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Purpose: To develop a radiomics signature based on preoperative MRI to estimate disease-free survival (DFS) in patients with invasive breast cancer and to establish a radiomics nomogram that incorporates the radiomics signature and MRI and clinicopathological findings.Experimental Design: We identified 294 patients with invasive breast cancer who underwent preoperative MRI. Patients were randomly divided into training (n = 194) and validation (n = 100) sets. A radiomics signature (Rad-score) was generated using an elastic net in the training set, and the cutoff point of the radiomics signature to divide the patients into high- and low-risk groups was determined using receiver-operating characteristic curve analysis. Univariate and multivariate Cox proportional hazards model and Kaplan–Meier analysis were used to determine the association of the radiomics signature, MRI findings, and clinicopathological variables with DFS. A radiomics nomogram combining the Rad-score and MRI and clinicopathological findings was constructed to validate the radiomic signatures for individualized DFS estimation.Results: Higher Rad-scores were significantly associated with worse DFS in both the training and validation sets (P = 0.002 and 0.036, respectively). The radiomics nomogram estimated DFS [C-index, 0.76; 95% confidence interval (CI); 0.74–0.77] better than the clinicopathological (C-index, 0.72; 95% CI, 0.70–0.74) or Rad-score–only nomograms (C-index, 0.67; 95% CI, 0.65–0.69).Conclusions: The radiomics signature is an independent biomarker for the estimation of DFS in patients with invasive breast cancer. Combining the radiomics nomogram improved individualized DFS estimation. Clin Cancer Res; 24(19); 4705–14. ©2018 AACR.

Appendix E1 The Acquisition Parameters and Retrieving Procedure Appendix E2 MR Imaging Preparation for Radiomic Analysis Appendix E3 MR Imaging Interpretation Appendix E4 Computer code used to compute the Radiomics Features Appendix E5 Categorical Concepts of Radiomic Features and the Mathematical Definition of Adopted Feature Algorithms Appendix E6 Radiomics Score (Rad-score) Calculation Formula

In this study, we aimed to evaluate the benefits and losses of mammography with and without implant displacement (ID) and propose an appropriate imaging protocol for the screening of breasts with implants. We evaluated mammograms of 162 breasts in 96 patients including 71 breasts with biopsy-proven cancers. Mammography of each breast included standard MLO and ID MLO images. We reviewed the mammograms using clinical image quality criteria, which consist of parameters that evaluate the proper positioning of the breast and the image resolution. Standard MLO images showed significantly higher scores for proper positioning but showed significantly lower scores for image resolution than the ID MLO images. Moreover, standard MLO images showed significantly higher kVp, mAs, and compressed breast thickness than the ID MLO images. The organ dose was also higher in the standard MLO images than in the ID MLO images, but the difference was not statistically significant. In mammography with proven cancer, ID MLO images showed significantly higher degree of cancer visibility than standard MLO images. For screening mammography in patients with breast implants, ID MLO view alone is sufficient for MLO projection with reducing the patient’s radiation dose without compromising the breast cancer detection capability, especially in dense breasts with subpectoral implants.

This study aimed to investigate the predictability of breast MRI for pathologic complete response (pCR) by molecular subtype in patients with breast cancer receiving neoadjuvant chemotherapy (NAC) and investigate the MRI findings that can mimic residual malignancy.A total of 506 patients with breast cancer who underwent MRI after NAC and underwent surgery between January and December 2018 were included. Two breast radiologists dichotomized the post-NAC MRI findings as radiologic complete response (rCR) and no-rCR. The diagnostic performance of MRI predicting pCR was evaluated. pCR was determined based on the final pathology reports. Tumors were divided according to hormone receptor (HR) and human epidermal growth factor receptor (HER) 2. Residual lesions on post-NAC MRI were divided into overt and subtle which classified as nodularity or delayed enhancement. Pearson's χThe overall pCR rate was 30.04%. The overall accuracy for predicting pCR using MRI was 76.68%. The accuracy was significantly different by subtypes (p 0.001), as follows in descending order: HR - /HER2 - (85.63%), HR + /HER2 - (82.84%), HR + /HER2 + (69.37%), and HR - /HER2 + (62.38%). MRI in the HR - /HER2 + type showed the highest false-negative rate (18.81%) for predicting pCR. The subtle residual enhancement observed only in the delayed phase was associated with false-negative findings (76.2%, p = 0.016).The diagnostic accuracy of MRI for predicting pCR differed by molecular subtypes. When the residual enhancement on MRI after NAC is subtle and seen only in the delayed phase, overinterpretation of residual tumors should be performed with caution.• In patients with breast cancer after completion of neoadjuvant chemotherapy, the diagnostic accuracy of MRI for predicting pathologic complete response (pCR) differed according to molecular subtype. • When residual enhancement on MRI is subtle and seen only in the delayed phase, this finding could be associated with false-negative pCR results.

To evaluate the frequency and location of abnormal lymph nodes (LNs) in breast cancer patients with a single axillary lymph node (ALN) metastasis on breast magnetic resonance imaging (MRI). We retrospectively reviewed the MRI findings of 219 consecutive patients with breast cancer with single ALN metastasis who were surgically confirmed at our institution between January 2018 and December 2018. The morphological features and locations of the abnormal LN on MRI were analyzed. Pathology reports were reviewed to evaluate the size of the metastases and whether they were sentinel LNs (SLNs). Of the 219 patients with a single ALN metastasis, 56 (25.6%) showed abnormal MRI findings. Of these, 54 (96.4%) had either the lowest or second-lowest LN in the level I axilla. In 184 (91.5%) of 201 patients who underwent SLN biopsy, the metastatic LN were SLN. Macrometastases were found more frequently in cases with abnormal LNs than in those with normal-looking LNs (P = .004). The most frequent morphological feature of metastatic ALNs was a diffuse cortical thickening of 3 to 5 mm (37.5%). Although MRI findings of single ALN metastasis in breast cancer patients are none or minimal, abnormalities are observed in the lowest or second-lowest LN in the lower axilla when present, suggesting the location of the SLNs.

Objective: To investigate the added value of kinetic information for breast lesion evaluation on abbreviated breast MRI (AB-MRI). Methods: This retrospective study analyzed 207 breast lesions with Breast Imaging Reporting and Data System categories 3, 4, or 5 on AB-MRI in 198 consecutive patients who had breast MRI for screening after breast cancer surgery between January 2017 and December 2019. All lesions were pathologically confirmed or stable on follow-up images for 2 years or more. Kinetic information of the lesions regarding the degree and rate of enhancement on the first post-contrast-enhanced image and the enhancement curve type from two post-contrast-enhanced images were analyzed on a commercially available computer-assisted diagnosis system. The diagnostic performances of AB-MRI with morphological analysis alone and with the addition of kinetic information were compared using the McNemar test. Results: Of 207 lesions, 59 (28.5%) were malignant and 148 (71.5%) were benign. The addition of an enhancement degree of ≥90% to the morphological analysis significantly increased the specificity of AB-MRI (29.7% vs. 52.7%, p < 0.001) without significantly reducing the sensitivity (94.9% vs. 89.8%, p = 0.083) compared to morphological analysis alone. Unnecessary biopsy could have been avoided in 34 benign lesions, although three malignant lesions could have been missed. For detecting invasive cancer, adding an enhancement degree ≥107% to the morphological analysis significantly increased the specificity (26.5% vs. 57.6%, p < 0.001) without significantly decreasing the sensitivity (94.6% vs. 86.5%, p = 0.083). Conclusion: Adding the degree of enhancement on the first post-contrast-enhanced image to the morphological analysis resulted in higher AB-MRI specificity without compromising its sensitivity.

