Multimodality Imaging of Postmastectomy Breast Reconstruction Techniques, Complications, and Tumor Recurrence.

For women undergoing mastectomy, breast reconstruction can be performed by using implants or autologous tissue flaps. Mastectomy options include skin- and nipple-sparing techniques. Implant-based reconstruction can be performed with saline or silicone implants. Various autologous pedicled or free tissue flap reconstruction methods based on different tissue donor sites are available. The aesthetic outcomes of implant- and flap-based reconstructions can be improved with oncoplastic surgery, including autologous fat graft placement and nipple-areolar complex reconstruction. The authors provide an update on recent advances in implant reconstruction techniques and contemporary expanded options for autologous tissue flap reconstruction as it relates to imaging modalities. As breast cancer screening is not routinely performed in this clinical setting, tumor recurrence after mastectomy and reconstruction is often detected by palpation at physical examination. Most local recurrences occur within the skin and subcutaneous tissue. Diagnostic breast imaging continues to have a critical role in confirmation of disease recurrence. Knowledge of the spectrum of benign and abnormal imaging appearances in the reconstructed breast is important for postoperative evaluation of patients, including recognition of early and late postsurgical complications and breast cancer recurrence. The authors provide an overview of multimodality imaging of the postmastectomy reconstructed breast, as well as an update on screening guidelines and recommendations for this unique patient population. ©RSNA, 2024 Test Your Knowledge questions for this article are available in the supplemental material.

Breast lymphedema following breast-conserving treatment for breast cancer: current status and future directions.

PURPOSE: To examine the current evidence on breast lymphedema (BL) diagnosis and treatment after breast-conserving surgery, identify gaps in the literature, and propose future research directions. METHODS: A comprehensive literature review was conducted using Ovid, PubMed, and Cochrane, including studies published between 2000 and 2023. References were reviewed manually for eligible studies. Inclusion criteria were as follows: patients who underwent breast conserving treatment (surgery ± radiation) for breast cancer, goals of the paper included analyzing or reviewing BL measurement with ultrasound or tissue dielectric constant, or BL treatment. Twenty-seven manuscripts were included in the review. RESULTS: There is variation in incidence, time course, and risk factors for BL. Risk factors for BL included breast size, primary and axillary surgery extent, radiation, and chemotherapy but require further investigation. Diagnostic methods for BL currently rely on patient report and lack standardized criteria. Tissue dielectric constant (TDC) and ultrasound (US) emerged as promising ambulatory BL assessment tools; however, diagnostic thresholds and validation studies with ICG lymphography are needed to establish clinical utility. The evidence base for treatment of BL is weak, lacking high-quality studies. CONCLUSION: The natural history of BL is not well defined. TDC and US show promise as ambulatory assessment tools for BL; however, further validation with lymphatic imaging is required. BL treatment is not established in the literature. Longitudinal, prospective studies including pre-radiation measurements and validating with lymphatic imaging are required. These data will inform screening, diagnostic criteria, and evidence-based treatment parameters for patients with BL after breast-conserving surgery and radiation.

Spectrum of Mucin-containing Lesions of the Breast: Multimodality Imaging Review with Pathologic Correlation.

Mucin-containing lesions of the breast encompass a wide range of benign and malignant processes. The spectrum of histologic findings includes incidental mucus-filled benign cysts or ducts, mucocele-like lesions (MLLs), mucin-producing ductal carcinoma in situ, and invasive mucinous carcinoma. MLL is characterized by the presence of mucin-containing cysts that are typically associated with extravasated stromal mucin. MLL is often benign but can be associated with epithelial atypia or malignancy. Mucinous carcinoma represents the malignant end of the spectrum of mucinous lesions of the breast. Evidence-based literature supports a conservative approach for benign MLLs without associated atypia or malignancy, reserving excision for those lesions exhibiting such pathologic features. The most common imaging finding for MLL is microcalcifications at mammography. No specific imaging feature is predictive of malignant outcome at surgical excision. Invasive mucinous carcinoma is a heterogeneous breast tumor subtype, as defined according to the World Health Organization criteria. Mucinous carcinomas are categorized into pure (>90% mucinous component) or mixed (10%-90% mucinous component) subtypes. Pure mucinous carcinomas are generally associated with excellent prognosis and survival, with a few exceptions. Mixed mucinous carcinomas do not have the same favorable prognosis and instead behave similarly to invasive breast carcinomas of no special type. Characteristic diagnostic imaging features can be identified for mucinous carcinoma based on its mucinous and nonmucinous contents. ©RSNA, 2023 Online supplemental material is available for this article. Quiz questions for this article are available through the Online Learning Center.

