Multimodality Imaging of Benign and Malignant Diseases of the Nipple-Areolar Complex.

The nipple-areolar complex (NAC), a unique anatomic structure of the breast, encompasses the terminal intramammary ducts and skin appendages. Several benign and malignant diseases can arise within the NAC. As several conditions have overlapping symptoms and imaging findings, understanding the distinctive nipple anatomy, as well as the clinical and imaging features of each NAC disease process, is essential. A multimodality imaging approach is optimal in the presence or absence of clinical symptoms. The authors review the ductal anatomy and anomalies, including congenital abnormalities and nipple retraction. They then discuss the causes of nipple discharge and highlight best practices for the imaging workup of pathologic nipple discharge, a common condition that can pose a diagnostic challenge and may be the presenting symptom of breast cancer. The imaging modalities used to evaluate and differentiate benign conditions (eg, dermatologic conditions, epidermal inclusion cyst, mammary ductal ectasia, periductal mastitis, and nonpuerperal abscess), benign tumors (eg, papilloma, nipple adenoma, and syringomatous tumor of the nipple), and malignant conditions (eg, breast cancer and Paget disease of the breast) are reviewed. Breast MRI is the current preferred imaging modality used to evaluate for NAC involvement by breast cancer and select suitable candidates for nipple-sparing mastectomy. Different biopsy techniques (US -guided biopsy and stereotactic biopsy) for sampling NAC masses and calcifications are described. This multimodality imaging approach ensures an accurate diagnosis, enabling optimal clinical management and patient outcomes. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Diffusion Tensor Imaging for Characterizing Changes in Triple-Negative Breast Cancer During Neoadjuvant Systemic Therapy.

BACKGROUND: Assessment of treatment response in triple-negative breast cancer (TNBC) may guide individualized care for improved patient outcomes. Diffusion tensor imaging (DTI) measures tissue anisotropy and could be useful for characterizing changes in the tumors and adjacent fibroglandular tissue (FGT) of TNBC patients undergoing neoadjuvant systemic treatment (NAST). PURPOSE: To evaluate the potential of DTI parameters for prediction of treatment response in TNBC patients undergoing NAST. STUDY TYPE: Prospective. POPULATION: Eighty-six women (average age: 51 ± 11 years) with biopsy-proven clinical stage I-III TNBC who underwent NAST followed by definitive surgery. 47% of patients (40/86) had pathologic complete response (pCR). FIELD STRENGTH/SEQUENCE: 3.0 T/reduced field of view single-shot echo-planar DTI sequence. ASSESSMENT: Three MRI scans were acquired longitudinally (pre-treatment, after 2 cycles of NAST, and after 4 cycles of NAST). Eleven histogram features were extracted from DTI parameter maps of tumors, a peritumoral region (PTR), and FGT in the ipsilateral breast. DTI parameters included apparent diffusion coefficients and relative diffusion anisotropies. pCR status was determined at surgery. STATISTICAL TESTS: Longitudinal changes of DTI features were tested for discrimination of pCR using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC). A P value <0.05 was considered statistically significant. RESULTS: 47% of patients (40/86) had pCR. DTI parameters assessed after 2 and 4 cycles of NAST were significantly different between pCR and non-pCR patients when compared between tumors, PTRs, and FGTs. The median surface/average anisotropy of the PTR, measured after 2 and 4 cycles of NAST, increased in pCR patients and decreased in non-pCR patients (AUC: 0.78; 0.027 ± 0.043 vs. -0.017 ± 0.042 mm2 /s). DATA CONCLUSION: Quantitative DTI features from breast tumors and the peritumoral tissue may be useful for predicting the response to NAST in TNBC. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Predicting pathological complete response to neoadjuvant systemic therapy for triple-negative breast cancers using deep learning on multiparametric MRIs.

