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There are few radiogenomic studies to correlate ultrasound features of breast cancer with genomic changes. We investigated whether vascular ultrasound phenotypes are associated with breast cancer gene profiles for predicting angiogenesis and prognosis. We prospectively correlated quantitative and qualitative features of microvascular ultrasound (vascular index, vessel morphology, distribution, and penetrating vessel) and contrast-enhanced ultrasound (time–intensity curve parameters and enhancement pattern) with genomic characteristics in 31 breast cancers. DNA obtained from breast tumors and normal tissues were analyzed using targeted next-generation sequencing of 105 genes. The single-variant association test was used to identify correlations between vascular ultrasound features and genomic profiles. Chi-square analysis was used to detect single nucleotide polymorphisms (SNPs) associated with ultrasound features by estimating p values and odds ratios (ORs). Eight ultrasound features were significantly associated with 9 SNPs (p ERBB2 (p = 0.04, OR = 7.75); large area under the curve on contrast-enhanced ultrasound with rs35597368 in PDGFRA (p = 0.04, OR = 4.07); high peak intensity with rs35597368 in PDGFRA (p = 0.049, OR = 4.05) and rs2305948 in KDR (p = 0.04, OR = 5.10); and long mean transit time with rs2275237 in ARNT (p = 0.02, OR = 10.25) and rs755793 in FGFR2 (p = 0.02, OR = 10.25). We identified 198 non-silent SNPs in 71 various cancer-related genes. Vascular ultrasound features can reflect genomic changes associated with angiogenesis and prognosis in breast cancer.

Background: Tumor heterogeneity and vascularity can be noninvasively quantified using histogram and perfusion analyses on computed tomography (CT) and magnetic resonance imaging (MRI). We compared the association of histogram and perfusion features with histological prognostic factors and progression-free survival (PFS) in breast cancer patients on low-dose CT and MRI. Methods: This prospective study enrolled 147 women diagnosed with invasive breast cancer who simultaneously underwent contrast-enhanced MRI and CT before treatment. We extracted histogram and perfusion parameters from each tumor on MRI and CT, assessed associations between imaging features and histological biomarkers, and estimated PFS using the Kaplan–Meier analysis. Results: Out of 54 histogram and perfusion parameters, entropy on T2- and postcontrast T1-weighted MRI and postcontrast CT, and perfusion (blood flow) on CT were significantly associated with the status of subtypes, hormone receptors, and human epidermal growth factor receptor 2 (p < 0.05). Patients with high entropy on postcontrast CT showed worse PFS than patients with low entropy (p = 0.053) and high entropy on postcontrast CT negatively affected PFS in the Ki67-positive group (p = 0.046). Conclusions: Low-dose CT histogram and perfusion analysis were comparable to MRI, and the entropy of postcontrast CT could be a feasible parameter to predict PFS in breast cancer patients.

Objective To determine survival outcomes in women with breast cancer detected at combined screening with breast MRI and mammography versus screening mammography alone. Methods This is an institutional review board-approved retrospective study, and the need for informed consent was waived. A total of 3002 women with an increased risk of breast cancer were screened between 2001 and 2004. Of the 3002 women, 1534 (51.1%) had 2780 combined screenings (MRI and mammography) and 1468 (48.9%) had 4811 mammography-only screenings. The Χ2 test and the Kaplan-Meier method were used to compare cancer detection rates and survival rates. Results The overall cancer detection rate was significantly higher in the MRI plus mammography group compared with the mammography-only group (1.4% [40 of 2780] vs 0.5% [23 of 4811]; P < 0.001). No interval cancers occurred in the MRI plus mammography group, whereas 9 interval cancers were found in the mammography-only group. During a median follow-up of 10.9 years (range: 0.7 to 15.2), a total of 11 recurrences and 5 deaths occurred. Of the 11 recurrences, 6 were in the MRI plus mammography group and 5 were in the mammography-only group. All five deaths occurred in the mammography-only group. Disease-free survival showed no statistically significant difference between the two groups (P = 0.32). However, overall survival was significantly improved in the MRI plus mammography group (P = 0.002). Conclusion Combined screening with MRI and mammography in women at elevated risk of breast cancer improves cancer detection and overall survival.

PURPOSE: To determine preoperative magnetic resonance imaging (MRI) features associated with positive or close margins in patients with breast cancer who underwent breast-conserving surgery (BCS). MATERIALS AND METHODS: A retrospective review identified 249 patients with invasive ductal carcinoma (IDC) who underwent preoperative MRI and BCS as a primary procedure between 2008 and 2010. The MR images were reviewed for descriptions of findings with no new interpretations made. Margins were defined as positive (tumor touching the inked specimen margin), close (< 2 mm tumor-free margin), or negative (≥ 2 mm tumor-free margin). Multivariate logistic regression analysis was performed to evaluate imaging and clinical factors predictive of positive or close margins. RESULTS: Of the 249 patients, 83 (33.3%) had positive or close margins and 166 (66.7%) had negative margins on the initial BCS specimen. Multivariate analysis showed that multifocal disease (odds ratio, 4.8; 95% CI, 1.9–12.2; p = 0.001), nonmass enhancement lesion (odds ratio, 3.0; 95% CI, 1.5–6.2, p = 0.003), greater background parenchymal enhancement (odds ratio, 2.5; 95% CI, 1.1–5.6; p = 0.023), larger lesion size (odds ratio, 1.3; 95% CI, 1.0–1.7, p = 0.032), and presence of ductal carcinoma in situ on needle biopsy (odds ratio, 2.4; 95% CI, 1.3–4.6; p = 0.008) were independent predictors of positive or close margins. CONCLUSIONS: Multifocal disease, nonmass enhancement lesion, or greater background parenchymal enhancement on preoperative breast MRI were significantly associated with positive or close margins. Identifying these MRI features before surgery can be helpful to reduce the reoperation rate in BCS.

To compare the diagnostic performances of tomosynthesis and ultrasonography as adjunctives to digital mammography in women with dense breasts.A total of 778 women with dense breasts underwent digital mammography with tomosynthesis and ultrasonography for screening and diagnostic purposes. The findings of tomosynthesis and ultrasonography were evaluated independently. The primary endpoint was overall diagnostic accuracy determined by area under the receiver operating characteristic curve (AUC). Secondary endpoints included sensitivity, specificity, and predictive values.Of the 778 participants, 698 women (140 breast cancers) were included in the analysis. Based on the AUC findings, the non-inferiority of tomosynthesis to ultrasonography was established in the overall group as well as in all subgroups except for that comprising women with extremely dense breast composition. There were no significant differences in AUC between tomosynthesis and ultrasonography among asymptomatic participants and participants who underwent imaging for screening (0.912 vs. 0.934 [P = 0.403] and 0.987 vs. 0.950 [P = 0.270], respectively). Tomosynthesis exhibited lower sensitivity (91.4 vs. 96.4%; P = 0.039), and higher specificity (83.9 vs. 70.4%; P 0.001) and positive predictive value (58.7 vs. 45.0%; P 0.001) than ultrasonography.Tomosynthesis exhibits comparable performance to ultrasonography as an adjunct to mammography for diagnosis of breast cancer, except among women with extremely dense breasts.

