Added value of abbreviated breast magnetic resonance imaging for assessing suspicious microcalcification on screening mammography-a prospective study.

OBJECTIVES: To investigate the added diagnostic value of abbreviated breast magnetic resonance imaging (MRI) for suspicious microcalcifications on screening mammography. METHODS: This prospective study included 80 patients with suspicious calcifications on screening mammography who underwent abbreviated MRI before undergoing breast biopsy between August 2017 and September 2020. The abbreviated protocol included one pre-contrast and the first post-contrast T1-weighted series. MRI examinations were interpreted as either positive or negative based on the visibility of any significant enhancement. The positive predictive value (PPV) was compared before and after the MRI. RESULTS: Of the 80 suspicious microcalcifications, 33.8% (27/80) were malignant and 66.2% (53/80) were false positives. Abbreviated MRI revealed 33 positive enhancement lesions, and 25 and two lesions showed true-positive and false-negative findings, respectively. Abbreviated MRI increased PPV from 33.8 (27 of 80 cases; 95% CI: 26.2%, 40.8%) to 75.8% (25 of 33 cases; 95% CI: 62.1%, 85.7%). A total of 85% (45 of 53) false-positive diagnoses were reduced after abbreviated MRI assessment. CONCLUSIONS: Abbreviated MRI added significant diagnostic value in patients with suspicious microcalcifications on screening mammography, as demonstrated by a significant increase in PPV with a potential reduction in unnecessary biopsy. KEY POINTS: • Abbreviated breast magnetic resonance imaging increased the positive predictive value of suspicious microcalcifications on screening mammography from 33.8 (27/80 cases) to 75.8% (25/33 cases) (p < .01). • Abbreviated magnetic resonance imaging helped avoid unnecessary benign biopsies in 85% (45/53 cases) of lesions without missing invasive cancer.

Texture analysis using machine learning-based 3-T magnetic resonance imaging for predicting recurrence in breast cancer patients treated with neoadjuvant chemotherapy.

OBJECTIVES: To determine whether texture analysis for magnetic resonance imaging (MRI) can predict recurrence in patients with breast cancer treated with neoadjuvant chemotherapy (NAC). METHODS: This retrospective study included 130 women who received NAC and underwent subsequent surgery for breast cancer between January 2012 and August 2017. We assessed common features, including standard morphologic MRI features and clinicopathologic features. We used a  commercial software and analyzed texture features from pretreatment and midtreatment MRI. A random forest (RF) method was performed to build a model for predicting recurrence. The diagnostic performance of this model for predicting recurrence was assessed and compared with those of five other machine learning classifiers using the Wald test. RESULTS: Of the 130 women, 21 (16.2%) developed recurrence at a median follow-up of 35.4 months. The RF classifier with common features including clinicopathologic and morphologic MRI features showed the lowest diagnostic performance (area under the receiver operating characteristic curve [AUC], 0.83). The texture analysis with the RF method showed the highest diagnostic performances for pretreatment T2-weighted images and midtreatment DWI and ADC maps showed better diagnostic performance than that of an analysis of common features (AUC, 0.94 vs. 0.83, p < 0.05). The RF model based on all sequences showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers. CONCLUSIONS: Texture analysis using an RF model for pretreatment and midtreatment MRI may provide valuable prognostic information for predicting recurrence in patients with breast cancer treated with NAC and surgery. KEY POINTS: • RF model-based texture analysis showed a superior diagnostic performance than traditional MRI and clinicopathologic features (AUC, 0.94 vs.0.83, p < 0.05) for predicting recurrence in breast cancer after NAC. • Texture analysis using RF classifier showed the highest diagnostic performances (AUC, 0.94) for pretreatment T2-weighted images and midtreatment DWI and ADC maps. • RF model showed a better diagnostic performance for predicting recurrence than did the five other machine learning classifiers.

Fully automated measurements of volumetric breast density adapted for BIRADS 5th edition: a comparison with visual assessment.