While the extrinsic factors affecting reproducibility of shear wave elastography (SWE) have been well documented, there are few resources assessing intrinsic characteristics of the lesion affecting the reproducibility and accuracy of SWE. In this regard, this study aimed to evaluate the accuracy of measured elasticity and the reproducibility of SWE according to the lesion size and stiffness. Two breast radiologists examined 20 targets of 4 different levels of stiffness and 5 different sizes (2.5, 4, 7, 11, and 18 mm) in a customized elasticity phantom. The B-mode image, color elastography image, and kPa measurement were obtained twice by each examiner with a 1-week interval. Inter- and intra-observer reproducibility and the accuracy of measured kPa were analyzed using intraclass correlation coefficient (ICC) and Bland-Altman analysis. Subgroup analysis was run to evaluate the effect of lesion size and stiffness on the reproducibility and accuracy of measured kPa. Inter- and intraobserver reproducibility for measuring kPa showed excellent agreement (ICC: 0.9742 and 0.9582; ICC: 0.9932 and 0.9294). The size and stiffness of the targets did not affect reproducibility. The overall accuracy of measured kPa was very high (ICC: 0.8049). In the subgroup analysis, targets that were ≤4 mm in size showed lower accuracy (ICC: 0.542), whereas targets that were 7 and 11 mm in size showed higher accuracy (ICC: 0.9832 and 0.9656, respectively). SWE shows excellent reproducibility regardless of lesion size or stiffness in phantom targets. The accuracy of measured kPa is high in lesions that are 7 and 11 mm in size but is low in lesions that are ≤4 mm in size.

This study aimed to investigate the differences in ultrasound (US) visibility for the localization of clipped metastatic lymph nodes after neoadjuvant chemotherapy (NAC), according to tissue marker type. This single-center retrospective study included 59 consecutive patients with breast cancer who underwent tissue marker insertion for histologically proven metastatic axillary lymph nodes before NAC, between March 2020 and August 2021. Two breast tissue markers were used: UltraClip™ (n = 29) and UltraCor™ Twirl™ (n = 30). The US visibility of tissue markers after NAC and the successful excision rate of the clipped lymph nodes were compared between the two types of tissue markers. UltraCor™ Twirl™ showed better overall US visibility than UltraClip™ after NAC (86.7% vs. 72.4%), but the difference was statistically insignificant. In the absence of residual metastatic lymph nodes on US after NAC (n = 32), UltraCor™ Twirl™ showed significantly better US visibility (83.3%, 15/18) than UltraClip™ (42.9%, 6/14; p = 0.027). The marker type was not associated with the successful excision of the clipped lymph node. UltraCor™ Twirl™ showed better US visibility than UltraClip™ in the metastatic axillary lymph nodes after NAC in the absence of residual suspicious lymph nodes on US.

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This study aimed to compare the background echotexture (BE) between automated breast ultrasound (ABUS) and handheld breast ultrasound (HHUS) and evaluate the correlation of BE with mammographic (MG) density and background parenchymal enhancement (BPE) on magnetic resonance imaging (MRI). A total of 212 women with newly diagnosed breast cancer who had undergone preoperative ABUS, HHUS, MG, and MRI were included. Two breast radiologists blinded to the menopausal status analyzed the BE of the contralateral breasts of the patients with breast cancer in consensus. The MG density and BPE of breast MRI on the radiologic reports were compared with the BE in the ultrasound. We used the cumulative link mixed model to compare the BE and Spearman rank correlation to evaluate the association between BE with MG density and BPE. BE was more heterogeneous in ABUS than in HHUS (P.001) and in the premenopausal group than in the postmenopausal group (P.001). The heterogeneity of BE in the premenopausal group was higher with ABUS than with HHUS (P = .013). BE and MG density showed a moderate correlation in the postmenopausal group, but a weak correlation in the premenopausal group. BE and BPE showed moderate correlations only in the premenopausal group. ABUS showed a more heterogeneous BE, especially in the premenopausal group. Therefore, more attention is required to interpret ABUS screening in premenopausal women.

This study aimed to investigate the effect of calcifications on shear-wave elastography in evaluating breast lesions. We retrospectively reviewed ultrasound images of 673 breast lesions and compared the elasticity between lesions with and without calcifications in three subgroups: benign lesions, in situ carcinomas and invasive carcinomas. Breast lesions were confirmed histologically (n = 401) or by follow-up images for more than 2 y (n = 272). Calcifications were present in 25.3% (170/673) of the lesions. The Emean values with and without calcifications, respectively, were as follows: 62.8 and 29.8 kPa in benign lesions (p = 0.000), 114.6 and 52.8 kPa in in situ carcinomas (p = 0.037) and 171.9 and 146.4 kPa in invasive carcinomas (p = 0.018). The presence of calcifications significantly increased the Emean of breast lesions. Shear-wave elastography should be carefully interpreted in benign lesions with calcifications and in situ carcinomas without calcifications.

We studied the relationship between breast ultrasound background echotexture (BET) and magnetic resonance imaging (MRI) background parenchymal enhancement (BPE) and whether this relationship varied with hormonal status and amount of fibroglandular tissue (FGT) on MRI. Two hundred eighty-three Korean women (52.1 years; range = 27-79 years) with newly diagnosed primary breast cancer who underwent preoperative breast ultrasound and MRI were retrospectively studied. Background echotexture, BPE, and FGT were classified into 4 categories, and age, menopausal status, menstrual cycle regularity, and menstrual cycle stage at MRI were recorded. Background echotexture and BPE relationship was assessed overall, and in menopausal, FGT, menstrual cycle regularity, and menstrual cycle stage subgroups. Background echotexture and BPE correlated in women overall, and menopausal, FGT, and menstrual cycle subgroups and those in the first half of the cycle (all P < 0.001). Background echotexture reflects BPE, regardless of menopausal status, menstrual cycle regularity, and FGT and may be a biomarker of breast cancer risk.