Artificial Intelligence for Breast US.

US is a widely available, commonly used, and indispensable imaging modality for breast evaluation. It is often the primary imaging modality for the detection and diagnosis of breast cancer in low-resource settings. In addition, it is frequently employed as a supplemental screening tool via either whole breast handheld US or automated breast US among women with dense breasts. In recent years, a variety of artificial intelligence systems have been developed to assist radiologists with the detection and diagnosis of breast lesions on US. This article reviews the background and evidence supporting the use of artificial intelligence tools for breast US, describes implementation strategies and impact on clinical workflow, and discusses potential emerging roles and future directions.

Stacked dilated convolutions and asymmetric architecture for U-Net-based medical image segmentation.

Deep learning has been widely utilized for medical image segmentation. The most commonly used U-Net and its variants often share two common characteristics but lack solid evidence for the effectiveness. First, each block (i.e., consecutive convolutions of feature maps of the same resolution) outputs feature maps from the last convolution, limiting the variety of the receptive fields. Second, the network has a symmetric structure where the encoder and the decoder paths have similar numbers of channels. We explored two novel revisions: a stacked dilated operation that outputs feature maps from multi-scale receptive fields to replace the consecutive convolutions; an asymmetric architecture with fewer channels in the decoder path. Two novel models were developed: U-Net using the stacked dilated operation (SDU-Net) and asymmetric SDU-Net (ASDU-Net). We used both publicly available and private datasets to assess the efficacy of the proposed models. Extensive experiments confirmed SDU-Net outperformed or achieved performance similar to the state-of-the-art while using fewer parameters (40% of U-Net). ASDU-Net further reduced the model parameters to 20% of U-Net with performance comparable to SDU-Net. In conclusion, the stacked dilated operation and the asymmetric structure are promising for improving the performance of U-Net and its variants.

Power Spectrum Analysis of Breast Parenchyma with Digital Breast Tomosynthesis Images in a Longitudinal Screening Cohort from Two Vendors.

RATIONALE AND OBJECTIVES: To quantitatively compare breast parenchymal texture between two Digital Breast Tomosynthesis (DBT) vendors using images from the same patients. MATERIALS AND METHODS: This retrospective study included consecutive patients who had normal screening DBT exams performed in January 2018 from GE and normal screening DBT exams in adjacent years from Hologic. Power spectrum analysis was performed within the breast tissue region. The slope of a linear function between log-frequency and log-power, ß, was derived as a quantitative measure of breast texture and compared within and across vendors along with secondary parameters (laterality, view, year, image format, and breast density) with correlation tests and t-tests. RESULTS: A total of 24,339 DBT slices or synthetic 2D images from 85 exams in 25 women were analyzed. Strong power-law behavior was verified from all images. Values of ß d did not differ significantly for laterality, view, or year. Significant differences of ß were observed across vendors for DBT images (Hologic: 3.4±0.2 vs GE: 3.1±0.2, 95% CI on difference: 0.27 to 0.30) and synthetic 2D images (Hologic: 2.7±0.3 vs GE: 3.0±0.2, 95% CI on difference: -0.36 to -0.27), and density groups with each vendor: scattered (GE: 3.0±0.3, Hologic: 3.3±0.3) vs. heterogeneous (GE: 3.2±0.2, Hologic: 3.4±0.1), 95% CI (-0.27, -0.08) and (-0.21, -0.05), respectively. CONCLUSION: There are quantitative differences in the presentation of breast imaging texture between DBT vendors and across breast density categories. Our findings have relevance and importance for development and optimization of AI algorithms related to breast density assessment and cancer detection.

Patient Sociodemographic Characteristics Associated With Saturday Breast Imaging Clinic Utilization.