BACKGROUND: Since the 5th edition of BI-RADS was released, prior studies have compared BI-RADS and quantitative fully automated volumetric assessment, but with software packages that were not recalibrated according to the 5th edition. PURPOSE: To investigate mammographic density assessment of automated volumetric measurements recalibrated according to the BI-RADS 5th edition compared with visual assessment. MATERIAL AND METHODS: A total of 4000 full-field digital mammographic examinations were reviewed by three radiologists for the BI-RADS 5th edition density category by consensus after individual assessments. Volumetric density data obtained using Quantra and Volpara software were collected. The comparison of visual and volumetric density assessments was performed in total and according to the presence of cancer. RESULTS: Among 4000 examinations, 129 were mammograms of breast cancer. Compared to visual assessment, volumetric measurements showed higher category B (40.6% vs. 19.8%) in Quantra, and higher category D (40.4% vs. 14.7%) and lower category A (0.2% vs. 5.0%) in Volpara (P < 0.0001). All volumetric data showed a difference according to visually assessed categories and were correlated between the two volumetric measurements (P < 0.0001). The group with cancer showed a lower proportion of fatty breast than that without cancer: 17.8% vs. 46.9% for Quantra (P < 0.0001) and 9.3% vs. 21.5% for Volpara (P = 0.003). Both measurements showed significantly higher mean density data in the group with cancer than without cancer (P < 0.005 for all). CONCLUSION: Automated volumetric measurements adapted for the BI-RADS 5th edition showed different but correlated results with visual assessment and each other. Recalibration of volumetric measurement has not completely reflected the visual assessment.

Texture Analysis with 3.0-T MRI for Association of Response to Neoadjuvant Chemotherapy in Breast Cancer.

Background Previous studies have suggested that texture analysis is a promising tool in the diagnosis, characterization, and assessment of treatment response in various cancer types. Therefore, application of texture analysis may be helpful for early prediction of pathologic response in breast cancer. Purpose To investigate whether texture analysis of features from MRI is associated with pathologic complete response (pCR) to neoadjuvant chemotherapy (NAC) in breast cancer. Materials and Methods This retrospective study included 136 women (mean age, 47.9 years; range, 31-70 years) who underwent NAC and subsequent surgery for breast cancer between January 2012 and August 2017. Patients were monitored with 3.0-T MRI before (pretreatment) and after (midtreatment) three or four cycles of NAC. Texture analysis was performed at pre- and midtreatment T2-weighted MRI, contrast material-enhanced T1-weighted MRI, diffusion-weighted MRI, and apparent diffusion coefficient (ADC) mapping by using commercial software. A random forest method was applied to build a predictive model for classifying those with pCR with use of texture parameters. Diagnostic performance for predicting pCR was assessed and compared with that of six other machine learning classifiers (adaptive boosting, decision tree, k-nearest neighbor, linear support vector machine, naive Bayes, and linear discriminant analysis) by using the Wald test and DeLong method. Results Forty of the 136 patients (29%) achieved pCR after NAC. In the prediction of pCR, the random forest classifier showed the lowest diagnostic performance with pretreatment ADC (area under the receiver operating characteristic curve [AUC], 0.53; 95% confidence interval: 0.44, 0.61) and the highest diagnostic performance with midtreatment contrast-enhanced T1-weighted MRI (AUC, 0.82; 95% confidence interval: 0.74, 0.88) among pre- and midtreatment T2-weighted MRI, contrast-enhanced T1-weighted MRI, diffusion-weighted MRI, and ADC mapping. Conclusion Texture parameters using a random forest method of contrast-enhanced T1-weighted MRI at midtreatment of neoadjuvant chemotherapy were valuable and associated with pathologic complete response in breast cancer. © RSNA, 2019 Online supplemental material is available for this article.

Prediction of axillary response by monitoring with ultrasound and MRI during and after neoadjuvant chemotherapy in breast cancer patients.