We trained and validated a deep learning model that can predict the treatment response to neoadjuvant systemic therapy (NAST) for patients with triple negative breast cancer (TNBC). Dynamic contrast enhanced (DCE) MRI and diffusion-weighted imaging (DWI) of the pre-treatment (baseline) and after four cycles (C4) of doxorubicin/cyclophosphamide treatment were used as inputs to the model for prediction of pathologic complete response (pCR). Based on the standard pCR definition that includes disease status in either breast or axilla, the model achieved areas under the receiver operating characteristic curves (AUCs) of 0.96 ± 0.05, 0.78 ± 0.09, 0.88 ± 0.02, and 0.76 ± 0.03, for the training, validation, testing, and prospective testing groups, respectively. For the pCR status of breast only, the retrained model achieved prediction AUCs of 0.97 ± 0.04, 0.82 ± 0.10, 0.86 ± 0.03, and 0.83 ± 0.02, for the training, validation, testing, and prospective testing groups, respectively. Thus, the developed deep learning model is highly promising for predicting the treatment response to NAST of TNBC.Clinical Relevance- Deep learning based on serial and multiparametric MRIs can potentially distinguish TNBC patients with pCR from non-pCR at the early stage of neoadjuvant systemic therapy, potentially enabling more personalized treatment of TNBC patients.

Triple-Negative Breast Cancer: Histopathologic Features, Genomics, and Treatment.

Triple-negative breast cancer (TNBC) is a heterogeneous and aggressive group of tumors that are defined by the absence of estrogen and progesterone receptors and lack of ERBB2 (formerly HER2 or HER2/neu) overexpression. TNBC accounts for 8%-13% of breast cancers. In addition, it accounts for a higher proportion of breast cancers in younger women compared with those in older women, and it disproportionately affects non-Hispanic Black women. TNBC has high metastatic potential, and the risk of recurrence is highest during the 5 years after it is diagnosed. TNBC exhibits benign morphologic imaging features more frequently than do other breast cancer subtypes. Mammography can be suboptimal for early detection of TNBC owing to factors that include the fast growth of this cancer, increased mammographic density in young women, and lack of the typical features of malignancy at imaging. US is superior to mammography for TNBC detection, but benign-appearing features can lead to misdiagnosis. Breast MRI is the most sensitive modality for TNBC detection. Most cases of TNBC are treated with neoadjuvant chemotherapy, followed by surgery and radiation. MRI is the modality of choice for evaluating the response to neoadjuvant chemotherapy. Survival rates for individuals with TNBC are lower than those for persons with hormone receptor-positive and human epidermal growth factor receptor 2-positive cancers. The 5-year survival rates for patients with localized, regional, and distant disease at diagnosis are 91.3%, 65.8%, and 12.0%, respectively. The early success of immunotherapy has raised hope regarding the development of personalized strategies to treat TNBC. Imaging and tumor biomarkers are likely to play a crucial role in the prediction of TNBC treatment response and TNBC patient survival in the future. ©RSNA, 2023 Quiz questions for this article are available in the supplemental material.

Identifying and Reducing Barriers to Breast Imaging.

Purpose of Review: The purpose of this review is to discuss disparities in breast health care access and outcomes related to race, gender, cultural diversity, sexual orientation, socioeconomic status, geographic location, and disability. The authors recognize the complexity of eliminating inequalities in health care but are optimistic that all patients will one day have equal access to care through dialogue, acknowledgment, recognition, and action. Recent Findings: After lung cancer, breast cancer is the second leading cause of death among American women. Mammography as a preventative screening tool has resulted in significant reductions in breast cancer mortality. Despite existing breast cancer recommendations, it has been projected that 43,250 women will die from breast cancer in 2022. Summary: Disparities in healthcare outcomes exist for many reasons including inequalities based on race, gender, cultural diversity, religion, sexual orientation, and socioeconomic status. Disparities, no matter how large or complex, are not insurmountable.

Prediction of pathologic complete response to neoadjuvant systemic therapy in triple negative breast cancer using deep learning on multiparametric MRI.

Triple-negative breast cancer (TNBC) is an aggressive subtype of breast cancer. Neoadjuvant systemic therapy (NAST) followed by surgery are currently standard of care for TNBC with 50-60% of patients achieving pathologic complete response (pCR). We investigated ability of deep learning (DL) on dynamic contrast enhanced (DCE) MRI and diffusion weighted imaging acquired early during NAST to predict TNBC patients' pCR status in the breast. During the development phase using the images of 130 TNBC patients, the DL model achieved areas under the receiver operating characteristic curves (AUCs) of 0.97 ± 0.04 and 0.82 ± 0.10 for the training and the validation, respectively. The model achieved an AUC of 0.86 ± 0.03 when evaluated in the independent testing group of 32 patients. In an additional prospective blinded testing group of 48 patients, the model achieved an AUC of 0.83 ± 0.02. These results demonstrated that DL based on multiparametric MRI can potentially differentiate TNBC patients with pCR or non-pCR in the breast early during NAST.