OBJECTIVE: To determine patient sociodemographic characteristics associated with breast imaging utilization on Saturdays to inform potential initiatives designed to improve access and reduce disparities in breast cancer care. METHODS: This was an IRB-approved retrospective cross-sectional study. All adult women (aged ≥18 years) who received a screening or diagnostic examination at our breast imaging facility from January 1, 2016 to December 31, 2017 were included. Patient characteristics including age, race, primary language, partnership status, insurance status, and primary care physician status were collected using the electronic medical record. Multiple variable logistic regression analyses were performed to evaluate patient characteristics associated with utilization. RESULTS: Of 53 695 patients who underwent a screening examination and 10 363 patients who underwent a diagnostic examination over our study period, 9.6% (5135/53 695) and 2.0% (209/10 363) of patients obtained their respective examination on a Saturday. In our multiple variable logistic regression analyses, racial/ethnic minorities (odds ratio [OR], 1.5; 95% confidence interval [CI]: 1.4-1.6; P < 0.01) and women who speak English as a second language (OR, 1.1; 95% CI: 1.0-1.3; P = 0.03) were more likely to obtain their screening mammogram on Saturday than their respective counterparts. CONCLUSION: Racial/ethnic minorities and women who speak English as a second language were more likely to obtain their screening mammogram on Saturdays than their respective counterparts. Initiatives to extend availability of breast imaging exams outside of standard business hours increases access for historically underserved groups, which can be used as a tool to reduce breast cancer-related disparities in care.

Breast Cancer Screening in Women With Dense Breasts: Current Status and Future Directions for Appropriate Risk Stratification and Imaging Utilization.

Breast density continues to be a prevailing topic in the field of breast imaging, with continued complexities contributing to overall confusion and controversy among patients and the medical community. In this article, we explore the current status of breast cancer screening in women with dense breasts including breast density legislation. Risk-based approaches to supplemental screening may be more financially cost-effective. While all advanced imaging modalities detect additional primarily invasive, node-negative cancers, the degree to which this occurs can vary by density category. Future directions include expanding the use of density-inclusive risk models with appropriate risk stratification and imaging utilization. Further research is needed, however, to better understand how to optimize population-based screening programs with knowledge of patients' individualized risk, including breast density assessment, to improve the benefit-to-harm ratio of breast cancer screening.

Preoperative Breast MRI for Newly Diagnosed Ductal Carcinoma in Situ: Imaging Features and Performance in a Multicenter Setting (ECOG-ACRIN E4112 Trial).

Background There are limited data from clinical trials describing preoperative MRI features and performance in the evaluation of mammographically detected ductal carcinoma in situ (DCIS). Purpose To report qualitative MRI features of DCIS, MRI performance in the identification of additional disease, and associations of imaging features with pathologic, genomic, and surgical outcomes from the Eastern Cooperative Oncology Group-American College of Radiology Imaging Network (ECOG-ACRIN) E4112 trial. Materials and Methods Secondary analyses of a multicenter prospective clinical trial from the ECOG-ACRIN Cancer Research Group included women with DCIS diagnosed with conventional imaging techniques (mammography and US), confirmed via core-needle biopsy (CNB), and enrolled between March 2015 and April 2016 who were candidates for wide local excision (WLE) based on conventional imaging and clinical examination results. DCIS MRI features and pathologic features from CNB and excision were recorded. Each woman without invasive upgrade of the index DCIS at WLE received a 12-gene DCIS score. MRI performance metrics were calculated. Associations of imaging features with invasive upgrade, dichotomized DCIS score (<39 vs ≥39), and single WLE success were estimated in uni- and multivariable analyses. Results Among 339 women (median age, 60 years; interquartile range, 51-66 years), most DCIS cases showed nonmass enhancement (NME) (195 of 339 [58%]) on MRI scans with larger median size than on mammograms (19 mm vs 12 mm; P < .001). Positive predictive value of MRI-prompted CNBs was 32% (21 of 66) (95% CI: 22, 44), yielding an additional cancer detection rate of 6.2% (21 of 339) (95% CI: 4.1, 9.3). MRI false-positive rate was 14.2% (45 of 318) (95% CI: 10.7, 18.4). No imaging features were associated with invasive upgrade or DCIS score (P = .05 to P = .95). Smaller size and focal NME distribution at MRI were linked to single WLE success (P < .001). Conclusion Preoperative MRI depicted ductal carcinoma in situ (DCIS) diagnosed with conventional imaging most commonly as nonmass enhancement, with larger median span than mammography, and additional cancer detection rate of 6.2%. MRI features of this subset of DCIS did not enable prediction of pathologic or genomic outcomes. Clinical trial registration no. NCT02352883 © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Kuhl in this issue. An earlier incorrect version of this article appeared online. This article was corrected on August 4, 2021.

Shear-Wave Elastography of the Breast: Impact of Technical Image Quality Parameters on Diagnostic Accuracy.