PURPOSE: To investigate whether monitoring with ultrasound and MR imaging before, during and after neoadjuvant chemotherapy (NAC) can predict axillary response in breast cancer patients. MATERIALS AND METHODS: A total of 131 breast cancer patients with clinically positive axillary lymph node (LN) who underwent NAC and subsequent surgery were enrolled. They had ultrasound and 3.0 T-MR examinations before, during and after NAC. After reviewing ultrasound and MR images, axillary LN features and tumour size (T size) were noted. According to LN status after surgery, imaging features and their diagnostic performances were analysed. RESULTS: Of the 131 patients, 60 (45.8%) had positive LNs after surgery. Pre-NAC T size at ultrasound and MR was different in positive LN status after surgery (p < 0.01). There were significant differences in mid- and post-NAC number, cortical thickness (CxT), T size and T size reduction at ultrasound and mid- and post-NAC CxT, hilum, T size and T size reduction, and post-NAC ratio of diameter at MR (p < 0.03). On multivariate analysis, pre-NAC MR T size (OR, 1.03), mid-NAC ultrasound T size (OR, 1.05) and CxT (OR, 1.53), and post-NAC MR T size (OR, 1.06) and CxT (OR, 1.64) were independently associated with positive LN (p < 0.004). Combined mid-NAC ultrasound T size and CxT showed the best diagnostic performance with AUC of 0.760. CONCLUSION: Monitoring ultrasound and MR axillary LNs and T size can be useful to predict axillary response to NAC in breast cancer patients. KEY POINTS: • Monitoring morphologic features of LNs is useful to predict axillary response. • Monitoring tumour size by imaging is useful to predict axillary response. • The axillary ultrasound during NAC showed the highest diagnostic performance.

Performance of shear-wave elastography for breast masses using different region-of-interest (ROI) settings.

Background Various size and shape of region of interest (ROI) can be applied for shear-wave elastography (SWE). Purpose To investigate the diagnostic performance of SWE according to ROI settings for breast masses. Material and Methods To measure elasticity for 142 lesions, ROIs were set as follows: circular ROIs 1 mm (ROI-1), 2 mm (ROI-2), and 3 mm (ROI-3) in diameter placed over the stiffest part of the mass; freehand ROIs drawn by tracing the border of mass (ROI-M) and the area of peritumoral increased stiffness (ROI-MR); and circular ROIs placed within the mass (ROI-C) and to encompass the area of peritumoral increased stiffness (ROI-CR). Mean (Emean), maximum (Emax), and standard deviation (ESD) of elasticity values and their areas under the receiver operating characteristic (ROC) curve (AUCs) for diagnostic performance were compared. Results Means of Emean and ESD significantly differed between ROI-1, ROI-2, and ROI-3 ( P < 0.0001), whereas means of Emax did not ( P = 0.50). For ESD, ROI-1 (0.874) showed a lower AUC than ROI-2 (0.964) and ROI-3 (0.975) ( P < 0.002). The mean ESD was significantly different between ROI-M and ROI-MR and between ROI-C and ROI-CR ( P < 0.0001). The AUCs of ESD in ROI-M and ROI-C were significantly lower than in ROI-MR ( P = 0.041 and 0.015) and ROI-CR ( P = 0.007 and 0.004). Conclusion Shear-wave elasticity values and their diagnostic performance vary based on ROI settings and elasticity indices. Emax is recommended for the ROIs over the stiffest part of mass and an ROI encompassing the peritumoral area of increased stiffness is recommended for elastic heterogeneity of mass.

Diagnostic performance of tomosynthesis and breast ultrasonography in women with dense breasts: a prospective comparison study.

PURPOSE: To compare the diagnostic performances of tomosynthesis and ultrasonography as adjunctives to digital mammography in women with dense breasts. METHODS: 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. RESULTS: 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. CONCLUSIONS: Tomosynthesis exhibits comparable performance to ultrasonography as an adjunct to mammography for diagnosis of breast cancer, except among women with extremely dense breasts.

Predictive Factors for Active Surveillance of Subcentimeter Thyroid Nodules with Highly Suspicious US Features.