Review of the Sonographic Features of Interpectoral (Rotter) Lymph Nodes in Breast Cancer Staging.

ABSTRACT: This article reviews the ultrasound evaluation and staging of breast cancer with respect to the involvement of interpectoral (Rotter) lymph nodes. The primary objective is to demonstrate and assess the characteristic sonographic findings of interpectoral (Rotter) lymph nodes to help provide accurate nodal staging information. We aim to provide a comprehensive review and serve as an imaging guide for the identification and evaluation of Rotter lymph nodes. The detection of abnormalities and pathologic features of metastatic axillary nodal disease in the interpectoral region is reviewed, and the impact on clinical management and treatment is discussed. In the radiology literature, there is no comprehensive review of the sonographic appearance and evaluation of Rotter lymph nodes.

Challenging Contrast-Enhanced Mammography-Guided Biopsies: Practical Approach Using Real-Time Multimodality Imaging and a Proposed Procedural Algorithm.

Contrast-enhanced mammography (CEM) is an emerging functional breast imaging technique that entails the acquisition of dual-energy digital mammographic images after IV administration of iodine-based contrast material. CEM-guided biopsy technology was introduced in 2019 and approved by the U.S. FDA in 2020. This technology's availability enables direct sampling of suspicious enhancement seen only on or predominantly on recombined CEM images and addresses a major obstacle to the clinical implementation of CEM technology. The literature describing clinical indications and procedural techniques of CEM-guided biopsy is scarce. This article describes our initial experience in performing challenging CEM-guided biopsies and proposes a step-by-step procedural algorithm designed to proactively address anticipated technical difficulties and thereby increase the likelihood of achieving successful targeting.

Quantitative Apparent Diffusion Coefficients From Peritumoral Regions as Early Predictors of Response to Neoadjuvant Systemic Therapy in Triple-Negative Breast Cancer.

BACKGROUND: Pathologic complete response (pCR) to neoadjuvant systemic therapy (NAST) in triple-negative breast cancer (TNBC) is a strong predictor of patient survival. Edema in the peritumoral region (PTR) has been reported to be a negative prognostic factor in TNBC. PURPOSE: To determine whether quantitative apparent diffusion coefficient (ADC) features from PTRs on reduced field-of-view (rFOV) diffusion-weighted imaging (DWI) predict the response to NAST in TNBC. STUDY TYPE: Prospective. POPULATION/SUBJECTS: A total of 108 patients with biopsy-proven TNBC who underwent NAST and definitive surgery during 2015-2020. FIELD STRENGTH/SEQUENCE: A 3.0 T/rFOV single-shot diffusion-weighted echo-planar imaging sequence (DWI). ASSESSMENT: Three scans were acquired longitudinally (pretreatment, after two cycles of NAST, and after four cycles of NAST). For each scan, 11 ADC histogram features (minimum, maximum, mean, median, standard deviation, kurtosis, skewness and 10th, 25th, 75th, and 90th percentiles) were extracted from tumors and from PTRs of 5 mm, 10 mm, 15 mm, and 20 mm in thickness with inclusion and exclusion of fat-dominant pixels. STATISTICAL TESTS: ADC features were tested for prediction of pCR, both individually using Mann-Whitney U test and area under the receiver operating characteristic curve (AUC), and in combination in multivariable models with k-fold cross-validation. A P value < 0.05 was considered statistically significant. RESULTS: Fifty-one patients (47%) had pCR. Maximum ADC from PTR, measured after two and four cycles of NAST, was significantly higher in pCR patients (2.8 ± 0.69 vs 3.5 ± 0.94 mm2 /sec). The top-performing feature for prediction of pCR was the maximum ADC from the 5-mm fat-inclusive PTR after cycle 4 of NAST (AUC: 0.74; 95% confidence interval: 0.64, 0.84). Multivariable models of ADC features performed similarly for fat-inclusive and fat-exclusive PTRs, with AUCs ranging from 0.68 to 0.72 for the cycle 2 and cycle 4 scans. DATA CONCLUSION: Quantitative ADC features from PTRs may serve as early predictors of the response to NAST in TNBC. EVIDENCE LEVEL: 1 TECHNICAL EFFICACY: Stage 4.

Clinical Outcomes Using Magnetic Seeds as a Non-wire, Non-radioactive Alternative for Localization of Non-palpable Breast Lesions.