OBJECTIVE. The purpose of this study is to determine the impact of shear-wave elastography (SWE) image quality parameters on the diagnostic performance of elasticity measurements in classifying breast lesions. MATERIALS AND METHODS. This retrospective study included 281 breast lesions that underwent SWE and ultrasound-guided biopsy performed between October 1, 2017, and August 31, 2018. Three readers who were blinded to pathologic outcomes independently scored the image quality of each SWE image (with low quality denoted by a score of 0 and high quality indicated by a score of 1) on the basis of five parameters: B-mode visualization of the lesion on a dual-panel display, SWE red pattern (denoting high stiffness) in the near field of the FOV, appearance of the surrounding tissue, FOV placement, and ROI placement for the maximum (Emax), minimum (Emin), mean (Emean), and SD (ESD) of Young modulus elasticity measurements. Using ROC analysis, we compared the performance of Emax, Emean, and ESD in diagnosing malignancy on low- and high-quality images on the basis of consensus (i.e., majority) scores for each individual quality parameter as well as two models combining a few of the quality parameters. RESULTS. Three quality parameters (B-mode visualization of the lesion, presence of a near-field red pattern, and the appearance of the surrounding tissue) showed moderate-to-substantial interobserver agreement. SWE images were considered high quality (n = 167) if both B-mode visualization and near-field red pattern received a consensus score of 1, and they were considered low quality (n = 114) if either parameter received a consensus score of 0. High-quality images had a statistically higher AUC value than low-quality images when Emax (p < .001), Emean (p = .002), and ESD (p < .001) were used as classifiers of malignancy. CONCLUSION. Quality parameters can support radiologists who are performing and interpreting breast SWE images. These quality parameters have the potential to improve the accuracy of SWE in differentiating malignant from benign breast lesions.

Opportunities for Radiology Trainee Education Amid the COVID-19 Pandemic: Lessons From an Academic Breast Imaging Program.

The COVID-19 pandemic required restructuring of Radiology trainee education across US institutions. While reduced clinical imaging volume and mandates to maintain physical distancing presented new challenges to traditional medical education during this period, new opportunities developed to support our division in providing high-quality training for residents and fellows. The Accreditation Council for Graduate Medical Education (ACGME) Core Competencies for Diagnostic Radiology helped guide division leadership in restructuring and reframing breast imaging education during this time of drastic change and persistent uncertainty. Here, we reflect on the educational challenges and opportunities faced by our academic breast imaging division during the height of the COVID-19 pandemic across each of the ACGME Core Competencies. We also discuss how systems and processes developed out of necessity during the first peak of the pandemic may continue to support radiology training during phased reopening and beyond.

Imaging Evaluation of the Axilla-A National Survey of Clinical Practice Among Radiologists.

OBJECTIVE: To assess awareness and implementation of the American College of Surgeons Oncology Group Z0011 trial findings, approaches to axillary nodal imaging, and to identify differences in practice based on respondent characteristics. METHODS: An online survey was distributed to members of the Society of Breast Imaging. Questions regarded demographics, evaluation approaches, and impact of the Z0011 trial. Poisson regression with robust standard errors to regression was used to generate multivariable-adjusted relative risks and 95% confidence intervals (CIs) for associations. RESULTS: The response rate was 21.7% (430/2007). The majority (295/430, 68.6%) reported always performing axillary US in patients with a BI-RADS 4B, 4C, or 5 breast mass. Most respondents (299/430, 69.5%) were familiar with the findings of the Z0011 trial. Radiologists in academic practice were 0.67 (95% CI: 0.54-0.83) times less likely than private practice radiologists to perform axillary US in all masses and 1.31 (95% CI: 1.13-1.52) times more likely to be very familiar with the trial. Frequency of axillary US showed no association with time spent in breast imaging, years in practice, or presence of dedicated breast surgeons. Increased time in breast imaging and presence of dedicated breast surgeons was strongly associated with familiarity with the trial. No association was observed with years in practice. Most respondents (291/430, 67.7%) made little or no change to their practice based on trial findings. CONCLUSION: There is wide variability in approaches to axillary nodal evaluation, demonstrating a need for improved education and guidelines for axillary imaging in breast cancer patients.

Rare case of invasive lobular carcinoma in a male.

Invasive lobular carcinoma (ILC) in the male breast is a rare subtype of a rare disease in men, accounting for approximately 1%-2% of all male breast cancers [1,2]. Only a few cases have been reported in the literature. The pathophysiology is uncommon due to a paucity of lobular development seen in men. We present a rare case of ILC in the male breast, highlighting imaging, pathology findings, and clinical management.

Kinetic Analysis of Lesions Identified on a Rapid Abridged Multiphase (RAMP) Breast MRI Protocol.