PURPOSE: This study was designed to assess the outcomes of subcentimeter thyroid nodules with highly suspicious ultrasonography (US) features and to investigate the predictive factors associated with malignancy and aggressive biological behavior to determine appropriate candidate factors for active surveillance. METHODS: Between June 2011 and December 2013, 1866 subcentimeter thyroid nodules with highly suspicious US features that were subjected to US-guided fine needle aspiration and subsequent surgery or US follow-up of at least 2 years were evaluated. A multivariate logistic regression analysis was performed to identify independent clinical characteristics and US features associated with the malignancy rate and aggressive biological behavior. RESULTS: Of the 1866 subcentimeter thyroid nodules, 821 (44.0%) were benign and 1045 (56.0%) were malignant. Age younger than 45 years, presence of microcalcification, and a taller than wide shape on US were associated independently with malignancy in the subcentimeter thyroid nodules (P < 0.05). Of 1041 evaluated papillary microcarcinomas, a multivariate analysis revealed that male gender, presence of microcalcification, and a taller than wide on US were independently associated with lymph node metastasis and ATA intermediate risk (P < 0.01). CONCLUSIONS: Age younger than 45 years, male gender, and subcentimeter thyroid nodules exhibiting microcalcification, and a taller than wide shape on US might be not good candidate factors for active surveillance.

Management for BI-RADS category 3 lesions detected in preoperative breast MR imaging of breast cancer patients.

OBJECTIVE: To retrospectively evaluate characteristics of and determine appropriate follow-up recommendations for BI-RADS category 3 lesions detected in preoperative MRI of breast cancer patients. METHODS: BI-RADS category 3 assessments were identified from the breast MRI database for 5,110 consecutive breast cancer patients who had undergone preoperative MRI and surgery. Patient and lesion characteristics, malignancy rate, and interval between lesion detection and cancer diagnosis were analysed. Histopathological results or imaging at or after 2-year follow-up were used as reference standards. RESULTS: Of the 626 lesions, morphological features included a single focus in 26.5% (n = 166), multiple foci in 47.1% (n = 295), mass in 21.7% (n = 136) and non-mass enhancement in 4.6% (n = 29). Cancer was found in 0.8% (5/626) at a median interval of 50 months (range, 29-66 months). Malignancy rate according to morphological feature was: 1.8% (3/166) in a single focus, 0.7% (1/136) in mass and 3.4% (1/29) in non-mass enhancement. All detected cancers were stage 0 or IA. CONCLUSIONS: Annual follow-up might be adequate for BI-RADS category 3 lesions detected at preoperative MRI because of the 0.8% (5/626) malignancy rate, long interval between lesion detection and cancer diagnosis, and early stage of diagnosed cancers. KEY POINTS: • BI-RADS category 3 lesions on preoperative MRI had 0.8% malignancy rate. • All cancer diagnoses from BI-RADS 3 occurred after 24-month follow-up. • Annual follow-up might be adequate for BI-RADS 3 detected on preoperative MRI.

Comparison of Visual Assessment of Breast Density in BI-RADS 4th and 5th Editions With Automated Volumetric Measurement.

OBJECTIVE: The purpose of this study was to compare visual assessments of mammographic breast density by radiologists using BI-RADS 4th and 5th editions in correlation with automated volumetric breast density measurements. MATERIALS AND METHODS: A total of 337 consecutive full-field digital mammographic examinations with standard views were retrospectively assessed by two radiologists for mammographic breast density according to BI-RADS 4th and 5th editions. Fully automated measurement of the volume of fibroglandular tissue and total breast and percentage breast density was performed with a commercially available software program. Interobserver and intraobserver agreement was assessed with kappa statistics. The distributions of breast density categories for both editions of BI-RADS were compared and correlated with volumetric data. RESULTS: Interobserver agreement on breast density category was moderate to substantial (κ = 0.58-0.63) with use of BI-RADS 4th edition and substantial (κ = 0.63-0.66) with use of the 5th edition but without significant difference between the two editions. For intraobserver agreement between the two editions, the distributions of density category were significantly different (p < 0.0001), the proportions of dense breast increased, and the proportion of fatty breast decreased with use of the 5th edition compared with the 4th edition (p < 0.0001). All volumetric breast density data, including percentage breast density, were significantly different among density categories (p < 0.0001) and had significant correlation with visual assessment for both editions of BI-RADS (p < 0.01). CONCLUSION: Assessment using BI-RADS 5th edition revealed a higher proportion of dense breast than assessment using BI-RADS 4th edition. Nevertheless, automated volumetric density assessment had good correlation with visual assessment for both editions of BI-RADS.