Purpose: The aim of this study was to evaluate the diagnostic value of shear-wave elastography (SWE) combined with Doppler ultrasonography (US) in selecting equivocal breast fibroepithelial lesions (FELs) for follow-up without further excision.Methods: A retrospective analysis was conducted of 88 patients with equivocal breast FELs (FELs with the possibility of both fibroadenoma [FA] and phyllodes tumor [PT]) diagnosed by core needle biopsy (CNB). For post-CNB treatment, surgical or vacuum-assisted excision was performed on 88 equivocal FELs, of which 56 were diagnosed as FAs and 32 as PTs on histopathology. Mean elasticity (Emean) and vascularity were determined using SWE and Doppler US. The diagnostic performances of B-mode US, SWE, and Doppler US were calculated to differentiate FAs and PTs in the excised equivocal FELs.Results: In the excised equivocal FELs diagnosed by CNB, FAs showed significantly lower median Emean values (36.4 vs. 66.7 kPa, P=0.005) and more frequent low vascularity (0–1 vessel flow signal) (P60.9 kPa and high vascularity (≥2 vessel flows) showed a sensitivity and negative predictive value of 100%, as well as better performance in other diagnostic values than B-mode US alone (Breast Imaging Reporting and Data System ≥4A) (all P

The purpose of our study was to evaluate the reproducibility of size measurement of breast lesions using automated breast ultrasonography (ABUS) compared with that with handheld ultrasonography (HHUS). Three breast radiologists performed HHUS and measured the lesions size in 2 different phantoms: lesions with various shape, size, and same stiffness (phantom 1) and lesions with same shape, size, and various stiffness (phantom 2). After 1 month, the same radiologists measured the lesion size of the same breast phantoms in the images obtained using ABUS. We evaluated interobserver variability between 3 radiologists in ABUS and HHUS, and intraobserver variability of radiologists between ABUS and HHUS. Intraclass correlation coefficient (ICC) was used in statistical analysis. The measured size of lesions on HHUS was slightly larger than that on ABUS in both phantom 1 and 2, although not statistically significant (P = 0.314, P = 0.858). There were no significant differences in size measurements between the radiologists' measurements and the reference size in phantom 2 (P = 0.862). The ICCs for the interobserver agreement between the 3 radiologists were 0.98 to 0.99 on ABUS and 0.99 to 1.00 on HHUS, respectively. The ICCs for the intraobserver agreement between ABUS and HHUS were 0.97 to 0.97 in phantom 1 and 0.98 to 0.99 in phantom 2. In conclusion, ABUS showed excellent interobserver and intraobserver agreement with HHUS in measuring size of the lesions, regardless of shape, size, and stiffness. Therefore, ABUS mixed with HHUS can be used reliably in following up breast lesions size.

To compare digital breast tomosynthesis (DBT) and MRI as an adjunct to full-field digital mammography (FFDM) for the preoperative evaluation of women with breast cancer based on mammographic density.This retrospective study enrolled 280 patients with breast cancer who had undergone FFDM, DBT, and MRI for preoperative local tumor staging. Three radiologists independently sought the index cancer and additional ipsilateral and contralateral breast cancers using either FFDM alone, DBT plus FFDM, or MRI plus FFDM. Diagnostic performances across the three radiologists were compared among the reading modes in all patients and subgroups with dense (n = 186) and non-dense breasts (n = 94) according to mammographic density.Of 280 patients, 46 (16.4%) had 48 additional (39 ipsilateral and nine contralateral) cancers in addition to the index cancer. For index cancers, both DBT plus FFDM and MRI plus FFDM showed sensitivities of 100% in the non-dense group. In the dense group, DBT plus FFDM showed lower sensitivity than that of MRI plus FFDM (94.6% vs. 99.6%,DBT plus FFDM showed an overall higher specificity than that of MRI plus FFDM regardless of breast density, perhaps without substantial loss in sensitivity and NPV in the diagnosis of additional cancers. Thus, DBT may have the potential to be used as a preoperative breast cancer staging tool.

Purpose Interest in unenhanced magnetic resonance imaging (MRI) screening for breast cancer is growing due to concerns about gadolinium deposition in the brain and the high cost of contrast-enhanced MRI. The purpose of this report is to describe the protocol of the Diffusion-Weighted Magnetic Resonance Imaging Screening Trial (DWIST), which is a prospective, multicenter, intraindividual comparative cohort study designed to compare the performance of mammography, ultrasonography, dynamic contrast-enhanced (DCE) MRI, and diffusion-weighted (DW) MRI screening in women at high risk of developing breast cancer. Methods A total of 890 women with BRCA mutation or family history of breast cancer and lifetime risk ≥ 20% are enrolled. The participants undergo 2 annual breast screenings with digital mammography, ultrasonography, DCE MRI, and DW MRI at 3.0 T. Images are independently interpreted by trained radiologists. The reference standard is a combination of pathology and 12-month follow-up. Each image modality and their combination will be compared in terms of sensitivity, specificity, accuracy, positive predictive value, rate of invasive cancer detection, abnormal interpretation rate, and characteristics of detected cancers. The first participant was enrolled in April 2019. At the time of manuscript submission, 5 academic medical centers in South Korea are actively enrolling eligible women and a total of 235 women have undergone the first round of screening. Completion of enrollment is expected in 2022 and the results of the study are expected to be published in 2026. Discussion DWIST is the first prospective multicenter study to compare the performance of DW MRI and conventional imaging modalities for breast cancer screening in high-risk women. DWIST is currently in the patient enrollment phase. Trial registration ClinicalTrials.gov Identifier: NCT03835897.

Background Data are limited regarding the performance of abbreviated screening breast MRI during consecutive years and the characteristics of breast cancers missed and detected with it. Purpose To assess the longitudinal diagnostic performance of abbreviated screening MRI and to determine whether the screening outcomes of abbreviated MRI differed between yearly time periods for 3 consecutive years. Materials and Methods This retrospective study included 1975 consecutive women who underwent abbreviated screening MRI between September 2015 and August 2018. Breast Imaging Reporting and Data System (BI-RADS) categories 3-5 defined positive results, and BI-RADS categories 1-2 defined negative results. Cancer detection rate (CDR), sensitivity, specificity, positive predictive value (PPV), abnormal interpretation rate (AIR), and interval cancer rate were assessed annually. Yearly performance measures were compared with the Fisher exact test by using the permutation method. Clinical-pathologic and imaging characteristics of the missed and detected cancers were compared by using the Fisher exact test and the Wilcoxon rank sum test. Results A total of 1975 women (median age, 49 years; interquartile range, 44-56 years) underwent 3037 abbreviated MRI examinations over 3 years. CDR (year 1 to year 3, 6.9-10.7 per 1000 examinations), positive predictive value for recall (9.7% [six of 62] to 15.6% [12 of 77]), positive predictive value for biopsy (31.6% [six of 19] to 63.2% [12 of 19]), sensitivity (75.0% [six of eight] to 80.0% [12 of 15]), and specificity (93.5% [807 of 863] to 94.1% [1041 of 1106]) were highest in year 3, and AIR (7.1% [62 of 871] to 6.9% [77 of 1121]) was lowest in year 3. However, all outcome measures did not differ statistically between years 1, 2, and 3 (all P > .05). The interval cancer rate was 0.66 per 1000 examinations (two of 3037). Thirty-eight breast cancers were identified in 36 women; 29 were detected with abbreviated MRI, but nine were missed. Of these, seven were detected with other imaging modalities after negative results at the last screening MRI examination, and two were interval cancers. All missed cancers were node-negative early-stage invasive cancers and were smaller (median size, 0.8 cm vs 1.2 cm; P = .01) than detected cancers. Conclusion Screening outcome measures of abbreviated MRI were sustained without significant differences between 3 consecutive years. All cancers missed at abbreviated MRI were node-negative invasive cancers and tended to be smaller than detected cancers. © RSNA, 2021 See also the editorial by Lee in this issue. Online supplemental material is available for this article.