To retrospectively investigate the reasons for and features of undiagnosed cancers at previous supplemental screening ultrasonography (US) in women who subsequently received a diagnosis of breast cancer.The institutional review board approved this retrospective study and waived the requirement to obtain informed patient consent. The study consisted of 230 women (median age, 49 years; age range, 29-81 years) with 230 pairs of US examinations (prior and subsequent examinations) performed between December 2003 and August 2013 who were found to have cancer (median interval, 12 months; range, 2-24 months). The authors compared the clinical-pathologic features of patients with negative findings on prior images with those of patients with visible findings on prior images. Findings visible at prior US were classified as actionable or underthreshold by means of a blinded review by five radiologists. Lesions classified as Breast Imaging Reporting and Data System category 4 or 5 by fewer than three readers were determined to be underthreshold. Reasons for undiagnosed cancers and their imaging features were analyzed.Among the 230 prior US examinations, 72 (31.3%) showed visible findings and 158 (68.7%) showed negative findings. High-nuclear-grade cancers and triple-negative cancers were more common in patients with negative findings than in those with visible findings (P = .023 and P = .006, respectively). Blinded review revealed that 57 of the 72 visible findings (79%) were actionable. Misinterpretation (39% [28 of 72 lesions]) and multiple distracting lesions (17% [12 of 72 lesions]) were the two most common reasons for missing these actionable findings, which showed more noncircumscribed margins than did underthreshold findings (P = .028).At supplemental screening breast US, close attention should be paid to the presence of a margin that is not circumscribed, and multiple lesions should be separately assessed to reduce the number of missed breast cancers.

Purpose: Breast tissue composition is considered to be associated with breast cancer risk. This study aimed to develop a computer-aided classification (CAC) system to automatically classify echotexture patterns as heterogeneous or homogeneous using automated breast ultrasound (ABUS) images. Methods: A CAC system was proposed that can recognize breast echotexture patterns in ABUS images. For each case, the echotexture pattern was assessed by two expert radiologists and classified as heterogeneous or homogeneous. After neutrosophic image transformation and fuzzy c-mean clusterings, the lower and upper boundaries of the fibroglandular tissues were defined. Then, the number of hypoechoic regions and histogram features were extracted from the fibroglandular tissues, and the support vector machine model with the leave-one-out cross-validation method was utilized as the classifier. The authors’ database included a total of 208 ABUS images of the breasts of 104 females. Results: The accuracies of the proposed system for the classification of heterogeneous and homogeneous echotexture patterns were 93.48% (43/46) and 92.59% (150/162), respectively, with an overall Az (area under the receiver operating characteristic curve) of 0.9786. The agreement between the radiologists and the proposed system was almost perfect, with a kappa value of 0.814. Conclusions: The use of ABUS and the proposed method can provide quantitative information on the echotexture patterns of the breast and can be used to evaluate whether breast echotexture patterns are associated with breast cancer risk in the future.

Purpose: Triple-negative breast cancer (TNBC), an aggressive subtype, is frequently misclassified as fibroadenoma due to benign morphologic features on breast ultrasound (US). This study aims to develop a computer-aided diagnosis (CAD) system based on texture features for distinguishing between TNBC and benign fibroadenomas in US images. Methods: US images of 169 pathology-proven tumors (mean size, 1.65 cm; range, 0.7–3.0 cm) composed of 84 benign fibroadenomas and 85 TNBC tumors are used in this study. After a tumor is segmented out using the level-set method, morphological, conventional texture, and multiresolution gray-scale invariant texture feature sets are computed using a best-fitting ellipse, gray-level co-occurrence matrices, and the ranklet transform, respectively. The linear support vector machine with leave-one-out cross-validation schema is used as a classifier, and the diagnostic performance is assessed with receiver operating characteristic curve analysis. Results: The Az values of the morphology, conventional texture, and multiresolution gray-scale invariant texture feature sets are 0.8470 [95% confidence intervals (CIs), 0.7826–0.8973], 0.8542 (95% CI, 0.7911–0.9030), and 0.9695 (95% CI, 0.9376–0.9865), respectively. The Az of the CAD system based on the combined feature sets is 0.9702 (95% CI, 0.9334–0.9882). Conclusions: The CAD system based on texture features extracted via the ranklet transform may be useful for improving the ability to discriminate between TNBC and benign fibroadenomas.

Background and objectives Axillary lymph node (ALN) status is a key indicator in assessing and determining the treatment strategy for patients with newly diagnosed breast cancer. Previous studies suggest that sonographic features of a primary tumor have the potential to predict ALN status in the preoperative staging of breast cancer. In this study, a computer-aided prediction (CAP) model as well as the tumor features for ALN metastasis in breast cancers were developed using breast ultrasound (US) images. Methods A total of 249 malignant tumors were acquired from 247 female patients (ages 20–84 years; mean 55 ± 11 years) to test the differences between the non-metastatic (130) and metastatic (119) groups based on various features. After applying semi-automatic tumor segmentation, 69 quantitative features were extracted. The features included morphology and texture of tumors inside a ROI of breast US image. By the backward feature selection and linear logistic regression, the prediction model was constructed and established to estimate the likelihood of ALN metastasis for each sample collected. Results In the experiments, the texture features showed higher performance for predicting ALN metastasis compared to morphology (Az, 0.730 vs 0.667). The difference, however, was not statistically significant (p-values > 0.05). Combining the textural and morphological features, the accuracy, sensitivity, specificity, and Az value achieved 75.1% (187/249), 79.0% (94/119), 71.5% (93/130), and 0.757, respectively. Conclusions The proposed CAP model, which combines textural and morphological features of primary tumor, may be a useful method to determine the ALN status in patients with breast cancer.

Background Most patients with early-stage breast cancer have clinically negative lymph nodes (LNs). However, 15–20% of patients have axillary nodal metastasis based on the sentinel LN biopsy. Purpose To assess whether ultrasound (US) features of a primary tumor are associated with axillary LN metastasis in patients with clinical T1–T2N0 breast cancer. Material and Methods This retrospective study included 138 consecutive patients (median age = 51 years; age range = 27–78 years) who underwent breast surgery with axillary LN evaluation for clinically node-negative T1–T2 breast cancer. Three radiologists blinded to the axillary surgery results independently reviewed the US images. Tumor distance from the skin and distance from the nipple were determined based on the US report. Association between US features of a breast tumor and axillary LN metastasis was assessed using a multivariate logistic regression model after controlling for clinicopathologic variables. Results Of the 138 patients, 28 (20.3%) had nodal metastasis. At univariate analysis, tumor distance from the skin ( P = 0.019), tumor size on US ( P = 0.023), calcifications ( P = 0.036), architectural distortion ( P = 0.001), and lymphovascular invasion ( P = 0.049) were associated with axillary LN metastasis. At multivariate analysis, shorter skin-to-tumor distance (odds ratio [OR] = 4.15; 95% confidence interval [CI] = 1.01–16.19; P = 0.040) and masses with associated architectural distortion (OR = 3.80; 95% CI = 1.57–9.19; P = 0.003) were independent predictors of axillary LN metastasis. Conclusion US features of breast cancer can be promising factors associated with axillary LN metastasis in patients with clinically node-negative early-stage breast cancer.

Background Locoregional recurrence (LRR) following breast conservation therapy (BCT) is associated with an increased risk of distant metastasis and death in patients with breast cancer. Purpose To investigate whether preoperative breast magnetic resonance imaging (MRI) features are associated with the risk of LRR in patients undergoing BCT. Material and Methods A total of 3781 women with primary invasive breast cancer underwent preoperative MRI and BCT between 2003 and 2013. Forty-eight patients who developed LRR comprised the LRR cohort and one-to-one matching (age, tumor stage, grade, and axillary nodal status) of each patient to a control participant was performed in patients who did not develop recurrence. Three readers independently reviewed MR images of the index cancer and the presence of multifocal disease was assessed. Χ2 analysis was used to compare imaging and clinical features between LRR and control cohorts, with multivariate logistic regression analysis used to identify independent features. Results Significant differences were found in the proportion of multifocal disease ( P = 0.001), background parenchymal enhancement level ( P = 0.007), and breast cancer molecular subtype ( P = 0.01) between LRR and control cohorts. Multivariate analysis showed that multifocal disease (odds ratio [OR] = 11.9; 95% confidence interval [CI] = 1.4–102.5; P = 0.02) and human epidermal growth factor receptor 2-positive subtype (OR = 12.7; 95% CI = 1.3–127.6; P = 0.03) were both independently associated with LRR. Conclusion Multifocal disease on preoperative breast MRI may indicate an increased risk of LRR in patients treated with BCT.