Comparison of the diagnostic performance of digital breast tomosynthesis and magnetic resonance imaging added to digital mammography in women with known breast cancers.

OBJECTIVES: To compare the diagnostic performance of digital breast tomosynthesis (DBT) and magnetic resonance imaging (MRI) added to mammography in women with known breast cancers. METHODS: Three radiologists independently reviewed image sets of 172 patients with 184 cancers; mammography alone, DBT plus mammography and MRI plus mammography, and scored for cancer probability using the Breast Imaging Reporting and Data System (BI-RADS). Jack-knife alternative free-response receiver-operating characteristic (JAFROC), which allows diagnostic performance estimation using single lesion as a statistical unit in a cancer-only population, was used. Sensitivity and positive predictive value (PPV) were compared using the McNemar and Fisher-exact tests. RESULTS: The JAFROC figures of merit (FOMs) was lower in DBT plus mammography (0.937) than MRI plus mammography (0.978, P = 0.0006) but higher than mammography alone (0.900, P = 0 .0013). The sensitivity was lower in DBT plus mammography (88.2 %) than MRI plus mammography (97.8 %) but higher than mammography alone (78.3 %, both P < 0 .0001). The PPV was significantly higher in DBT plus mammography (93.3 %) than MRI plus mammography (89.6 %, P = 0 .0282). CONCLUSIONS: DBT provided lower diagnostic performance than MRI as an adjunctive imaging to mammography. However, DBT had higher diagnostic performance than mammography and higher PPV than MRI. KEY POINTS: • Digital breast tomosynthesis (DBT) plus mammography was compared with MRI plus mammography. • DBT had lower sensitivity and higher PPV than MRI. • DBT had higher diagnostic performance than mammography.

Automated Volumetric Breast Density Measurements in the Era of the BI-RADS Fifth Edition: A Comparison With Visual Assessment.

OBJECTIVE: The purpose of this study is to evaluate automated volumetric measurements in comparison with visual assessment of mammographic breast density by use of the fifth edition of BI-RADS. MATERIALS AND METHODS: A total of 1185 full-field digital mammography examinations with standard views were retrospectively analyzed. All images were visually assessed by two blinded radiologists according to breast density category in the fifth edition of the BI-RADS lexicon. Automated volumetric breast density assessment was performed using two different software programs, Quantra and Volpara. A weighted kappa value was calculated to assess the degree of agreement among the visual and volumetric assessments of the density category. The volumes of fibroglandular tissue or total breast and the percentage breast density provided by the two software programs were compared. RESULTS: Compared with a visual assessment, the agreement of density category ranged from moderate to substantial in Quantra (κ = 0.54-0.61) and fair to moderate in Volpara (κ = 0.32-0.43). The distribution of density category was statistically significantly different among visual and volumetric measurements (p < 0.0001). Quantra assigned category A and B (43.5%) more frequently than did the radiologists (25.6%) or Volpara (16.0%). Volpara assigned category D (42.1%) more frequently than did the radiologists (19.5%) or Quantra (15.4%). Between the two software programs, the means of all volumetric data were statistically significantly different (p < 0.0001), but were well correlated (γ = 0.79-0.99; p < 0.0001). CONCLUSION: More mammographic examinations were classified as nondense breast tissue using the Quantra software and as dense breast tissue using the Volpara software, as compared with visual assessments according to the BI-RADS fifth edition.

Shear-Wave Elastography for the Detection of Residual Breast Cancer After Neoadjuvant Chemotherapy.