A major limitation of screening breast ultrasound (US) is a substantial number of false-positive biopsy. This study aimed to develop a deep learning-based computer-aided diagnosis (DL-CAD)-based diagnostic model to improve the differential diagnosis of screening US-detected breast masses and reduce false-positive diagnoses. In this multicenter retrospective study, a diagnostic model was developed based on US images combined with information obtained from the DL-CAD software for patients with breast masses detected using screening US; the data were obtained from two hospitals (development set: 299 imaging studies in 2015). Quantitative morphologic features were obtained from the DL-CAD software, and the clinical findings were collected. Multivariable logistic regression analysis was performed to establish a DL-CAD-based nomogram, and the model was externally validated using data collected from 164 imaging studies conducted between 2018 and 2019 at another hospital. Among the quantitative morphologic features extracted from DL-CAD, a higher irregular shape score (P = .018) and lower parallel orientation score (P = .007) were associated with malignancy. The nomogram incorporating the DL-CAD-based quantitative features, radiologists’ Breast Imaging Reporting and Data Systems (BI-RADS) final assessment (P = .014), and patient age (P P P P = .317 in the development cohort; each 100% in the validation cohort). In conclusion, the proposed model showed good performance for differentiating screening US-detected breast masses, thus demonstrating a potential to reduce unnecessary biopsies.

This study aimed to investigate the impact of baseline values and temporal changes in body composition parameters, including skeletal muscle index (SMI) and visceral adipose tissue area (VAT), measured using serial computed tomography (CT) imaging on the prognosis of operable breast cancers in Asian patients.This study retrospectively included 627 Asian female (mean age ± standard deviation [SD], 53.6 ± 8.3 years) who underwent surgery for stage I-III breast cancer between January 2011 and September 2012. Body composition parameters, including SMI and VAT, were semi-automatically calculated on baseline abdominal CT at the time of diagnosis and follow-up CT for post-treatment surveillance. Serial changes in SMI and VAT were calculated as the delta values. Multivariable Cox regression analysis was used to evaluate the association of baseline and delta SMI and VAT values with disease-free survival.Among 627 patients, 56 patients (9.2%) had breast cancer recurrence after a median of 40.5 months. The mean value ± SD of the baseline SMI and baseline VAT were 43.7 ± 5.8 cm²/m² and 72.0 ± 46.0 cm², respectively. The mean value of the delta SMI was -0.9 cm²/m² and the delta VAT was 0.5 cm². The baseline SMI and VAT were not significantly associated with disease-free survival (adjusted hazard ratio [HR], 0.983; 95% confidence interval [CI], 0.937-1.031;Our study revealed that baseline and early temporal changes in SMI and VAT were not independent prognostic factors regarding disease-free survival in Asian patients undergoing surgery for breast cancer.

With the increase in the number of cases of silicone implant insertion either for cosmetic surgery or breast reconstruction after mastectomy, it is not unusual to encounter patients with silicone implants in clinical settings. Recently, the first case of breast implant-associated anaplastic large cell lymphoma was reported in Korea. In addition to previously known complications, such as implant rupture or contracture, the number of implant-associated imaging examinations has also increased. Considering this background, radiologists should have sufficient knowledge about the type of examination required in patients who have undergone implant insertion and imaging findings to correctly identify implant-associated complications. In this article, various complications of silicone implants are discussed, including various imaging findings, which radiologists should know.

The purpose of this study was to identify perfusional subregions sharing similar kinetic characteristics from dynamic contrast-enhanced magnetic resonance imaging (MRI) using data-driven clustering, and to evaluate the effect of perfusional heterogeneity based on those subregions on patients’ survival outcomes in various risk models. From two hospitals, 308 and 147 women with invasive breast cancer who underwent preoperative MRI between October 2011 and July 2012 were retrospectively enrolled as development and validation cohorts, respectively. Using the Cox-least absolute shrinkage and selection operator model, a habitat risk score (HRS) was constructed from the radiomics features from the derived habitat map. An HRS-only, clinical, combined habitat, and two conventional radiomics risk models to predict patients’ disease-free survival (DFS) were built. Patients were classified into low-risk or high-risk groups using the median cutoff values of each risk score. Five habitats with distinct perfusion patterns were identified. An HRS was an independent risk factor for predicting worse DFS outcomes in the HRS-only risk model (hazard ratio = 3.274 [95% CI = 1.378–7.782]; p = 0.014) and combined habitat risk model (hazard ratio = 4.128 [95% CI = 1.744–9.769]; p = 0.003) in the validation cohort. In the validation cohort, the combined habitat risk model (hazard ratio = 4.128, p = 0.003, C-index = 0.760) showed the best performance among five different risk models. The quantification of perfusion heterogeneity is a potential approach for predicting prognosis and may facilitate personalized, tailored treatment strategies for breast cancer.

Purpose: To develop a radiomics signature based on preoperative MRI to estimate disease-free survival (DFS) in patients with invasive breast cancer and to establish a radiomics nomogram that incorporates the radiomics signature and MRI and clinicopathological findings. Experimental Design: We identified 294 patients with invasive breast cancer who underwent preoperative MRI. Patients were randomly divided into training (n = 194) and validation (n = 100) sets. A radiomics signature (Rad-score) was generated using an elastic net in the training set, and the cutoff point of the radiomics signature to divide the patients into high- and low-risk groups was determined using receiver-operating characteristic curve analysis. Univariate and multivariate Cox proportional hazards model and Kaplan–Meier analysis were used to determine the association of the radiomics signature, MRI findings, and clinicopathological variables with DFS. A radiomics nomogram combining the Rad-score and MRI and clinicopathological findings was constructed to validate the radiomic signatures for individualized DFS estimation. Results: Higher Rad-scores were significantly associated with worse DFS in both the training and validation sets (P = 0.002 and 0.036, respectively). The radiomics nomogram estimated DFS [C-index, 0.76; 95% confidence interval (CI); 0.74–0.77] better than the clinicopathological (C-index, 0.72; 95% CI, 0.70–0.74) or Rad-score–only nomograms (C-index, 0.67; 95% CI, 0.65–0.69). Conclusions: The radiomics signature is an independent biomarker for the estimation of DFS in patients with invasive breast cancer. Combining the radiomics nomogram improved individualized DFS estimation. Clin Cancer Res; 24(19); 4705–14. ©2018 AACR.