RATIONALE AND OBJECTIVES: We implemented a rapid abridged multiphase (RAMP) breast magnetic resonance imaging (MRI) protocol to reduce scan time and increase workflow efficiency. In this study, we compared delayed-phase kinetic analyses of benign and malignant lesions on the RAMP protocol versus a full dynamic contrast-enhanced (DCE) MRI protocol. MATERIALS AND METHODS: Consecutive breast MRI examinations obtained from October 2015 to August 2016 with tissue diagnoses of suspicious MRI lesions were identified. RAMP MRI included one precontrast and two postcontrast phases. Full DCE MRI included one precontrast and at least three postcontrast phases. Lesion kinetic analyses including mean delayed-phase volume percentage of washout, predominant curve type, and worst curve type were assessed. Kinetic analyses assessed on RAMP and DCE MRI protocols were compared using Wilcoxon rank-sum test and Chi-Square test. Receiver operating characteristic analysis was performed to discriminate benign and malignant lesions based on delayed-phase parameters. RESULTS: The study included 177 consecutive breast lesions (50 benign, 127 malignant) in 162 women. RAMP MRI (23 benign, 61 malignant) and DCE MRI examinations (27 benign, 66 malignant) demonstrated 8.4% vs 9.3% washout (p = 0.36) for benign lesions and 18.5% vs 17% washout (p = 0.66) for malignancies, respectively. There was no difference in the predominant and worst curve types for malignant and benign lesions or in area under the receiver operating characteristic curves for delayed-phased parameters between the two protocols (p > 0.05). CONCLUSION: Lesion kinetic analyses from the RAMP MRI protocol can achieve the same discriminatory ability as the full DCE protocol. By reducing scan time, the RAMP MRI protocol improves patient comfort and enhances workflow efficiency and can be easily implemented in any clinical setting.

Data Engineering for Machine Learning in Women's Imaging and Beyond.

OBJECTIVE. Data engineering is the foundation of effective machine learning model development and research. The accuracy and clinical utility of machine learning models fundamentally depend on the quality of the data used for model development. This article aims to provide radiologists and radiology researchers with an understanding of the core elements of data preparation for machine learning research. We cover key concepts from an engineering perspective, including databases, data integrity, and characteristics of data suitable for machine learning projects, and from a clinical perspective, including the HIPAA, patient consent, avoidance of bias, and ethical concerns related to the potential to magnify health disparities. The focus of this article is women's imaging; nonetheless, the principles described apply to all domains of medical imaging. CONCLUSION. Machine learning research is inherently interdisciplinary: effective collaboration is critical for success. In medical imaging, radiologists possess knowledge essential for data engineers to develop useful datasets for machine learning model development.

Value of Mammography for Women 30-39 Years Old Presenting With Breast Symptoms.

OBJECTIVE: The purpose of this study was to determine the performance and added value of bilateral mammography in identifying cancers distant from sites of presenting breast symptoms in women 30-39 years old. MATERIALS AND METHODS: A search identified consecutively registered women 30-39 years old who underwent mammography and ultrasound to evaluate focal breast symptoms between June 2006 and August 2016. Outcomes were determined by imaging and pathologic analysis through linkage with a tumor registry. Medical records were reviewed to determine the presence of breast cancer risk factors. Lifetime breast cancer risk was calculated with the International Breast Cancer Intervention Study model. RESULTS: The study included 4426 diagnostic examinations of 3997 women 30-39 years old. Sixty-eight breast cancers were diagnosed (cancer detection rate, 15.4 per 1000 examinations). Sixty examinations led to biopsy of a finding distant from the presenting symptom site, yielding nine incidental malignancies (positive predictive value, 15.0%; incidental cancer detection rate, 2.0 per 1000 examinations [9/4426]). Among the other 59 cancers diagnosed in the symptomatic area, bilateral mammography depicted multicentric or contra-lateral disease in seven (11.9%). Average lifetime risk of breast cancer among the 68 women with cancer was significantly higher than that among age-matched control subjects (22.8% vs 13.1%, p < 0.001); 45 of these 68 women (66.2%) had identifiable risk factors. Lifetime risk among the nine women with incidental cancers was higher than that of age-matched control subjects, although without statistical significance (24.9% vs 13.2%, p = 0.07). CONCLUSION: Bilateral mammographic evaluation of women 30-39 years old presenting with breast symptoms yielded an additional 2.0 incidental cancers per 1000 examinations. The low added cancer yield may support the judicious rather than routine use of mammography in this patient cohort.