OBJECTIVE: This study was designed to evaluate the accuracy of shear-wave elastography (SWE) in the detection of residual breast cancer after neoadjuvant chemotherapy (NAC). METHODS: Seventy-one women with stage II-III breast cancers who underwent B-mode ultrasound (US), SWE, and magnetic resonance imaging (MRI) after NAC were included. The presence of residual cancer was determined on B-mode US and MRI, and the maximum elasticity of residual lesions was assessed on SWE. The sensitivity, specificity, accuracy, and area under the receiver operating characteristic curve (AUC) of B-mode US, SWE, and MRI were compared. RESULTS: Sixty-one of 71 women (86 %) had residual cancer and showed higher maximum elasticity values (mean 116.0 ± 74.1 kPa) than those without residual cancer (26.4 ± 21.0 kPa; p < 0.001). B-mode US showed 72.1 % (44/61) sensitivity, 50.0 % (5/10) specificity, and 69.0 % (49/71) accuracy. The sensitivity, specificity, and accuracy of SWE were 83.6 % (51/61), 80.0 % (8/10), and 83.1 % (59/71) when a maximum elasticity value of >30 kPa was considered to indicate the presence of residual cancer. The combined AUC of B-mode US and SWE (0.877) was significantly higher than that of B-mode US (0.702) (p = 0.014) and comparable to that of MRI (0.939) (p = 0.147). CONCLUSIONS: SWE allowed relatively accurate assessment for the presence of residual lesion after NAC and improved the diagnostic performance of B-mode US.

Breast MR imaging screening in women with a history of breast conservation therapy.

PURPOSE: To retrospectively investigate the outcomes of single-screening breast magnetic resonance (MR) imaging in women who had a history of breast conservation therapy (BCT) for breast cancers and who had previous negative mammography and ultrasonographic (US) findings. MATERIALS AND METHODS: This study was institutional review board-approved and informed consent was waived. Between January 2008 and March 2012, 607 consecutive women (median age, 48 years; age range, 20-72 years) who underwent BCT for breast cancer, had negative mammography and US findings, and underwent subsequent screening breast MR imaging were studied. Of the study population, 91.8% (557 of 607) patients underwent preoperative MR examinations. Cancer detection rate, characteristics of detected cancers, positive predictive value (PPV), sensitivity, and specificity were assessed. Multivariate logistic regression analysis was performed to identify independent clinical-pathologic factors associated with women with cancers detected by using MR imaging. RESULTS: Eleven cancers (eight invasive, three ductal carcinoma in situ; median invasive size, 0.8 cm; range, 0.4-1.4 cm; all node negative) were additionally detected with MR imaging in 607 women (18.1 cancers per 1000 women). PPV for recall, PPV for biopsy, sensitivity, and specificity were 9.4% (11 of 117 examinations), 43.5% (10 of 23 examinations), 91.7% (11 of 12 examinations), and 82.2% (489 of 595 examinations), respectively. At multivariate analysis, the independent factors associated with women with MR-detected cancers were age younger than 50 years at initial diagnosis (P < .001) and more than a 24-month interval between initial surgery and screening MR imaging (P = .011). CONCLUSION: Single-screening MR imaging depicted 18.1 additional cancers per 1000 women with a history of BCT. Multivariate analysis revealed age younger than 50 years at initial younger than 50 years.

Added value of shear-wave elastography for evaluation of breast masses detected with screening US imaging.

PURPOSE: 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. MATERIALS AND METHODS: 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. RESULTS: 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]). CONCLUSION: 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.

Computer-aided evaluation as an adjunct to revised BI-RADS Atlas: improvement in positive predictive value at screening breast MRI.