Purpose To evaluate the value of preoperative axillary ultrasonography (US) for preventing unnecessary axillary lymph node dissection after sentinel lymph node (SLN) biopsy in a large series of patients with early-stage breast cancers treated with both breast-conserving surgery and SLN biopsy. Materials and Methods From March 2009 to February 2013, 1802 patients who underwent breast-conserving surgery for clinical T1-2/N0 cancers and SLN biopsy with or without axillary lymph node dissection were included. Preoperative axillary US results and clinical-pathologic variables were compared according to the status of non-SLN metastasis. Multivariate logistic regression analysis was performed to find factors associated with non-SLN metastasis. Results Of 1802 patients, 397 (22.0%) underwent axillary lymph node dissection due to positive SLN biopsy and 76 (4.2%) had non-SLN metastasis at final histopathologic examination. Patients with non-SLN metastasis were younger and showed positive axilla at US and clinical T2 stage more frequently (P < .05). At multivariate analysis, positive axilla at US (P = .001), clinical T2 stage (P = .005), and lymphovascular invasion (P < .001) were significantly associated with non-SLN metastasis. Among 1284 patients with negative axilla at US and clinical T1 stage cancer, 1254 (97.7%) did not have non-SLN metastasis and 30 (2.3%) had non-SLN metastasis. Conclusion Preoperative axillary US results and clinical T stage are associated with the status of non-SLN metastasis in patients with early breast cancer. The results of this study suggest that preoperative axillary US can help select patients at minimal risk of non-SLN metastasis, for whom axillary lymph node dissection can be omitted. © RSNA, 2018 Online supplemental material is available for this article.

To compare the performance of synthetic mammography (SM) and digital mammography (DM) with digital breast tomosynthesis (DBT) or alone for the evaluation of microcalcifications. This retrospective study includes 198 mammography cases, all with DM, SM, and DBT images, from January to October 2013. Three radiologists interpreted images and recorded the presence of microcalcifications and their conspicuity scores and final BI-RADS categories (1, 2, 3, 4a, 4b, 4c, 5). Readers' area under the ROC curves (AUCs) were analyzed for SM plus DBT vs. DM plus DBT and SM alone vs. DM alone using the BI-RADS categories for the overall group and dense breast subgroup. Conspicuity scores of detected microcalcifications were neither significantly different between SM and DM with DBT nor alone (p>0.05). In predicting malignancy of detected microcalcifications, no significant difference was found between readers' AUCs for SM and DM with DBT or alone in the overall group or dense breast subgroup (p>0.05). Diagnostic performances of SM and DM for the evaluation of microcalcifications are not significantly different, whether performed with DBT or alone. • In DBT-imaging, SM and DM show comparable performances when evaluating microcalcifications. • For BI-RADS classification of microcalcifications, SM and DM show similar AUCs. • DBT with SM may be sufficient for diagnosing microcalcifications, without DM.

Background Ultrasonography (US) is an important tool to evaluate the status of internal mammary lymph node (IMN). US features of metastatic IMNs could help determine when biopsy should be performed. Purpose To compare US features of metastatic IMNs to those of benign entities. Material and Methods In women with suspected IMN metastasis on US, their intercostal space (ICS) abnormalities were classified into metastatic IMN, benign IMN, and lymph node (LN) mimickers. US features, distribution, and depth of abnormalities in one ICS and involved ICS level were analyzed. Results Among 66 ICS abnormalities in 53 women, 46 were metastatic IMNs, ten were benign IMNs, and ten were LN mimickers. For metastatic IMNs, the second ICS was the most commonly involved ICS (n = 22), followed by the first (n = 13), the third (n = 8), and the fourth (n = 3). ICS level distribution of metastatic IMNs was not significantly ( P = 0.5407) different from that of non-metastatic lesions. Metastatic IMNs were predominantly seen in the posterior layer of ICS, significantly ( P Conclusion Metastatic IMNs are more likely to be found in the posterior layer of ICS. This can help distinguish them from LN mimickers. Any part (upper, middle, or lower) of one ICS in craniocaudal direction could be involved. The second ICS was the most commonly involved level.

Purpose To determine the relationship between tumor heterogeneity assessed by means of magnetic resonance (MR) imaging texture analysis and survival outcomes in patients with primary breast cancer. Materials and Methods Between January and August 2010, texture analysis of the entire primary breast tumor in 203 patients was performed with T2-weighted and contrast material-enhanced T1-weighted subtraction MR imaging for preoperative staging. Histogram-based uniformity and entropy were calculated. To dichotomize texture parameters for survival analysis, the 10-fold cross-validation method was used to determine cutoff points in the receiver operating characteristic curve analysis. The Cox proportional hazards model and Kaplan-Meier analysis were used to determine the association of texture parameters and morphologic or volumetric information obtained at MR imaging or clinical-pathologic variables with recurrence-free survival (RFS). Results There were 26 events, including 22 recurrences (10 local-regional and 12 distant) and four deaths, with a mean follow-up time of 56.2 months. In multivariate analysis, a higher N stage (RFS hazard ratio, 11.15 [N3 stage]; P = .002, Bonferroni-adjusted α = .0167), triple-negative subtype (RFS hazard ratio, 16.91; P.001, Bonferroni-adjusted α = .0167), high risk of T1 entropy (less than the cutoff values [mean, 5.057; range, 5.022-5.167], RFS hazard ratio, 4.55; P = .018), and T2 entropy (equal to or higher than the cutoff values [mean, 6.013; range, 6.004-6.035], RFS hazard ratio = 9.84; P = .001) were associated with worse outcomes. Conclusion Patients with breast cancers that appeared more heterogeneous on T2-weighted images (higher entropy) and those that appeared less heterogeneous on contrast-enhanced T1-weighted subtraction images (lower entropy) exhibited poorer RFS.

PURPOSE To analyze the malignancy rate of ultrasound-guided core needle biopsy (US-CNB) for screen-detected breast lesions and to evaluate the results according to the mode of detection of the target lesions. METHODS This is a retrospective review of 703 consecutive women who underwent US-CNB for screen-detected breast lesions at a single tertiary hospital. Breast Imaging Reporting and Data System (BI-RADS) categories and histopathological results of the target lesions were assessed. The cases were divided into two groups: the mammography-based detected lesions (M-group) and the US-based detected lesions (U-group). The biopsy performances of the two groups were compared using the χ2 test. RESULTS The malignancy rate in the entire population was 22.0%: 0.8%, 12.3%, 65.2%, 89.3%, and 94.6% in BI-RADS categories 3, 4A, 4B, 4C, and 5, respectively. The malignancy rate was significantly higher in the M-group (54.1% [79/146]) than in the U-group (13.6% [76/557]) (p < 0.001). BI-RADS category 3 was the most common assessment overall that led to a US-CNB (362/703, 51.5%) and the rate of BI-RADS category 3 diagnoses that led to US-CNB was significantly higher in the U-group (p < 0.001). CONCLUSIONS The malignancy rate associated with US-CNB for screen-detected breast lesions was 22.0%. The breast lesions detected by mammography have a higher malignancy rate than those detected by US. © 2016 Wiley Periodicals, Inc. J Clin Ultrasound 45:261-266, 2017.