Importance Younger women (aged ≤50 years) who underwent breast conservation therapy may benefit from breast magnetic resonance imaging (MRI) screening as an adjunct to mammography. Objective To prospectively determine the cancer yield and tumor characteristics of combined mammography with MRI or ultrasonography screening in women who underwent breast conservation therapy for breast cancers and who were 50 years or younger at initial diagnosis. Design, Setting, and Participants This multicenter, prospective, nonrandomized study was conducted from December 1, 2010, to January 31, 2016, at 6 academic institutions. Seven hundred fifty-four women who were 50 years or younger at initial diagnosis and who had undergone breast conservation therapy for breast cancer were recruited to participate in the study. Reference standard was defined as a combination of pathology and 12-month follow-up. Interventions Participants underwent 3 annual MRI screenings of the conserved and contralateral breasts in addition to mammography and ultrasonography, with independent readings. Main Outcomes and Measures Cancer detection rate, sensitivity, specificity, interval cancer rate, and characteristics of detected cancers. Results A total of 754 women underwent 2065 mammograms, ultrasonography, and MRI screenings. Seventeen cancers were diagnosed, and most of the detected cancers (13 of 17 [76%]) were stage 0 or stage 1. Overall cancer detection rate (8.2 vs 4.4 per 1000; P = .003) or sensitivity (100% vs 53%; P = .01) of mammography with MRI was higher than that of mammography alone. After the addition of ultrasonography, the cancer detection rate was higher than that by mammography alone (6.8 vs 4.4 per 1000; P = .03). The specificity of mammography with MRI or ultrasonography was lower than that by mammography alone (87% or 88% vs 96%; P Conclusions and Relevance After breast conservation therapy in women 50 years or younger, the addition of MRI to annual mammography screening improves detection of early-stage but biologically aggressive breast cancers at acceptable specificity. Results from this study can inform patient decision making on screening methods after breast conservation therapy.

Our aim was to determine whether triple-negative breast cancers (TNBCs) with and without androgen receptor (AR) expression have distinguishing imaging features on mammography, breast ultrasound (US), and magnetic resonance (MR) imaging.AR expression was assessed immunohistochemically in 125 patients with TNBC from a consecutive series of 1,086 operable invasive breast cancers. Two experienced radiologists blinded to clinicopathological findings reviewed all imaging studies in consensus using the BI-RADS lexicon. The imaging and pathological features of 33 AR-positive TNBCs were compared with those of 92 AR-negative TNBCs.The presence of mammographic calcifications with or without a mass (p 0.001), non-mass enhancement on MR imaging (p 0.001), and masses with irregular shape or spiculated margins on US (p 0.001 and p = 0.002) and MR imaging (p = 0.001 and p 0.001) were significantly associated with AR-positive TNBC. Compared with AR-negative TNBC, AR-positive TNBC was more likely to have a ductal carcinoma in situ component (59.8% vs. 90.9%, p = 0.001) and low Ki-67 expression (30.4% vs. 51.5%, p = 0.030).AR-positive and AR-negative TNBCs have different imaging features, and certain imaging findings can be useful to predict AR status in TNBC.• Triple-negative breast cancers have distinguishing imaging features according to AR expression. • AR-positive TNBC is associated with calcifications, spiculated masses, and non-mass enhancement. • Multimodality imaging can help predict androgen receptor status in TNBC.

To retrospectively investigate whether the background parenchymal features around a tumor at preoperative dynamic contrast material-enhanced magnetic resonance (MR) imaging are associated with ipsilateral breast tumor recurrence (IBTR)-free survival in patients with ductal carcinoma in situ (DCIS) after breast conservation surgery.The institutional review board approved this study, and the requirement for informed consent was waived. Between 2004 and 2009, 215 consecutive women with pure DCIS who had undergone preoperative dynamic contrast-enhanced MR imaging and curative breast conservation surgery were identified. Clinical-pathologic features (age, menopausal status, presentation of clinical findings, biopsy method, tumor size, nuclear grade, hormonal receptor status, margin status, and adjuvant therapy) and MR imaging features (lesion size, background parenchymal enhancement grade, fibroglandular density, parenchymal signal enhancement ratio [SER] around the tumor, lesion type, and lesion kinetics) were analyzed. A Cox proportional hazards model was used to determine the association between MR imaging variables and IBTR-free survival after controlling for clinical-pathologic variables. Reproducibility of SER measurements was evaluated by using the intraclass correlation coefficient.There were 15 of 215 (7.0%) IBTR cases (nine DCIS cases and six invasive cases) at a median of 36 months (range, 11-61 months). Multivariate analysis showed that higher parenchymal SER (hazard ratio [HR] = 2.028, P.001 for reader 1; HR = 1.652, P.001 for reader 2) and larger histologic tumor size (HR = 1.360, P = .009 for reader 1; HR = 1.402, P = .006 for reader 2) were independent factors associated with worse IBTR-free survival. The intraclass correlation coefficient of SER measurements between two readers was 0.852 (95% confidence interval: 0.811, 0.885).Higher parenchymal SER around the tumor at preoperative dynamic contrast-enhanced MR imaging and larger histologic tumor size were independent factors associated with worse IBTR-free survival in patients with DCIS after breast conservation surgery.

To retrospectively review the mammograms of women with breast cancers detected at screening ultrasonography (US) to determine the reasons for nondetection at mammography.This study received institutional review board approval, and informed consent was waived. Between 2003 and 2011, a retrospective database review revealed 335 US-depicted cancers in 329 women (median age, 47 years; age range, 29-69 years) with Breast Imaging Reporting and Data System breast density type 2-4. Five blinded radiologists independently reviewed the mammograms to determine whether the findings on negative mammograms should be recalled. Three unblinded radiologists re-reviewed the mammograms to determine the reasons for nondetection by using the reference location of the cancer on mammograms obtained after US-guided wire localization or breast magnetic resonance imaging. The number of cancers recalled by the blinded radiologists were compared with the reasons for nondetection determined by the unblinded radiologists.Of the 335 US-depicted cancers, 63 (19%) were recalled by three or more of the five blinded radiologists, and 272 (81%) showed no mammographic findings that required immediate action. In the unblinded repeat review, 263 (78%) cancers were obscured by overlapping dense breast tissue, and nine (3%) were not included at mammography owing to difficult anatomic location or poor positioning. Sixty-three (19%) cancers were considered interpretive errors. Of these, 52 (82%) were seen as subtle findings (46 asymmetries, six calcifications) and 11 (18%) were evident (six focal asymmetries, one distortion, four calcifications).Most breast cancers (81%) detected at screening US were not seen at mammography, even in retrospect. In addition, 19% had subtle or evident findings missed at mammography.

Rapid volume density analysis (RVDA) for automated breast ultrasound (ABUS) has been proposed as a more efficient method for estimating breast density. In the current experiment, ABUS images were obtained for 67 breasts from 40 patients. For each case, three rectangular volumes of interest (VOIs) were extracted, including the VOIs located at the 6 and 12 o’clock positions relative to the nipple in the anterior to posterior pass and the lateral position relative to the nipple in the lateral pass. The centers of these VOIs were defined to align with the center of nipple, and the depths reached the retromammary fat boundary. The fuzzy c-means classifier was applied to differentiate the fibroglandular and fat tissues to estimate the density. The classification results of the three VOIs were averaged to obtain the breast density. The density correlations between the RVDA and the ABUS methods were 0.98 and 0.96 using Pearson’s correlation and linear regression coefficients, respectively. The average computation times for RVDA and ABUS were 4.2 and 17.8 seconds, respectively, using an Intel® Core™2 2.66 GHz computer with 3.25 GB memory. In conclusion, the RVDA method offers a quantitative and efficient breast density estimation for ABUS.