OBJECTIVES: To investigate whether kinetic features via magnetic resonance (MR)-computer-aided evaluation (CAE) can improve the positive predictive value (PPV) of morphological descriptors for suspicious lesions at screening breast MRI. METHODS: One hundred and sixteen consecutive, suspiciously enhancing lesions detected at contralateral breast MRI screening in 116 women with newly-diagnosed breast cancers were included. Morphological descriptors according to the revised BI-RADS Atlas and kinetic features from MR-CAE were analysed. The PPV of each descriptor was analysed to identify subgroups in which PPV could be improved by the addition of MR-CAE. RESULTS: When biopsy recommendations were downgraded to follow-up in cases where there were both the absence of enhancement at a 50% threshold and the absence of delayed washout, PPV increased from 0.328 (95% CI, 0.249-0.417) to 0.500 (95% CI, 0.387- 0.613). Two ductal carcinoma in situ (DCIS) non-mass enhancement (NME) lesions were missed. Application of downgrading criteria to foci or masses led to increased PPV from 0.310 (95% CI, 0.216-0.419) to 0.437 (95% CI, 0.331-0.547) without missing cancers. CONCLUSIONS: MR-CAE has the potential to improve the PPV of breast MR imaging by reducing the number of false positives. When suspicious mass lesions do not show enhancement at a 50% threshold nor delayed washout, follow-up rather than biopsy can be considered. KEY POINTS: • MR-CAE has the potential to increase PPV at breast MRI screening. • Lesions without enhancement at 50% threshold and washout might be downgraded. • DCIS non-mass lesions might be false-negative cases at MR-CAE.

Smaller reduction in 3D breast density associated with subsequent cancer recurrence in patients with breast cancer receiving adjuvant tamoxifen therapy.

OBJECTIVE: The purpose of this study was to retrospectively investigate whether 3D breast density changes measured using MRI were associated with recurrent cancer in patients with breast cancer who received adjuvant tamoxifen. MATERIALS AND METHODS: A search of the breast MRI database (2007-2008) revealed a dataset that included 80 women (mean age, 44 years; range, 27-68 years) with breast cancer who underwent breast-conserving surgery, adjuvant tamoxifen treatment, and breast MRI before and after tamoxifen. The following clinicopathologic variables were collected: age, body mass index, menopausal status, family history, tumor stage, tumor grade, hormonal receptor status, and adjuvant chemotherapy status. MRI variables (total breast volume, fibro-glandular volume, and breast density) were measured for the contralateral untreated breast before and after tamoxifen treatment, and the percentage changes were recorded. A multivariate logistic regression analysis was performed to identify independent factors that were associated with cancer recurrence. RESULTS: Overall, 12 (15%) of the 80 women developed recurrence. No recurrent cancers were found in the remaining 68 patients (85%) at a median follow-up of 48 months (range, 37-60 months). Percentage reduction of breast density after tamoxifen was the only independent factor associated with recurrence (adjusted odds ratio [OR] = 0.848, 95% CI = 0.769-0.935, and p = 0.001 for observer 1; adjusted OR = 0.957, 95% CI = 0.919-0.996, and p = 0.032 for observer 2) in the multivariate analysis. CONCLUSION: Three-dimensional breast density changes measured using MRI during tamoxifen treatment were an independent factor associated with cancer recurrence in patients with breast cancer who received adjuvant tamoxifen.

Role of diffusion-weighted MRI: predicting axillary lymph node metastases in breast cancer.

BACKGROUND: Ultrasound (US) is probably the standard imaging procedure in most centers, and US-guided fine needle aspiration can be added if suspicious lymph nodes are found. However, US-guided fine needle aspiration is an invasive method to diagnose a metastasis and has showed relatively low sensitivity. In general, diffusion-weighted (DW) magnetic resonance imaging (MRI) has become an emerging technique for discriminating benign from malignant breast lesions in a short imaging acquisition time. PURPOSE: To evaluate the potential for using DW MRI with an apparent diffusion coefficient (ADC) value to predict axillary lymph node metastases in patients with invasive breast cancer. MATERIAL AND METHODS: This study enrolled 110 axillary lymph nodes from 110 consecutive women who were diagnosed with invasive breast cancer for preoperative breast MRI and US. The largest enhancing ipsilateral axillary lymph nodes were included in this study, and benign and metastatic axillary lymph nodes were compared according to the pathologic reports. The cut-off ADC value to differentiate between benign and metastatic axillary lymph nodes was evaluated with receiver-operating characteristic curve analysis. Diagnostic performance of ultrasound and DW MRI was calculated for enhancing lymph node in dynamic contrast-enhanced MRI. RESULTS: Nodal metastases were documented in 68 (62%) axillary lymph nodes. The mean size of metastatic axillary lymph nodes was larger than that of benign axillary lymph nodes (15.5 mm vs. 10.9 mm, P < 0.001). The mean ADC value (0.69 × 10(-3 )mm(2)/s) of the metastases was significantly lower than that of the benign axillary lymph nodes (1.04 × 10(-3 )mm(2)/s) (P < 0.001). The ADC value cut-off between metastatic and benign axillary lymph nodes was 0.90 × 10(-3 )mm(2)/s. Using ADC cut-off, sensitivity, specificity, and accuracy of DW MRI were 100%, 83.3%, and 93.6%, respectively. The sensitivity, specificity, and accuracy of US showed 94.1%, 54.8%, and 79.1%, respectively. CONCLUSION: DW MRI of axillary lymph nodes can provide reliable information for the differentiation of benign from metastatic axillary lymph nodes in invasive breast cancer patients.