To investigate factors related to false shear wave elastography (SWE) results for breast non-mass lesions (NMLs) detected by B-mode US. This retrospective study enrolled 152 NMLs detected by B-mode US and later pathologically confirmed (79 malignant, 73 benign). All lesions underwent B-mode US and SWE. Quantitative (mean elasticity [E mean]) and qualitative (maximum stiffness colour) SWE parameters were assessed, and ‘E mean > 85.1 kPa’ or ‘stiff colour (green to red)’ determined malignancy. Final SWE results were matched to pathology results. Multivariate logistic regression analysis identified factors associated with false SWE results for diagnosis of breast NMLs. Associated calcifications (E mean: odds ratio [OR] = 7.60, P

Objective: To compare the diagnostic performance of breast MRI with abbreviated protocol (AB-MRI) and full ddiagnostic protocol (FDP-MRI) for surveillance of females with a personal history of breast cancer Methods: In this retrospective study, we analyzed the outcomes of total 1312 post-operative screening breast MRI matched from 1045 AB-MRI and 677 FDP-MRI, which had histologic confirmation for suspicious MRI findings or 1 year negative follow-up images. This study was approved by the institutional review board and informed patient consent was waved. AB-MRI consists of T2 weighted scanning and dynamic contrast-enhanced imaging including one pre-contrast and two post-contrast scans. We compared the diagnostic performance for recurrent breast cancer in terms of sensitivity, specificity, positive-predictive value, negative-predictive value, and accuracy and area under the curve between the screening AB-MRI and FDP-MRI. Results: Overall, 13 recurrent tumors among 1312 post-operative cases screened with breast MRI (1.0%) were detected including 8 invasive cancer, 2 cases of in situ cancer, and 3 cases of metastatic lymph nodes. The sensitivity and negative predictive value were 70 vs 100 and 99.5% vs 100% in AB-MRI and FDP-MRI. Specificity, positive predictive value, accuracy, and area under the curve of AB-MRI and FDP-MRI were 98.0% vs 96.9%, 35.0% vs 23.1%, 97.6% vs 97.0%, and 0.840 vs 0.985, respectively. Conclusion: The performance of AB-MRI was comparable to that of FDP-MRI in detecting recurrent breast cancer and decreased false positive cases. Advances in knowledge: AB-MRI provides a reliable alternative with similar diagnostic performance and shorter MRI acquisition time.

Summary: Background: Mammography is the current standard for breast cancer screening. This study aimed to develop an artificial intelligence (AI) algorithm for diagnosis of breast cancer in mammography, and explore whether it could benefit radiologists by improving accuracy of diagnosis. Methods: In this retrospective study, an AI algorithm was developed and validated with 170 230 mammography examinations collected from five institutions in South Korea, the USA, and the UK, including 36 468 cancer positive confirmed by biopsy, 59 544 benign confirmed by biopsy (8827 mammograms) or follow-up imaging (50 717 mammograms), and 74 218 normal. For the multicentre, observer-blinded, reader study, 320 mammograms (160 cancer positive, 64 benign, 96 normal) were independently obtained from two institutions. 14 radiologists participated as readers and assessed each mammogram in terms of likelihood of malignancy (LOM), location of malignancy, and necessity to recall the patient, first without and then with assistance of the AI algorithm. The performance of AI and radiologists was evaluated in terms of LOM-based area under the receiver operating characteristic curve (AUROC) and recall-based sensitivity and specificity. Findings: The AI standalone performance was AUROC 0·959 (95% CI 0·952–0·966) overall, and 0·970 (0·963–0·978) in the South Korea dataset, 0·953 (0·938–0·968) in the USA dataset, and 0·938 (0·918–0·958) in the UK dataset. In the reader study, the performance level of AI was 0·940 (0·915–0·965), significantly higher than that of the radiologists without AI assistance (0·810, 95% CI 0·770–0·850; p

To develop a classification system using imaging features to interpret breast non-mass lesions (NMLs) detected on US and to stratify their cancer risk. This retrospective study included 715 patients with 715 breast NMLs detected on breast US from 2012 to 2016. Each patient underwent mammography at the time of diagnosis. Radiologists assessed US and mammographic features and final BI-RADS categories. Multivariable logistic regression was used to find imaging features associated with malignancy in a development dataset (n = 460). A system to classify BI-RADS categories (3 to 5) was developed based on the odds ratios (ORs) of imaging features significantly associated with malignancy and validated in a distinct validation dataset (n = 255). Among 715 NMLs, 385 (53.8%) were benign and 330 (46.2%) were malignant. In the development dataset, the following B-mode US features were associated with malignancy (all p < 0.001): segmental distribution (OR = 3.03; 95% confidence interval [CI], 1.50–6.15), associated calcifications (OR = 4.26; 95% CI, 1.62–11.18), abnormal ductal change (OR = 4.91; 95% CI, 2.07–11.68), and posterior shadowing (OR = 20.20; 95% CI, 6.46–63.23). The following mammographic features were also associated with malignancy (all p < 0.001): calcifications (OR = 7.98; 95% CI, 3.06–20.81) and focal asymmetry (OR = 4.75; 95% CI, 1.90–11.88). In the validation dataset, our classification system using US and mammography showed a higher area under the curve (0.951–0.956) compared to when it was not applied (0.908–0911) to predict malignancy with BI-RADS categories (p < 0.05). Our classification system which incorporates US and mammographic features of breast NMLs can help interpret and manage all NMLs detected on breast US by stratifying cancer risk according to BI-RADS categories. • When diagnosing breast NMLs detected on US, suspicious US features are segmental distribution, associated abnormal ductal change, calcifications, and posterior shadowing within or around the NML on B-mode US, while a probably benign US feature is the presence of multiple small cysts. • Corresponding suspicious mammographic features of breast NMLs detected on US are associated calcifications and focal asymmetry. • Our classification system which incorporates US features with and without mammography can potentially be used to interpret and manage any NMLs detected on breast US in clinical practice.

