (JABTS BC-04 study) was aimed at confirming the usefulness of our CD diagnostic criteria. We evaluated ultrasound images of 1408 solid breast masses from 16 institutions in Japan (malignant: 839, benign: 569). Multivariate analysis indicated that vascularity (amount of blood flow), vascular flow pattern ("surrounding marginal flow" or "penetrating flow") and the incident angle of penetrating flow were significant findings for distinguishing between benign and malignant lesions. However, the sensitivity and specificity of B-mode alone did not improve significantly with CD addition (97.6% → 97.9%, 38.3% → 41.5%, respectively). We explored the causes of these negative results and found that age should have been considered when evaluating vascularity. Simulation experiments suggested that specificity is significantly improved when age is taken into consideration (38.3% → 46.0%, p < 0.001) and we thereby improved our diagnostic criteria.

Ultrasound Image Classification of Ductal Carcinoma In Situ (DCIS) of the Breast: Analysis of 705 DCIS Lesions.

The Japan Association of Breast and Thyroid Sonology (JABTS) proposed, in 2003, a conceptual classification system for non-mass abnormalities to be applied in addition to the conventional concept of masses, to facilitate detecting ductal carcinoma in situ (DCIS) lesions. The aim of this study was to confirm the utility of this system and to clarify the distribution of these findings in DCIS lesions. Data on 705 surgically treated DCIS lesions from 16 institutions in Japan were retrospectively reviewed. All 705 DCIS lesions could be classified according to the JABTS classification system. The most frequent findings were hypo-echoic areas in the mammary gland (48.6%), followed by solid masses (28.0%) and duct abnormalities (10.2%) or mixed masses (8.1%). Distortion (1.3%), clustered microcysts (1.4%) and echogenic foci without a hypo-echoic area (2.5%) were uncommon. These results suggest that the concept of non-mass abnormalities is useful in detecting DCIS lesions.

Sonographic and pathologic image analysis of pure mucinous carcinoma of the breast.

The aims of this study were to elucidate sonographic and histologic features of pure mucinous carcinoma (P-MC) of the breast using quantitative analysis and to evaluate the relationship between quantitative analysis and visual qualitative assessment. Eleven P-MCs (nine patients) were evaluated qualitatively and quantitatively. Three experts assessed these sonographic images using the Breast Imaging Reporting and Data System (BI-RADS) lexicon. For assessment of internal echoes and posterior echoes, quantitative measures were determined using ImageJ software. Histologic thin sections were stained for classification into separate parts of the tumor (stroma, mucin and cancer cells) and were digitized. Internal echoes were isoechoic in 7 of 11 (63.6%) tumors and hypoechoic in 4 of 11 (36.4%); all P-MCs were "enhanced" in qualitative evaluation. As internal echoes increased, the proportion of stroma increased and that of mucin decreased. The high level of internal echoes is correlated with reflection and back-scattering, which are caused mainly by the interface between mucin and stroma.

Effect of the menstrual cycle on background parenchymal enhancement in breast MR imaging.

PURPOSE: We assessed the influence of the menstrual cycle on background parenchymal enhancement (BPE) of the breast in the early and delayed phases of dynamic magnetic resonance (MR) imaging and the optimal timing of MR imaging of the breast in Japanese women. MATERIAL AND METHODS: We reviewed dynamic MR images of 165 consecutive women with regular menstrual cycles and divided the women into 4 groups by week of the menstrual cycle: 32 in Week One (Days 1 through 4 of the menstrual cycle); 46 in Week 2 (Days 5 through 12); 49 in Week 3 (Days 13 through 20); and 38 in Week 4 (Days 21 through 30). We qualitatively evaluated BPE of the whole breast in the early and delayed phases of MR imaging; categorized enhancement as minimal, mild, moderate, or marked; and calculated the rate at which signal intensity increased (=SI post-SI pre/SI pre) in regions of interest in from the early and delayed phase to the before contrast administration phase to assess BPE quantitatively. RESULTS: In both the early and delayed dynamic MR phases, BPE was significantly more extensive and stronger in Week 4 than Week 2 (P<0.01). Throughout the menstrual cycle, BPE was significantly stronger in the delayed phase than in the early phase in both qualitative (Week One, P=0.0002; Weeks 2 through 4, P<0.0001) and quantitative (Weeks One through 4, P<0.0001) assessments. CONCLUSION: The optimal time to perform dynamic breast MR imaging in premenopausal Japanese women was during Days 5 through 12 of the menstrual cycle.