Preoperative assessment of extrathyroidal extension of papillary thyroid carcinoma: comparison of 2- and 3-dimensional sonography.

OBJECTIVES: The purpose of this study was to evaluate the diagnostic performance and interobserver agreement of 2-dimensional (2D) and 3-dimensional (3D) sonography for evaluating extrathyroidal extension of papillary thyroid carcinoma. METHODS: A total of 79 papillary thyroid carcinomas in 79 patients who underwent both 2D and 3D sonography for preoperative staging of papillary thyroid carcinoma were included. When the lesion was abutting on the thyroid capsule on 2D sonography, 3D sonography was performed. Three radiologists reviewed 3 data sets: 2D sonography, 3D sonography, and a combined set of both for tumor staging. The diagnostic performance, including sensitivity, specificity, positive predictive value, negative predictive value, and accuracy, for extrathyroidal extension was analyzed. Interobserver agreement of the 3 radiologists was assessed with κ values. RESULTS: The overall accuracy rates for 2D sonography, 3D sonography, and the combined set in predicting extrathyroidal extension were 60.8%, 66.2%, and 67.9%, respectively. The accuracy of the combined set was significantly higher than that of 2D sonography (P = .016). The interobserver agreement of the 3 reviewers was fair (κ = 0.33) for 2D sonography and moderate for 3D sonography (κ = 0.46) and the combined set (κ = 0.49). CONCLUSIONS: Adding 3D sonography to 2D sonography could improve the accuracy and interobserver agreement for predicting extrathyroidal extension of papillary thyroid carcinoma.

Shear-wave elastography of invasive breast cancer: correlation between quantitative mean elasticity value and immunohistochemical profile.

To compare the mean elasticity value, as measured by shear-wave elastography (SWE), with immunohistochemical profile of invasive breast cancer. This was an institutional review board-approved retrospective study, with a waiver of informed consent. A total of 166 invasive breast cancers in 152 women undergoing preoperative SWE and surgery were included. Quantitative mean elasticity values in kPa were measured for each lesion by using SWE. Medical records were reviewed to determine palpability, invasive size, lymphovascular invasion, histologic grade, and axillary lymph node status. Based on the immunohistochemical profiles, tumor subtypes were categorized as triple-negative (TN), luminal A and B, or human epidermal growth factor receptor 2-enriched cancer. The mean elasticity value was correlated with clinicopathological features using univariate regression models and multivariate linear regression analysis. Palpability (P < 0.0001), larger size (P = 0.013), lymphovascular invasion (P < 0.0001), higher histologic grade (P < 0.0001), and lymph node involvement (P = 0.018) were significantly associated with the mean elasticity value. For the immunohistochemical profiles and tumor subtypes, the estrogen receptor (P = 0.015), progesterone receptor (P = 0.002), Ki-67 (P = 0.009), and the TN (P = 0.009) tumor subtype were correlated with the mean elasticity value. Multivariate logistic regression analysis showed that the following variables were significantly associated with the mean elasticity value: palpable abnormality, histologic grade, and lymphovascular invasion. No immunohistochemical profile of the cancers was independently correlated with the mean elasticity value. For invasive breast cancers, clinicopathological features of poor prognosis showed higher mean elasticity values than those of good prognosis. However, the immunohistochemical profile showed no independent association with the mean elasticity value.