To evaluate whether tumour stiffness on sonoelastography is associated with axillary nodal metastasis in T1 breast carcinoma patients. Between May 2006 and December 2010, 200 consecutive women (mean age, 51.6; range, 27 – 81 years) who underwent B-mode ultrasound (US), sonoelastography, and curative surgery with axillary nodal evaluation for clinically node negative T1 breast carcinomas (mean invasive tumour size, 12.4; range, 3 – 20 mm at pathology) were identified. The association between the elasticity score of the tumour and histopathological axillary nodal status was evaluated using a logistic regression model after controlling for imaging and clinicopathological variables of the tumour. The overall incidence of axillary nodal metastasis was 15.5 % (31 of 200). Axillary nodal metastasis was significantly more frequent in tumours with elasticity scores ≥4 than in tumours with elasticity scores 10 mm (OR, 5.98; P = 0.022), and lymphovascular invasion (OR, 10.68; P < 0.001) of tumours were independently associated with axillary nodal metastasis. Tumour stiffness on sonoelastography is independently associated with axillary nodal metastasis in T1 breast carcinoma patients. • Prediction of axillary nodal status using imaging techniques is valuable. • High ultrasound elasticity scores of T1 tumours were associated with axillary metastasis • Node-positive T1 tumours frequently had elasticity scores 4 or 5. • Sonoelastography might render axillary surgery unnecessary in T1 breast carcinoma patients.

To evaluate the correlation between stiffness values obtained by shear-wave elastography (SWE) and breast cancer subtypes. This was an institutional review board-approved retrospective study with a waiver of informed consent. The stiffness of 337 invasive breast cancers in 337 women was evaluated by SWE and mean stiffness values (kPa) and qualitative colour scores (1–5) of tumours were obtained. The results were analysed according to BI-RADS category, tumour size, grade and tumour subtype (triple-negative [TN], human epidermal growth factor receptor 2 [HER2]-positive, and oestrogen receptor [ER]-positive) using a multiple linear regression analysis. The mean stiffness values and colour scores were: 146.8 kPa ± 57.0 and 4.1 ± 1.1; 165.8 kPa ± 48.5 and 4.6 ± 0.7 for TN tumours (n = 64), 160.3 kPa ± 56.2 and 4.3 ± 1.0 for HER2-positive tumours (n = 55) and 136.9 kPa ± 57.2 and 4.0 ± 1.1 for ER-positive tumours (n = 218; P < 0.0001). All three breast cancers classified as BI-RADS category 3 on B-mode ultrasound were TN subtype. A multiple linear regression analysis revealed that tumour size, histological grade and tumour subtype were independent factors that influenced the stiffness values. High stiffness values correlated with aggressive subtypes of breast cancer. • Shear-wave elastography is increasingly used to measure the stiffness of breast tumours. • Triple-negative and HER2-positive tumours showed greater stiffness than ER-positive tumours. • All breast cancers classified as BI-RADS 3 on B-mode ultrasound were triple-negative subtype. • Tumour size, histological grade and subtype were independent factors influencing SWE stiffness.

Ultrasonographic (US) assessment of breast density has the potential to provide a nonionizing method. This study was to prospectively evaluate intermodality and interobserver agreements for assessment of breast density between US and mammography. Institutional review board approval was obtained. Forty-one women (mean 52.1 years; range 25-72 years) with variable breast density consented to participate. Eight radiologists blinded to mammographic information performed breast US for all participants and assessed each breast density using four categories based on the proportion of the breast occupied by the fibroglandular tissue. All participants underwent full-field digital mammography and mammographic density was independently assessed by eight radiologists 2 weeks after US using the breast imaging reporting and data system (BI-RADS) 4-category system. Intermodality agreements between US and mammographic assessments and interobserver agreements among radiologists were assessed using kappa statistics (к) and intraclass correlation coefficients (ICCs). There was substantial intermodality agreement between the US and mammographic assessments of breast density (к = 0.65 and ICC = 0.80), and 68 % (222/328) of the assessments had exact agreement. When categories were dichotomized into fatty (categories 1 and 2) and dense (categories 3 and 4), 86 % (282/328) of the assessments had exact agreement (к = 0.71). The interobserver agreement for the US assessments of breast density was substantial (average к = 0.63, ICC = 0.82) and not significantly different from that for the mammographic assessments (average к = 0.74, ICC = 0.85) (P = 0.701). US and mammography demonstrated substantial intermodality and interobserver agreement for assessment of breast density.

Purpose To investigate whether pretreatment breast magnetic resonance (MR) imaging features are associated with pathologic complete response (PCR) and recurrence-free survival after neoadjuvant chemotherapy (NAC) in patients with triple-negative breast cancer. Materials and Methods Identified were 132 patients with primary triple-negative breast cancers who underwent NAC and pretreatment MR imaging between 2004 and 2010. Three breast radiologists independently reviewed the MR images based on the 2013 Breast Imaging Reporting and Data System lexicon. Presence of intratumoral high signal intensity and peritumoral edema on T2-weighted images was also evaluated. Association of PCR and recurrence-free survival with MR imaging features was assessed by using logistic regression and Cox regression. Bonferroni correction was applied to the P values. Results Among 132 patients, 18 (14%) underwent PCR. Round or oval masses (odds ratio, 3.5 [95% confidence interval: 1.3, 9.7]; P = .02), the absence of intratumoral T2 high signal intensity (odds ratio, 3.8 [95% confidence interval: 1.3, 11.0]; P = .01), and the absence of peritumoral edema (odds ratio, 3.4 [95% confidence interval: 1.2, 9.5]; P = .02) were associated with PCR, but not significantly. After 54 months of median follow-up, there were 41 (31% [41 of 132]) breast cancer recurrences. Peritumoral edema was the only significant variable associated with worse recurrence-free survival (hazard ratio, 4.9 [95% confidence interval: 1.9, 12.6]; P = .001). Conclusion Pretreatment MR imaging features may be associated with PCR and recurrence-free survival in patients with triple-negative breast cancer. © RSNA, 2016 Online supplemental material is available for this article.

Background Human epidermal growth factor receptor 2-positive (HER2+) breast cancer has two distinct subtypes according to hormone receptor (HR) status. Survival, pattern of recurrence, and treatment response differ between HR–/HER2+ and HR+/HER2+ cancers. Purpose To investigate imaging and clinicopathologic features of HER2+ cancers and their correlation with HR expression. Material and Methods Between 2011 and 2013, 252 consecutive patients with 252 surgically confirmed HER2+ cancers (125 HR– and 127 HR+) were included. Two experienced breast radiologists blinded to the clinicopathologic findings reviewed the mammograms and magnetic resonance (MR) images using the BI-RADS lexicon. Tumor kinetic features were acquired by computer-aided detection (CAD). The imaging and clinicopathologic features of 125 HR–/HER2+ cancers were compared with those of 127 HR+/HER2+ cancers. Association between the HR status and each feature was assessed. Results Multiple logistic regression analysis showed that circumscribed mass margin (odds ratio [OR], 4.73; P Conclusion HER2+ breast cancers have different MR imaging (MRI) phenotypes and clinicopathologic feature according to HR status. MRI features related to HR and HER2 status have the potential to be used for the diagnosis and treatment decisions in HER2+ breast cancer patients.