BACKGROUND: Nonpalpable breast lesions require precise preoperative localization to facilitate negative margins with breast-conserving therapy. The traditional use of wires has several challenges including patient discomfort, wire migration, and coordination of schedules between radiology and the operating room. Radioactive seed localization overcomes some of these challenges, but radiation safety requirements have limited adoption of this technology. The authors examined their institutional experience with Magseed as an alternative technology for localization and compared outcomes with those of wire and radioactive seed localization. METHODS: An institutional review board (IRB)-approved retrospective study was performed to evaluate patients who underwent excisional biopsy or segmental mastectomy after wire-guided localization (WGL), radioactive seed localization (RSL), or Magseed localization (ML). The clinical and pathologic factors of the three groups were assessed with a negative margin rate as the primary outcome measure. RESULTS: Of the 1835 patients in the study, 825 underwent WGL, 449 underwent RSL, and 561 underwent ML. For the patients with either multiple lesions or a large lesion that required bracketing, multiple localization devices were placed in 31% of the WGL patients, 28% of the RSL patients, and 23% of the ML patients (p = 0.006). Negative margins were achieved in 91% of the WGL patients, 89% of the RSL patients, and 89% of the ML patients (p = 0.4). CONCLUSION: Localization of non-palpable breast lesions using Magseed is a safe and effective alternative to WGL and RSL that overcomes radiation safety limitations and increases radiology and surgery scheduling efficiency.

The Challenging Image-Guided Preoperative Breast Localization: A Modality-Based Approach.

Breast conservation surgery (BCS) is the standard of care for treating patients with early-stage breast cancer and those with locally advanced breast cancer who achieve an excellent response to neoadjuvant chemotherapy. The radiologist is responsible for accurately localizing nonpalpable lesions to facilitate successful BCS. In this article, we present a practical modality-based guide on approaching challenging pre-operative localizations and incorporate examples of challenging localizations performed under sonographic, mammographic, and MRI guidance, as well as under multiple modalities. Aspects of preprocedure planning, modality selection, patient communication, and procedural and positional techniques are highlighted. Clip and device migration is also considered. Further, an overview is provided of the most widely used wire and nonwire localization devices in the United States. Accurate pre-operative localization of breast lesions is essential to achieve successful surgical outcomes. Certain modality-based techniques can be adopted to successfully complete challenging cases.

Bracketing with Multiple Radioactive Seeds to Achieve Negative Margins in Breast Conservation Surgery: Multiple Seeds in Breast Surgery.

INTRODUCTION: Breast conservation surgery (BCS) is the treatment of choice for unifocal, early-stage breast cancer. The ability to offer BCS to a wider subset of patients, including those with multifocal/multicentric cancer as well as extensive ductal carcinoma in situ, has emerged over time, especially in those undergoing joint oncoplastic reconstruction and those treated with neoadjuvant therapy. However, localization techniques using multiple radioactive seeds for bracketing in this patient subset have not been validated. MATERIALS AND METHODS: A single-institution retrospective review was conducted of all patients with breast cancer who underwent BCS, guided by multiple bracketed iodine I 125 radioactive seeds between January 2014 and April 2017. RESULTS: Bracketing of breast cancer using 2 or more radioactive seeds was performed in 157 breasts in 156 patients. Negative margins were achieved in 124 of 157 (79%) breasts, including 33 cases (21%) that underwent targeted margin reexcision at the time of surgery after intraoperative, multidisciplinary margin assessment. Thirty-three cases (21%) resulted in close or positive margins, of which 11 (7%) and 10 (6.4%) underwent completion mastectomy or repeat lumpectomy, respectively. Twelve patients (7.6%) did not undergo reexcision. En bloc resection was successful in 134 of 157 (85.4%) lumpectomies. Eighty-nine percent of the procedures were coupled with oncoplastic reconstruction. CONCLUSION: Bracketing techniques using multiple radioactive seeds expands the indications for breast conservation therapy in patients who would have traditionally required mastectomy. Intraoperative margin assessment improves surgical and pathologic success. Larger defects created by multifocal resection are optimally managed in concert with oncoplastic reconstruction to minimize asymmetries and aesthetic defects.

Team Science: A Practical Approach to Starting Collaborative Projects.