Background The relationship between method of breast cancer screening (mammography or US) and survival outcome in patients with screening-detected ductal carcinoma in situ (DCIS) has not been determined. Purpose To investigate whether different methods of breast cancer screening are associated with different survival outcomes in patients with screening-detected DCIS and to evaluate clinical-pathologic and imaging factors associated with second breast cancer. Materials and Methods We retrospectively identified women who underwent surgery to treat DCIS initially detected with screening mammography or US between July 2004 and December 2011 in a single institution. Overall survival (OS) and disease-free survival (DFS) were assessed. Factors associated with second breast cancer (invasive carcinoma or DCIS) were found with multivariable Cox proportional hazards regression analysis. Subgroups were analyzed according to screening method. Results A total of 814 women (median age, 47 years; age range, 25-81 years) were included; 627 underwent treatment for screening mammography-detected DCIS (mammography-detected group), and 187 underwent treatment for screening US-detected DCIS (US-detected group). During follow-up (median, 7 years; interquartile range, 5-8 years), 26 ipsilateral and 26 contralateral second breast cancers (6.4%, 52 of 814) were found, with 44 in the mammography-detected group and eight in the US-detected group. The overall 5-year OS and DFS rates were 100% and 95.3%, respectively. DFS rates did not differ according to screening method (P = .21, 5-year DFS rates were 94.9% in the mammography-detected group and 96.5% in the US-detected group). In the mammography-detected group, higher nuclear grade (intermediate grade: hazard ratio [HR], 5.7; 95% confidence interval [CI]: 1.3, 24.3; P = 0.02) (high grade: HR, 8.0; 95% CI: 1.9, 34.2; P = .01) and dense breast (HR, 3.5; 95% CI: 1.1, 11.4; P = 0.04) were associated with second breast cancer. In the US-detected group, human epidermal growth factor receptor 2 positivity was associated with second breast cancer (HR, 9.2; 95% CI: 2.2, 38.5; P = .002). Conclusion Disease-free survival of patients who underwent treatment for screening-detected ductal carcinoma in situ (DCIS) did not differ according to screening detection method. In patients with screening mammography-detected DCIS, higher nuclear grade and dense breast were associated with second breast cancer, and in patients with screening US-detected DCIS, human epidermal growth factor 2 positivity was associated with second breast cancer. © RSNA, 2019 Online supplemental material is available for this article. See also the editorial by Fowler in this issue.

This study aimed to compare the accuracy and inter- and intra-observer reproducibility of the measured elasticity between 2 shear wave elastography systems. Three breast radiologists examined 8 targets of 4 different levels of stiffness (size: 11 mm, 4 mm) in an elasticity phantom (Customized 049A Elasticity QA Phantom, CIRS, Norfolk, VA, USA) using 2 different shear wave ultrasound elastography systems: SuperSonic Imagine (SSI) (SSI, Aix en Provence, France) and ShearScan (RS-80A, Samsung Medison, Seoul, Korea). Three radiologists performed ultrasound (US) elastography examinations for the phantom lesions using 2 equipment over a 1-week interval. Intra- and inter-observer reproducibility and the accuracy of the measured elasticity were analyzed and compared between the 2 systems. The accuracy of shape was also analyzed by shape-matching between B-mode and elastography color image. Intra-class correlation coefficients (ICC) were used in statistical analysis. For measured elasticity, the intra-observer and inter-observer reproducibility were excellent in both SSI and ShearScan (0.994 and 0.998). The overall accuracy was excellent in both systems, but the accuracy in small lesions (4 mm target) was lower in SSI than ShearScan (0.780 vs 0.967). The accuracy of shape-matching on the elastography image was 59.0% and 81.4% in the SSI and ShearScan, respectively. In conclusion, the SSI and ShearScan showed excellent intra- and inter-observer reproducibility. The accuracy of the Young's modulus was high in both the SSI and ShearScan, but the SSI showed decreased accuracy in measurement of elasticity in small targets and poor shape-matching between the B-mode image and color-coded elastography image.

Purpose To evaluate the accuracy of magnetic resonance imaging (MRI)-guided breast biopsy. Methods We retrospectively reviewed the clinical data of 111 consecutive patients referred for MRI-guided breast biopsy after mammography and breast ultrasound between May 2009 and April 2019. After excluding 37 patients without follow-up images (> 2 years), 74 patients (74 lesions) were finally included. We reviewed the histologic results of MRI-guided biopsy and subsequent surgery, post-biopsy management, and breast cancer development during follow-up. We investigated the false-negative rate, ductal carcinoma in situ (DCIS) underestimation, atypical ductal hyperplasia (ADH) underestimation rate, and technical failure rate of MRI-guided biopsy. Results Among 74 scheduled MRI-guided biopsies, six were canceled because biopsy was deemed unnecessary, while three failed due to technical difficulties (technical failure rate: 3/68, 4.4%). MRI-guided biopsy was performed in 65 patients, of which 18 patients were diagnosed with malignant lesions, 46 with benign lesions, and one with ADH bordering on DCIS. Subsequent surgery (n = 27) showed DCIS underestimation in three cases (3/7, 43%), ADH underestimation in two cases (1/2, 50%), as well as seven concordant benign and 11 concordant malignant lesions. The overall false-negative rate was 4.3% (2/46). Thirty-eight out of 48 benign lesions were followed-up (median period, 5.8 years; interquartile range, 4.1 years) without subsequent surgery. Thirty-seven concordant benign lesions were stable (n = 27) or disappeared (n = 10); however, the size of one discordant benign lesion increased on follow-up MRI and it was diagnosed as DCIS after 1 year. Conclusion MRI-guided biopsy is an accurate method for exclusion of malignancy with a very low false-negative rate.

Axillary ultrasonography (US) is the most commonly used imaging modality for nodal evaluation in patients with breast cancer. No Axillary Surgical Treatment in Clinically Lymph Node-Negative Patients after Ultrasonography (NAUTILUS) is a prospective, multicenter, randomized controlled trial investigating whether sentinel lymph node biopsy (SLNB) can be safely omitted in patients with clinically and sonographically node-negative T1-2 breast cancer treated with breast-conserving therapy. In this trial, a standardized imaging protocol and criteria were established for the evaluation of axillary lymph nodes. Women lacking palpable lymph nodes underwent axillary US to dismiss suspicious nodal involvement. Patients with a round hypoechoic node with effaced hilum or indistinct margins were excluded. Patients with T1 tumors and a single node with a cortical thickness ≥ 3 mm underwent US-guided biopsy. Finally, patients with negative axillary US findings were included. The NAUTILUS axillary US nodal assessment criteria facilitate the proper selection of candidates who can omit SLNB. Trial Registration: ClinicalTrials.gov Identifier: NCT04303715.

Objective To investigate whether a computer-aided diagnosis (CAD) system based on a deep learning framework (deep learning-based CAD) improves the diagnostic performance of radiologists in differentiating between malignant and benign masses on breast ultrasound (US). Materials and Methods B-mode US images were prospectively obtained for 253 breast masses (173 benign, 80 malignant) in 226 consecutive patients. Breast mass US findings were retrospectively analyzed by deep learning-based CAD and four radiologists. In predicting malignancy, the CAD results were dichotomized (possibly benign vs. possibly malignant). The radiologists independently assessed Breast Imaging Reporting and Data System final assessments for two datasets (US images alone or with CAD). For each dataset, the radiologists' final assessments were classified as positive (category 4a or higher) and negative (category 3 or lower). The diagnostic performances of the radiologists for the two datasets (US alone vs. US with CAD) were compared. Results When the CAD results were added to the US images, the radiologists showed significant improvement in specificity (range of all radiologists for US alone vs. US with CAD: 72.8–92.5% vs. 82.1–93.1%; p < 0.001), accuracy (77.9–88.9% vs. 86.2–90.9%; p = 0.038), and positive predictive value (PPV) (60.2–83.3% vs. 70.4–85.2%; p = 0.001). However, there were no significant changes in sensitivity (81.3–88.8% vs. 86.3–95.0%; p = 0.120) and negative predictive value (91.4–93.5% vs. 92.9–97.3%; p = 0.259). Conclusion Deep learning-based CAD could improve radiologists' diagnostic performance by increasing their specificity, accuracy, and PPV in differentiating between malignant and benign masses on breast US.