Purpose To determine additional cancer yield of magnetic resonance (MR) imaging in women with breast cancer detected at screening ultrasonography (US) and to identify a subgroup of women who are likely to benefit from preoperative MR imaging. Materials and Methods This study was approved by the institutional review board, and the requirement for informed consent was waived. A retrospective review of 374 women (median age, 48 years; age range, 30-74 years) with breast cancer detected at screening US (invasive, n = 321) who underwent preoperative breast MR imaging between 2007 and 2013 was performed. Cancer yield and positive predictive value of biopsy were calculated. Multivariate logistic regression analysis was performed to identify clinical-pathologic features associated with additional cancer detected at MR imaging. Results Of 374 women, 21 (5.6%; 95% confidence interval [CI]: 3.5%, 8.5%) were diagnosed with additional cancer (positive predictive value of biopsy, 42.0% [21 of 50 women]; 95% CI: 28%, 57%). Index invasive lobular cancer (ILC) histologic type was significantly associated with additional cancer detected at MR imaging (odds ratio, 4.0; 95% CI: 1.2, 13.6; P = .03). In women with index invasive cancer, premenopausal status (odds ratio, 5.7; 95% CI: 1.2, 35.8; P = .03) and lobular histologic type (odds ratio, 3.9; 95% CI: 1.1, 12.3; P = .03) were factors associated with additional cancer detected at MR imaging. Conclusion Preoperative MR imaging helped to detect additional sites of cancer in 5.6% of women with breast cancer detected at screening US. Women with index ILC and premenopausal women are more likely to benefit from preoperative MR imaging.

The shear wave elastography (SWE) uses the acoustic radiation force to measure the stiffness of tissues and is less operator dependent in data acquisition compared to strain elastography. However, the reproducibility of the result is still interpreter dependent. The purpose of this study is to develop a computer-aided diagnosis (CAD) method to differentiate benign from malignant breast tumors using SWE images. After applying the level set method to automatically segment the tumor contour and hue-saturation-value color transformation, SWE features including average tissue elasticity, sectional stiffness ratio, and normalized minimum distance for grouped stiffer pixels are calculated. Finally, the performance of CAD based on SWE features are compared with those based on B-mode ultrasound (morphologic and textural) features, and a combination of both feature sets to differentiate benign from malignant tumors. In this study, we use 109 biopsy-proved breast tumors composed of 57 benign and 52 malignant cases. The experimental results show that the sensitivity, specificity, accuracy and the area under the receiver operating characteristic ROC curve (Az value) of CAD are 86.5%, 93.0%, 89.9%, and 0.905 for SWE features whereas they are 86.5%, 80.7%, 83.5% and 0.893 for B-mode features and 90.4%, 94.7%, 92.3% and 0.961 for the combined features. The Az value of combined feature set is significantly higher compared to the B-mode and SWE feature sets (p=0.0296 and p=0.0204, respectively). Our results suggest that the CAD based on SWE features has the potential to improve the performance of classifying breast tumors with US.

Background Although digital breast tomosynthesis (DBT) is an emerging technique yielding higher sensitivity and specificity compared to digital mammography (DM) alone, relative contribution of prior mammograms on the interpretation of DBT combined with DM has not been investigated. Purpose To retrospectively compare the diagnostic performances of DM, DM + DBT, and DM + DBT with prior mammograms. Material and Methods Three breast radiologists independently reviewed images of 116 patients with 24 cancers in the sequential order of DM, DM + DBT, and DM + DBT with prior mammograms using Breast Imaging Reporting and Data System (BI-RADS) assessment categories. Results The average areas under the receiver operating characteristic curve (AUC) of DM, DM + DBT, and DM + DBT with prior mammograms were 0.712, 0.777, and 0.816, respectively. Adding prior mammograms did not significantly affect the AUC of DM + DBT ( P = 0.108), whereas adding DBT significantly increased the AUC of DM ( P = 0.009). Sensitivity for DM, DM + DBT, and DM + DBT with prior mammograms was 58.3%, 69.4%, and 69.4%, and specificities were 84.1%, 85.9%, and 93.8%, respectively. Addition of DBT significantly increased the sensitivity ( P = 0.0090) of DM. Prior mammograms significantly improved the specificity of DM + DBT ( P = 0.0004), whereas adding prior mammogram did not affect sensitivity of DM + DBT ( P = 1.000). Conclusion DBT significantly increases the overall sensitivity and diagnostic performance of DM. Prior mammograms significantly increase the specificity of DM + DBT but have no significant effect on sensitivity and overall diagnostic performance.

Objectives To evaluate the diagnostic performance and radiation dose of single view cranio-caudal (CC) digital mammography (DM) plus mediolateral oblique (MLO) digital breast tomosynthesis (DBT) combined with synthesized mammography (SM) in comparison with two-view DM with or without DBT. Material and methods This study was approved by our institutional review board, and informed consent was obtained from 130 women. Paired two-view DM and single MLO-DBT with SM images were acquired, and four independent retrospective reading sessions of different combinations of DM, SM and DBT were performed for the presence of malignant tumors using jackknife alternative free-response receiver operator curve (JAFROC) methods. The diagnostic performances and average glandular dose (AGD) were compared between different combinations of DM, SM and DBT. Results Of 159 lesions in 130 patients, 27 were malignant. When using MLO-DBT with SM instead of MLO-DM, a significantly higher sensitivity ( P = 0.016) and specificity ( P = 0.012) were noted than with two-view DM, and comparable figure of merit (FOM), sensitivity, and specificity to two-view DM with DBT were noted. The mean AGD of CC-DM plus MLO-DBT with SM was 5.78mGy ± 1.06 per patient, which was significantly lower than that with two-view DM with MLO-DBT (8.45mGy ± 1.32; P Conclusion s The combined use of CC-DM plus MLO-DBT with SM showed higher sensitivity and specificity to two-view DM with a smaller AGD increment and comparable diagnostic performance to that of two-view DM with MLO-DBT with a significantly lower mean AGD.

Background Unexpected focal 18F-FDG breast uptakes are occasionally identified on PET/CT due to its increased use for cancer staging and follow-up. The need for their characterization has been suggested. Purpose To retrospectively evaluate the diagnostic value of ultrasonography (US) in distinguishing benign from malignant lesions for unexpected focal 18F-FDG uptakes in breast on PET/CT scans. Material and Methods Between April 2004 and January 2010, 27 focal 18F-FDG breast uptakes in 27 patients (age range 33–62 years; mean age 46 years) among 5214 patients who had undergone PET/CT scans were retrospectively analyzed. The American College of Radiology (ACR) Breast Imaging-Reporting and Data System (BI-RADS) final assessment categories of the US and the maximum standardized uptake values (SUVs) of the lesions were compared between the benign and malignant lesions. Results Of the 27 lesions, 15 (56%) lesions were malignant. The rate of malignancy, according to the final assessment category on the US, was 0% (0 of 6) for category 3, 60% for category 4 (9 of 15), and 100% (6 of 6) for category 5 ( P = 0.001). The US evaluation revealed a sensitivity of 100% (15 of 15) and a specificity of 50% (6 of 12). The average maximum SUV of the malignant lesions was greater than that of the benign lesions (4.12 ± 1.94 vs. 1.94 ± 0.82; P = 0.001). Conclusion US evaluation of unexpected focal 18F-FDG uptakes on PET/CT scans can accurately distinguish benign lesions from malignant lesions.