A collaborative approach to treating patients is well taught in medical training. However, collaboration and team building in clinical and laboratory research may have been given less emphasis. More scientific discoveries are now being made with multidisciplinary teams, requiring a thoughtful approach in order to achieve research goals while mitigating potential conflicts. Specific steps for a successful team science project include building the team, assigning roles and responsibilities, allocating rules, and discussing authorship guidelines. Building a team involves bringing individuals together and developing a common research goal while establishing psychological safety for all members of the team. Clear assignment of roles and responsibilities avoids confusion and allows each member's contributions to be acknowledged. Allocating rules involves discussing how decisions in the team will be made, how data and knowledge sharing will occur, and how potential conflicts will be resolved. Discussing authorship at the start of the project ensures that the entire team knows what work must be completed for authorship to be obtained.

Fluid-filled breast: A unique clinical presentation of invasive micropapillary carcinoma.

Invasive micropapillary carcinoma is a rare variant of invasive ductal carcinoma of the breast. This variant has been described as clinically aggressive due to its high frequency of lymphovascular invasion, axillary nodal metastases, and a greater degree of loco-regional recurrence. Invasive micropapillary carcinoma can have a variety of imaging presentations, typically presenting as an irregular mass. This case report describes a unique presentation of invasive micropapillary carcinoma and illustrates the propensity of invasive micropapillary carcinoma to secrete fluid and have a lack of regional lymphadenopathy. The challenges of the accompanying diagnostic imaging-work up are discussed.

A Deep Learning Approach to Re-create Raw Full-Field Digital Mammograms for Breast Density and Texture Analysis.

PURPOSE: To develop a computational approach to re-create rarely stored for-processing (raw) digital mammograms from routinely stored for-presentation (processed) mammograms. MATERIALS AND METHODS: In this retrospective study, pairs of raw and processed mammograms collected in 884 women (mean age, 57 years ± 10 [standard deviation]; 3713 mammograms) from October 5, 2017, to August 1, 2018, were examined. Mammograms were split 3088 for training and 625 for testing. A deep learning approach based on a U-Net convolutional network and kernel regression was developed to estimate the raw images. The estimated raw images were compared with the originals by four image error and similarity metrics, breast density calculations, and 29 widely used texture features. RESULTS: In the testing dataset, the estimated raw images had small normalized mean absolute error (0.022 ± 0.015), scaled mean absolute error (0.134 ± 0.078) and mean absolute percentage error (0.115 ± 0.059), and a high structural similarity index (0.986 ± 0.007) for the breast portion compared with the original raw images. The estimated and original raw images had a strong correlation in breast density percentage (Pearson r = 0.946) and a strong agreement in breast density grade (Cohen κ = 0.875). The estimated images had satisfactory correlations with the originals in 23 texture features (Pearson r ≥ 0.503 or Spearman ρ ≥ 0.705) and were well complemented by processed images for the other six features. CONCLUSION: This deep learning approach performed well in re-creating raw mammograms with strong agreement in four image evaluation metrics, breast density, and the majority of 29 widely used texture features.Keywords: Mammography, Breast, Supervised Learning, Convolutional Neural Network (CNN), Deep learning algorithms, Machine Learning AlgorithmsSee also the commentary by Chan in this issue.Supplemental material is available for this article.©RSNA, 2021.

Clinicopathological features of and neoadjuvant therapy for human epidermal growth factor receptor 2-positive classic invasive lobular carcinoma.

Human epidermal growth factor receptor 2 (HER2)-positive classic invasive lobular carcinoma (ILC) is a rare entity, and its specific pathological characteristics and clinical behavior are unclear. Therefore, we retrospectively investigated the clinicopathological features of HER2-positive classic ILC and described HER2-targeted neoadjuvant chemotherapy outcome. Fourteen HER2-positive classic ILC cases were identified, their clinicopathological data were collected, and their clinical management was investigated. In general, HER2 positivity is associated with higher grade carcinoma in ductal lesions; however, our 14 cases had typical morphologic features of classic ILC. We did not identify unique morphologic features in HER2-positive classic ILC with the clinicopathological parameters examined, including age, menopausal status, histological grade, and hormone receptor status. Four of six patients who received HER2-targeted neoadjuvant chemotherapy had a pathological complete or partial response. Based on our findings, clinicopathological features of classic ILC may not predict HER2 overexpression or amplification. HER2-targeted neoadjuvant chemotherapy was effective against some HER2-positive classic ILCs. Taken together, these results demonstrate that HER2 immunohistochemistry and fluorescence in situ hybridization should be considered for all ILC patients regardless of subtype.