To evaluate the interpretative performance of two-dimensional (2D) synthetic mammography (SM) reconstructed from digital breast tomosynthesis (DBT) in the detection of T1-stage invasive breast cancers, compared to 2D full-field digital mammography (FFDM).This retrospective study enrolled 214 patients. For each patient, FFDM and DBT were performed between January and June 2013, and SM was reconstructed from DBT data. Three radiologists interpreted images and recorded visibility scores and morphologies of cancers. Diagnostic performances of SM and FFDM were compared. Percentages of detected cancers and visibility scores were compared for tumour size, and presence of calcifications for each observer.Observer sensitivity showed no difference for detection with SM and FFDM (P 0.05). One observer showed a higher specificity (P = 0.02) and higher positive predictive value with SM (95 % CI 0.6-16.4), but the differences in the corresponding values between SM and FFDM for the other observers were not statistically significant. In subgroup analyses according to tumour size and presence of calcifications, percentages of detected cancers and visibility scores were not significantly different.Diagnostic performances of SM and FFDM are comparable for detecting T1-stage breast cancers. Therefore, our results indicate that SM may eliminate the need for additional FFDM during DBT-based imaging.• DBT plus FFDM increases radiation dose compared to FFDM alone. • Detecting T1-stage cancers with only SM is comparable to detection with FFDM. • Two-dimensional SM may replace dose-requiring FFDM in DBT-based imaging.

Objective To determine what percentage of cancers, detected by screening ultrasonography (US), were detectable by full-field digital mammography (FFDM) and digital breast tomosynthesis (DBT). Materials and methods Eighty-four consecutive women in whom mammography was negatively interpreted and supplementary screening US initially detected breast cancers at outside hospitals underwent both FFDM and DBT. We excluded cases with overt suspicious findings on repeat mammography and ineligible cases. In the remaining 41 cases, three radiologists who were blinded to tumor location, even though they were aware that they had breast cancers independently reviewed both FFDM and DBT. The reference standard was the reference FFDM made by two unblinded reviewers who were aware of the tumor location and shape on DBT, US, and magnetic resonance imaging (MRI). The visibility score based on the correct marking was compared between FFDM and DBT. Results Among the 41 cases, the cancers were visible in 25 (61.0%) on FFDM and in 34 (82.9%) on DBT ( P = 0.047) by the unblinded review. In the blinded analysis, the cancers were significantly more "constantly visible" in the three radiologists on DBT than on FFDM [53.7% (22/41) vs. 26.8% (11/41), respectively, P = 0.013]. The dominant lesion type was "focal asymmetry" on DBT (39.0%) and "asymmetry" on FFDM (31.7%). Conclusions Our analysis suggests that 54% of cancers that were detected by US and were not evident on 2D mammography were detectable by screening using DBT. Additional 29% of cancers were visualized on DBT, when the area of concern was known.

Two automated volumetric breast density analyses of 44 patients who underwent image-guided needle localization in one breast were compared to calculate the agreement of assessment parameters in short-term digital mammography reimaging. The outputs of the automated volumetric breast density method included four parameters [fibroglandular tissue volume (Vfg), total breast volume (Vb), volumetric breast density (Vbd), and area breast density (Abd)]. The variability and agreement of each parameter were calculated in serial mammograms. There was no significant difference in mean Vfg, Vb, Vbd, or Abd between two mammograms (P = .249, .053, .727, and .603, respectively).

Background Further information is needed regarding whether histopathological characteristics affect breast tumor elasticity. Purpose To determine whether maximum elasticity values vary according to tumor-stroma ratio, dominant stroma type, or presence of fibrosis in invasive breast cancer. Material and Methods This study included 71 patients with invasive ductal carcinoma not otherwise specified (IDC NOS) who underwent breast shear-wave elastography (SWE). Maximum elasticity (Emax) values were retrospectively correlated with pathological findings that included tumor-stroma ratio, dominant stroma type (collagen, fibroblast, lymphocyte), and fibrosis. Multiple linear regression analysis was performed to determine variables independently associated with Emax. Results High histologic grade was significantly correlated with higher Emax ( P = 0.042). Estrogen receptor and progesterone receptor expression negatively correlated with high elasticity values ( P = 0.013 and P = 0.03, respectively). Breast cancers that exhibited higher cellularity demonstrated a greater level of stiffness that was not statistically significant (ρ = 0.153; P = 0.193). While dominant stroma type and fibrosis did not affect Emax ( P = 0.197 and P = 0.598, respectively), lesion size was significantly associated with Emax (ρ = 0.474, P max ( P Conclusion The composition of tumors did not affect their Emax.

The purpose of this study was to determine whether the apparent diffusion coefficient (ADC) and tumor detectability based on diffusion-weighted imaging (DWI) are affected by the menstrual cycle or menopausal status in breast cancer patients. Institutional review board approval was obtained, and the requirement for informed consent was waived. A total of 124 women with invasive ductal carcinoma not otherwise specified (IDC NOS) who underwent breast MRI with DWI were included in this study. Two radiologists retrospectively measured the ADCs of tumor and contralateral normal glandular tissue and scored the tumor detectability. The ADCs and detectability were compared to menstrual cycle and menopausal status, based on patient questionnaires. ADCs of tumors and contralateral tissue were significantly lower in postmenopausal women than in premenopausal women (P = 0.006 and P < 0.001, respectively). Tumor detectability did not differ significantly between the premenopausal and postmenopausal groups (P = 0.454). Normalized ADCs were not significantly lower in postmenopausal women compared to premenopausal women (P = 0.880). There was no statistically significant difference in the absolute, contralateral, and normalized ADCs (P = 0.091, 0.809, and 0.299, respectively), and the tumor detectability (P = 0.680) according to the menstrual cycle. Although ADCs of the IDC and normal glandular tissue in postmenopausal women were significantly lower than those in premenopausal women, the menstrual cycle did not affect tumor detectability and ADCs of IDC.

PURPOSE The purpose of this study was to investigate the final outcomes of magnetic resonance imaging (MRI)-identified additional lesions (MRALs) in breast cancer patients and the role of second-look ultrasound (SLUS) and imaging-guided interventions. METHODS We analyzed breast cancer patients with MRALs on preoperative MRI between January and June 2012. MRALs were defined as additional lesions suspected on MRI but not suspected on mammograms or ultrasound. The malignancy rate of MRALs, MRI-based Breast Imaging Reporting and Database System (BI-RADS) category, positional relationship with the index cancer, MRI-concordant lesion visibility on SLUS, performance of imaging-guided interventions, and total mastectomy (TM) rates were evaluated for the confirmed lesions. RESULTS Among the 119 confirmed lesions, SLUS and imaging-guided interventions were performed in 94 (79.0%) and 82 cases (68.9%), respectively. The malignancy rate was 68.1% (81 of 119), and was significantly higher in BI-RADS 4C-5 lesions than in 4A-4B lesions (94.6% vs. 56.1%, P