Screening ultrasound (US) can increase the detection of breast cancer. However, little is known about the clinicopathologic characteristics of breast cancers detected by screening US. A search of the database for patients with breast cancer yielded a dataset in 6837 women who underwent breast surgery at Seoul National University Hospital (Korea). Of 6837 women, 1047 were asymptomatic and had a non-palpable cancer. Two hundred fifty-four women with 256 cancers detected by US (US-detected cancer) and 793 women with 807 cancers detected by mammography (MG-detected cancer) were identified. The imaging, clinicopathologic, and molecular data were reviewed. Univariate and multivariate analyses were carried out. Women with US-detected cancer were younger and were more likely to undergo breast-conserving surgery and to have node-negative invasive cancer (P0.0001). By multivariate analysis, the significant independent characteristics were tumor size, mammographic density, final assessment category according to the American College of Radiology Breast Imaging Reporting and Data System, progesterone receptor (PR), human epidermal growth factor receptor 2 (HER2), and molecular subtype. Compared to tumors that were2 cm in size, tumors that were ≤ 1 cm in size were 2.2-fold more likely to be US-detected cancers (P = 0.02). Compared to the luminal A subtype tumors (estrogen receptor [ER]+, PR+, HER2-), luminal B subtype tumors (ER+, PR+, HER2+) were less likely to be in the US-detected cancer group (P0.01). Women with dense breasts were more likely to have US-detected cancer (P0.01) versus those with non-dense breasts. Screening US-detected cancers were less likely to be diagnosed as category 5 instead of category 4 (P0.01). In conclusion, women with US-detected breast cancer are more likely to have small-sized invasive cancer and more likely associated with the luminal A subtype.

Breast tissue composition is considered to be associated with breast cancer risk. This study aimed to develop a computer-aided classification (CAC) system to automatically classify echotexture patterns as heterogeneous or homogeneous using automated breast ultrasound (ABUS) images.A CAC system was proposed that can recognize breast echotexture patterns in ABUS images. For each case, the echotexture pattern was assessed by two expert radiologists and classified as heterogeneous or homogeneous. After neutrosophic image transformation and fuzzy c-mean clusterings, the lower and upper boundaries of the fibroglandular tissues were defined. Then, the number of hypoechoic regions and histogram features were extracted from the fibroglandular tissues, and the support vector machine model with the leave-one-out cross-validation method was utilized as the classifier. The authors' database included a total of 208 ABUS images of the breasts of 104 females.The accuracies of the proposed system for the classification of heterogeneous and homogeneous echotexture patterns were 93.48% (43/46) and 92.59% (150/162), respectively, with an overall Az (area under the receiver operating characteristic curve) of 0.9786. The agreement between the radiologists and the proposed system was almost perfect, with a kappa value of 0.814.The use of ABUS and the proposed method can provide quantitative information on the echotexture patterns of the breast and can be used to evaluate whether breast echotexture patterns are associated with breast cancer risk in the future.

To determine the imaging and clinical-pathologic factors associated with recurrence in patients with early stage triple-negative breast cancer.This study was approved by the institutional review board, and the requirement to obtain informed consent was waived. The authors evaluated 398 patients with stage I or II triple-negative breast cancer (median age, 48 years; range, 21-81 years) who were treated between January 2003 and December 2008. Data collected included preoperative breast magnetic resonance (MR) images, mammographic density, patient age, symptoms, family history of breast cancer, histologic tumor characteristics, tumor grade, tumor size, lymphovascular invasion, lymph node involvement, surgery type, margin status, and adjuvant treatment received. Multivariate analysis was performed by using a Cox proportional hazards model, and recurrence-free survival was estimated with the adjusted Kaplan-Meier method.Of the 398 patients, 63 (15.8%) had recurrent disease after a median follow-up of 6.1 years. The absence of preoperative MR imaging (hazard ratio [HR] with multivariate analysis = 2.66; 95% confidence interval = 1.49, 4.75; P.001), dense breast tissue (HR = 2.77; 95% confidence interval = 1.39, 5.51; P = .004), family history of breast cancer (HR = 2.32; 95% confidence interval = 1.10, 4.90; P = .028), and lymphovascular invasion (HR = 1.83; 95% confidence interval = 1.11, 3.03; P = .019) were found to be independently associated with recurrence. These same factors were also found to be associated with recurrence-free survival.The absence of preoperative MR imaging and the presence of dense breast tissue at mammography were associated with an increased risk of recurrence in patients with triple-negative breast cancer.

Triple-negative breast cancer (TNBC), an aggressive subtype, is frequently misclassified as fibroadenoma due to benign morphologic features on breast ultrasound (US). This study aims to develop a computer-aided diagnosis (CAD) system based on texture features for distinguishing between TNBC and benign fibroadenomas in US images.US images of 169 pathology-proven tumors (mean size, 1.65 cm; range, 0.7-3.0 cm) composed of 84 benign fibroadenomas and 85 TNBC tumors are used in this study. After a tumor is segmented out using the level-set method, morphological, conventional texture, and multiresolution gray-scale invariant texture feature sets are computed using a best-fitting ellipse, gray-level co-occurrence matrices, and the ranklet transform, respectively. The linear support vector machine with leave-one-out cross-validation schema is used as a classifier, and the diagnostic performance is assessed with receiver operating characteristic curve analysis.The Az values of the morphology, conventional texture, and multiresolution gray-scale invariant texture feature sets are 0.8470 [95% confidence intervals (CIs), 0.7826-0.8973], 0.8542 (95% CI, 0.7911-0.9030), and 0.9695 (95% CI, 0.9376-0.9865), respectively. The Az of the CAD system based on the combined feature sets is 0.9702 (95% CI, 0.9334-0.9882).The CAD system based on texture features extracted via the ranklet transform may be useful for improving the ability to discriminate between TNBC and benign fibroadenomas.

OBJECTIVE To retrospectively evaluate the features of undiagnosed breast cancers on prior screening breast magnetic resonance (MR) images in patients who were subsequently diagnosed with breast cancer, as well as the potential utility of MR-computer-aided evaluation (CAE). MATERIALS AND METHODS Between March 2004 and May 2013, of the 72 consecutive pairs of prior negative MR images and subsequent MR images with diagnosed cancers (median interval, 32.8 months; range, 5.4-104.6 months), 36 (50%) had visible findings (mean size, 1.0 cm; range, 0.3-5.2 cm). The visible findings were divided into either actionable or underthreshold groups by the blinded review by 5 radiologists. MR imaging features, reasons for missed cancer, and MR-CAE features according to actionability were evaluated. RESULTS Of the 36 visible findings on prior MR images, 33.3% (12 of 36) of the lesions were determined to be actionable and 66.7% (24 of 36) were underthreshold; 85.7% (6 of 7) of masses and 31.6% (6 of 19) of non-mass enhancements were classified as actionable lesions. Mimicking physiologic enhancements (27.8%, 10 of 36) and small lesion size (27.8%, 10 of 36) were the most common reasons for missed cancer. Actionable findings tended to show more washout or plateau kinetic patterns on MR-CAE than underthreshold findings, as the 100% of actionable findings and 46.7% of underthreshold findings showed washout or plateau (p = 0.008). CONCLUSION MR-CAE has the potential for reducing the number of undiagnosed breast cancers on screening breast MR images, the majority of which are caused by mimicking physiologic enhancements or small lesion size.

1508 Background: Mammography is the only imaging modality proven to reduce mortality from breast cancer. Over the past decade, magnetic resonance imaging (MRI) screening of women with increased risk of breast cancer ( > 20% cumulative life time risk) has been recommended. However, there is little evidence that supplemental screening with MRI improves survival. The purpose of this study was to compare survival outcomes of combined screening with MRI and mammography to screening mammography alone in women at increased risk for breast cancer. Methods: A total of 3,002 women at increased risk underwent at least two screening rounds between 2001 and 2005, with at least 5 years of follow-up. 1,534 women had combined screening (MRI and mammography), and 1,468 had screening mammography alone. Cancer detection yield and survival were determined in the two groups. Results: 60 women were diagnosed with breast cancer, 38 patients in the combined screening group and 22 in the mammography-only group. Cancer yield was 24.8 per 1000 (95% CI, 17.6-33.8) combined screening and 15.0 per 1000 (95% CI, 9.4-22.6) mammography-only. No interval cancers occurred in women undergoing combined screening, while 9 interval cancers were found in women undergoing only mammography screening. During a median follow-up of 10.8 years (range, 0.7-15.2), a total of 11 recurrences and 5 deaths (4 breast cancer cause and 1 unknown cause) were found. Of the 11 recurrences, 6 were in the combined screening group and 5 were in the mammography-only group. All deaths were in the mammography-only group. The Kaplan-Meier estimate for disease-free survival showed no statistically significant difference between the two groups ( P = .325). However, patients in the combined screening group had a significantly better overall survival compared with patients in the mammography-only group ( P = .002). Conclusions: Combined screening with MRI and mammography in women with increased risk of breast cancer resulted in not only a higher cancer detection yield but also better overall survival.

To evaluate the additional value of shear-wave elastography (SWE) to B-mode ultrasonography (US) and to determine an appropriate guideline for the combined assessment of screening US-detected breast masses.This study was conducted with institutional review board approval, and written informed consent was obtained. From March 2010 to February 2012, B-mode US and SWE were performed in 159 US-detected breast masses before biopsy. For each lesion, Breast Imaging Reporting and Data System (BI-RADS) category on B-mode US images and the maximum stiffness color and elasticity values on SWE images were assessed. A guideline for adding SWE data to B-mode US was developed with the retrospective cohort to improve diagnostic performance in sensitivity and specificity and was validated in a distinct prospective cohort of 207 women prior to biopsy.Twenty-one of 159 masses in the development cohort and 12 of 207 breast masses in the validation cohort were malignant. In the development cohort, when BI-RADS category 4a masses showing a dark blue color or a maximum elasticity value of 30 kPa or less on SWE images were downgraded to category 3, specificity increased from 9.4% (13 of 138) to 59.4% (82 of 138) and 57.2% (79 of 138) (P.001), respectively, without loss in sensitivity (100% [21 of 21]). In the validation cohort, specificity increased from 17.4% (34 of 195) to 62.1% (121 of 195) and 53.3% (104 of 195) (P.001) respectively, without loss in sensitivity (91.7% [11 of 12]).The addition of SWE to B-mode US improved diagnostic performance with increased specificity for screening US-detected breast masses. BI-RADS category 4a masses detected at US screening that showed a dark blue color or a maximum elasticity value of 30 kPa or less on SWE images can be safely followed up instead of performing biopsy.

Background Breast cancer is a heterogeneous disease with intrinsic molecular subtypes. The different biology and histology of breast cancer exhibit different tumor morphology at breast magnetic resonance imaging (MRI). However, few studies have examined the quantitative relationship between the MRI morphological and immunohistochemical features in breast cancer. Purpose To investigate the correlations between tumor roundness, as quantitatively assessed with MRI and biomarkers or subtypes of breast cancer. Material and Methods A total of 280 women (mean age, 51 years; range, 28–79 years) with 282 invasive breast cancers (Results An inverse correlation was observed between the ER (r = –0.408, P Conclusion Our results suggest that breast tumors with lower ER expression and higher cellular proliferation or biologically aggressive triple-negative tumors are likely to manifest with relatively benign morphologic features.

To compare the average glandular dose (AGD) and diagnostic performance of mediolateral oblique (MLO) digital breast tomosynthesis (DBT) plus cranio-caudal (CC) digital mammography (DM) with two-view DM, and to evaluate the correlation of AGD with breast thickness and density.MLO and CC DM and DBT images of both breasts were obtained in 149 subjects. AGDs of DBT and DM per exposure were recorded, and their correlation with breast thickness and density were evaluated. Paired data of MLO DBT plus CC DM and two-view DM were reviewed for presence of malignancy in a jack-knife alternative free-response ROC (JAFROC) method.The AGDs of both DBT and DM, and differences in AGD between DBT and DM (ΔAGD), were correlated with breast thickness and density. The average JAFROC figure of merit (FOM) was significantly higher on the combined technique than two-view DM (P = 0.005). In dense breasts, the FOM and sensitivity of the combined technique was higher than that of two-view DM (P = 0.003) with small ΔAGD.MLO DBT plus CC DM provided higher diagnostic performance than two-view DM in dense breasts with a small increase in AGD.• DBT has higher diagnostic performance and potential to overcome limitations of DM. • Dose differences (DBT-DM, ΔAGD) were inversely correlated with breast thickness and density. • Figure of merit of MLO-DBT/CC-DM was higher than that of two-view DM. • In dense breasts, MLO-DBT/CC-DM provides better diagnostic performance with a small AGD increase.

To determine whether two-view shear-wave elastography (SWE) improves the performance of radiologists in differentiating benign from malignant breast masses compared with single-view SWE.This prospective study was conducted with institutional review board approval, and written informed consent was obtained. B-mode ultrasonographic (US) and orthogonal SWE images were obtained for 219 breast masses (136 benign and 83 malignant; mean size, 14.8 mm) in 219 consecutive women (mean age, 47.9 years; range, 20-78 years). Five blinded radiologists independently assessed the likelihood of malignancy for three data sets: B-mode US alone, B-mode US and single-view SWE, and B-mode US and two-view SWE. Interobserver agreement regarding Breast Imaging Reporting and Data System (BI-RADS) category and the area under the receiver operating characteristic curve (AUC) of each data set were compared.Interobserver agreement was moderate (κ = 0.560 ± 0.015 [standard error of the mean]) for BI-RADS category assessment with B-mode US alone. When SWE was added to B-mode US, five readers showed substantial interobserver agreement (κ = 0.629 ± 0.017 for single-view SWE; κ = 0.651 ± 0.014 for two-view SWE). The mean AUC of B-mode US was 0.870 (range, 0.855-0.884). The AUC of B-mode US and two-view SWE (average, 0.928; range, 0.904-0.941) was higher than that of B-mode US and single-view SWE (average, 0.900; range, 0.890-0.920), with statistically significant differences for three readers (P ≤ .003).The performance of radiologists in differentiating benign from malignant breast masses was improved when B-mode US was combined with two-view SWE compared with that when B-mode US was combined with single-view SWE.

A computational method was developed for the measurement of breast density using chest computed tomography (CT) images and the correlation between that and mammographic density. Sixty-nine asymptomatic Asian women (138 breasts) were studied. With the marked lung area and pectoralis muscle line in a template slice, demons algorithm was applied to the consecutive CT slices for automatically generating the defined breast area. The breast area was then analyzed using fuzzy c-mean clustering to separate fibroglandular tissue from fat tissues. The fibroglandular clusters obtained from all CT slices were summed then divided by the summation of the total breast area to calculate the percent density for CT. The results were compared with the density estimated from mammographic images. For CT breast density, the coefficient of variations of intraoperator and interoperator measurement were 3.00 % (0.59 %–8.52 %) and 3.09 % (0.20 %–6.98 %), respectively. Breast density measured from CT (22 ± 0.6 %) was lower than that of mammography (34 ± 1.9 %) with Pearson correlation coefficient of r = 0.88. The results suggested that breast density measured from chest CT images correlated well with that from mammography. Reproducible 3D information on breast density can be obtained with the proposed CT-based quantification methods.

Computer-aided diagnosis (CAD) systems in gray-scale breast ultrasound images have the potential to reduce unnecessary biopsy of breast masses. The purpose of our study is to develop a robust CAD system based on the texture analysis. First, gray-scale invariant features are extracted from ultrasound images via multi-resolution ranklet transform. Thus, one can apply linear support vector machines (SVMs) on the resulting gray-level co-occurrence matrix (GLCM)-based texture features for discriminating the benign and malignant masses. To verify the effectiveness and robustness of the proposed texture analysis, breast ultrasound images obtained from three different platforms are evaluated based on cross-platform training/testing and leave-one-out cross-validation (LOO-CV) schemes. We compare our proposed features with those extracted by wavelet transform in terms of receiver operating characteristic (ROC) analysis. The AUC values derived from the area under the curve for the three databases via ranklet transform are 0.918 (95% confidence interval [CI], 0.848 to 0.961), 0.943 (95% CI, 0.906 to 0.968), and 0.934 (95% CI, 0.883 to 0.961), respectively, while those via wavelet transform are 0.847 (95% CI, 0.762 to 0.910), 0.922 (95% CI, 0.878 to 0.958), and 0.867 (95% CI, 0.798 to 0.914), respectively. Experiments with cross-platform training/testing scheme between each database reveal that the diagnostic performance of our texture analysis using ranklet transform is less sensitive to the sonographic ultrasound platforms. Also, we adopt several co-occurrence statistics in terms of quantization levels and orientations (i.e., descriptor settings) for computing the co-occurrence matrices with 0.632+ bootstrap estimators to verify the use of the proposed texture analysis. These experiments suggest that the texture analysis using multi-resolution gray-scale invariant features via ranklet transform is useful for designing a robust CAD system.

The objective of our study was to determine the cancer yield of preoperative breast MRI in women with newly diagnosed ductal carcinoma in situ (DCIS) and to identify subgroups of DCIS patients for whom MRI is more likely to identify additional cancers.A database search for patients with DCIS who had undergone breast surgery between 2007 and 2011 was performed. A total of 308 women (median age, 49 years; range, 25-82 years) with DCIS underwent mammography, sonography, and a preoperative evaluation with MRI. The cancer yield and positive biopsy rate were determined. Patient age at diagnosis, menopausal status, family history of breast cancer, mammographic breast density, index cancer size, nuclear grade, and estrogen receptor (ER) status were examined, and a multivariate logistic regression analysis was performed.The cancer yield was 8% (24/308), and the positive biopsy rate was 53% (24/45). Of the 24 additional cancers, 14 (58%) represented multifocal disease, two (8%) represented multicentric disease, and eight (33%) represented contralateral cancer. In a multivariate analysis, age and index cancer size were factors significantly associated with additional MRI-detected cancers. Compared with women≥50 years, women50 years had a 3.2-fold higher frequency of detection (95% CI, 1.2-8.9; p=0.02). Compared with women with DCIS lesions smaller than 2.5 cm, women with DCIS lesions 2.5 cm or larger showed a 2.6-fold higher frequency of detection (95% CI, 1.1-6.3; p=0.04).Preoperative breast MRI can be considered in patients with DCIS who are50 years old, have index cancers≥2.5 cm, or fulfill both criteria.

To determine whether a correlation exists between maximum standardized uptake value (SUVmax) on (18)F-fluorodeoxyglucose positron emission tomography (FDG-PET) and the subtypes of breast cancer.This retrospective study involved 548 patients (mean age 51.6 years, range 21-81 years) with 552 index breast cancers (mean size 2.57 cm, range 1.0-14.5 cm). The correlation between (18)F-FDG uptake in PET/CT, expressed as SUVmax, and immunohistochemically defined subtypes (luminal A, luminal B, human epidermal growth factor receptor 2 (HER2) positive and triple negative) was analyzed.The mean SUVmax value of the 552 tumours was 6.07 ± 4.63 (range 0.9-32.8). The subtypes of the 552 tumours were 334 (60%) luminal A, 66 (12%) luminal B, 60 (11%) HER2 positive and 92 (17%) triple negative, for which the mean SUVmax values were 4.69 ± 3.45, 6.51 ± 4.18, 7.44 ± 4.73 and 9.83 ± 6.03, respectively. In a multivariate regression analysis, triple-negative and HER2-positive tumours had 1.67-fold (P 0.001) and 1.27-fold (P = 0.009) higher SUVmax values, respectively, than luminal A tumours after adjustment for invasive tumour size, lymph node involvement status and histologic grade.FDG uptake was independently associated with subtypes of invasive breast cancer. Triple-negative and HER2-positive breast cancers showed higher SUVmax values than luminal A tumours.• (18) F-FDG PET demonstrates increased tissue glucose metabolism, a hallmark of cancers. • Immunohistochemically defined subtypes appear significantly associated with FDG uptake (expressed as SUV max ). • Triple-negative tumours had 1.67-fold higher SUV max values than luminal A tumours. • HER2-positive tumours had 1.27-fold higher SUV max values than luminal A tumours.

Background The level of background parenchymal enhancement around tumor is known to be associated with breast cancer risk. However, there is no study investigating predictive power of parenchymal signal enhancement ratio (SER) around tumor for ipsilateral breast tumor recurrence (IBTR). Purpose To investigate whether the breast parenchymal SER around the tumor on preoperative dynamic contrast-enhanced magnetic resonance imaging (MRI) is associated with subsequent IBTR in breast cancer patients who had undergone breast-conserving treatment. Material and Methods Nineteen consecutive women (mean age, 44 years; range, 34–63 years) with breast cancer who developed IBTR following breast-conserving treatment and 114 control women matched for age, as well as T and N stages were included. We compared the clinicopathologic features of the two groups including nuclear grade, histologic grade, hormonal receptor status, human epidermal growth factor receptor-2 (HER-2) status, lymphovascular invasion, negative margin width, use of adjuvant therapy, and parenchymal SER around the tumor on preoperative DCE-MRI. The SER was measured on a slice showing the largest dimension of the tumor. Multivariate conditional logistic regression analysis was used to identify independent factors associated with IBTR. Results In univariate analysis, ER negativity (odds ratio [OR] = 4.7; P = 0.040), PR negativity (OR = 4.0; P = 0.013), HER-2 positivity (OR = 3.6; P = 0.026), and a parenchymal SER greater than 0.53 (OR = 23.3; P = 0.011) were associated with IBTR. In multivariate analysis, ER negativity (OR = 3.8; P = 0.015) and a parenchymal SER greater than 0.53 (OR = 13.2; P = 0.040) on preoperative MRI were independent factors associated with IBTR. Conclusion In addition to ER negativity, a higher parenchymal SER on preoperative MRI was an independent factor associated with subsequent IBTR in patients with breast cancer who had undergone breast-conserving treatment.

Automated whole breast ultrasound (ABUS) is an emerging screening tool for detecting breast abnormalities. In this study, a computer-aided detection (CADe) system based on multi-scale blob detection was developed for analyzing ABUS images. The performance of the proposed CADe system was tested using a database composed of 136 breast lesions (58 benign lesions and 78 malignant lesions) and 37 normal cases. After speckle noise reduction, Hessian analysis with multi-scale blob detection was applied for the detection of tumors. This method detected every tumor, but some nontumors were also detected. The tumor like lihoods for the remaining candidates were estimated using a logistic regression model based on blobness, internal echo, and morphology features. The tumor candidates with tumor likelihoods higher than a specific threshold (0.4) were considered tumors. By using the combination of blobness, internal echo, and morphology features with 10-fold cross-validation, the proposed CAD system showed sensitivities of 100%, 90%, and 70% with false positives per pass of 17.4, 8.8, and 2.7, respectively. Our results suggest that CADe systems based on multi-scale blob detection can be used to detect breast tumors in ABUS images.

This study investigated the correlation of oestrogen receptor (ER) and human epidermal growth factor receptor 2 (HER2) status with the probability of malignancy (POM) of mammographic calcifications in ductal carcinoma in situ (DCIS). A total of 101 women (age range, 27–83 years) with pure DCIS that presented as mammographic calcifications were included. Three radiologists independently reviewed mammograms according to the BI-RADS lexicon and provided 100-point POM scores and a BI-RADS category. ER, HER2 and breast cancer subtypes were determined using immunohistochemistry (IHC) and fluorescence in situ hybridisation. Pairwise correlations between POM and IHC biomarker scores were calculated, and mammographic features were compared between breast cancer subtypes. HER2 level positively correlated with the POM score (P