Optimizing biopsy training experience for trainees and faculty: Utilizing 5S methodology with a focus on safety.

This manuscript explores the application of the 5S methodology in optimizing workplace safety and efficiency within the context of biopsy training equipment. Drawing from a Quality Improvement Report presented at the 2023 RSNA annual meeting, our manuscript focuses on implementing 5S principles with a dedicated emphasis on safety (the 6th S). We demonstrate how the systematic application of 5S principles can revolutionize the functionality of biopsy training equipment, mitigate safety risks, and enhance overall workplace productivity. This manuscript offers valuable insights and practical strategies for improving healthcare training environments, with broader implications for quality improvement initiatives in the healthcare sector.

Distance of Biopsy-Confirmed High-Risk Breast Lesion from Concurrently Identified Breast Malignancy Associated with Risk of Carcinoma at the High-Risk Lesion Site.

High-risk breast lesions including incidental intraductal papilloma without atypia (IPA), lobular hyperplasia (LCIS or ALH), flat epithelial atypia (FEA) and complex sclerosing lesion (CSL) are not routinely excised due to low upgrade rates to carcinoma. We aim to identify features of these lesions predictive of upgrade when identified concurrently with invasive disease. Methods: A single-center retrospective cohort study was performed for patients who underwent multi-site lumpectomies with invasive disease at one site and a high-risk lesion at another site between 2006 and 2021. A multinomial logistic regression was performed. Results: Sixty-five patients met the inclusion criteria. Four patients (6.2%) had an upgrade to in situ disease (DCIS) and one (1.5%) to invasive carcinoma. Three upgraded high-risk lesions were ipsilateral to the concurrent carcinoma and two were contralateral. In the multivariate model, a high-risk lesion within 5 cm of an ipsilateral malignancy was associated with increased risk of upgrade. The 3.8% upgrade rate for high-risk lesions located greater than 5 cm from ipsilateral malignancy or in the contralateral breast suggests that omission of excisional biopsy may be considered. Excisional biopsy of lesions within 5 cm of ipsilateral malignancy is recommended given the 25% upgrade risk in our series.

Restriction spectrum imaging with elastic image registration for automated evaluation of response to neoadjuvant therapy in breast cancer.

Purpose: Dynamic contrast-enhanced MRI (DCE) and apparent diffusion coefficient (ADC) are currently used to evaluate treatment response of breast cancer. The purpose of the current study was to evaluate the three-component Restriction Spectrum Imaging model (RSI3C), a recent diffusion-weighted MRI (DWI)-based tumor classification method, combined with elastic image registration, to automatically monitor breast tumor size throughout neoadjuvant therapy. Experimental design: Breast cancer patients (n=27) underwent multi-parametric 3T MRI at four time points during treatment. Elastically-registered DWI images were used to generate an automatic RSI3C response classifier, assessed against manual DCE tumor size measurements and mean ADC values. Predictions of therapy response during treatment and residual tumor post-treatment were assessed using non-pathological complete response (non-pCR) as an endpoint. Results: Ten patients experienced pCR. Prediction of non-pCR using ROC AUC (95% CI) for change in measured tumor size from pre-treatment time point to early-treatment time point was 0.65 (0.38-0.92) for the RSI3C classifier, 0.64 (0.36-0.91) for DCE, and 0.45 (0.16-0.75) for change in mean ADC. Sensitivity for detection of residual disease post-treatment was 0.71 (0.44-0.90) for the RSI3C classifier, compared to 0.88 (0.64-0.99) for DCE and 0.76 (0.50-0.93) for ADC. Specificity was 0.90 (0.56-1.00) for the RSI3C classifier, 0.70 (0.35-0.93) for DCE, and 0.50 (0.19-0.81) for ADC. Conclusion: The automatic RSI3C classifier with elastic image registration suggested prediction of response to treatment after only three weeks, and showed performance comparable to DCE for assessment of residual tumor post-therapy. RSI3C may guide clinical decision-making and enable tailored treatment regimens and cost-efficient evaluation of neoadjuvant therapy of breast cancer.

Cancer in pregnancy: breast cancer.

Breast cancer is the most common malignancy in women, and for women under 40, it is the leading cause of cancer-related deaths. A specific type of breast cancer is pregnancy-associated breast cancer, which is diagnosed during pregnancy, the first-year postpartum, or during lactation. Pregnancy-associated breast cancer is seen in 3/1000 pregnancies and is increasing in incidence as women delay pregnancy. This type of breast cancer is more aggressive, and not infrequently, there is a delay in diagnosis attributed to physiologic changes that occur during pregnancy and a lack of awareness among physicians. In this review, we discuss the demographics of pregnancy-associated breast cancer, provide differential considerations, and illustrate the multimodality imaging features to bring attention to the radiologist about this aggressive form of breast cancer.

Localizing Positive Axillary Lymph Nodes in Breast Cancer Patients Post Neoadjuvant Therapy.

INTRODUCTION: Multiple trials demonstrated the feasibility of sentinel lymph node biopsy (SLNB) after neoadjuvant chemotherapy. Those trials reported > 10% false-negative rate; however, a subset analysis of the Z1071 trial demonstrated that removing the clipped positive lymph node (LN) during SLNB reduces the false-negative rate to 6.8% post neoadjuvant chemotherapy. This study examines the factors that might contribute to the ability to identify the clipped nodes post neoadjuvant therapy (NAT). MATERIALS AND METHODS: Breast cancer patients with biopsy-proven metastatic axillary LN who underwent NAT, converted to N0, had preoperative localization, and then SLNB between 2018 and 2020 at a single institution were identified. A retrospective chart review was performed. Demographic and preoperative variables were compared between localization and nonlocalization groups. RESULTS: Eighty patients who met inclusion criteria were included. A total of 39 patients were localized after NAT completion (49%). Only half of the patients with ultrasound-detectable marker clips were able to be localized. Minimal LN abnormality was seen in imaging after NAT completion in 39 patients and is significantly associated with localization; 26 (67%) were localized (Odds Ratio 4.31, P = 0.002, 95% Confidence Interval 1.69-10.98). CONCLUSIONS: Our study suggests that radiologically abnormal LNs on preoperative imaging after NAT completion are more likely to be localized. Nodes that ultimately normalize by imaging criteria remain a significant challenge to localize, and thus localization before starting NAT is suggested. A better technology is needed for LN localization after prolonged NAT for best accuracy and avoids repeated procedures.

Tri-Compartmental Restriction Spectrum Imaging Breast Model Distinguishes Malignant Lesions from Benign Lesions and Healthy Tissue on Diffusion-Weighted Imaging.

Diffusion-weighted MRI (DW-MRI) offers a potential adjunct to dynamic contrast-enhanced MRI to discriminate benign from malignant breast lesions by yielding quantitative information about tissue microstructure. Multi-component modeling of the DW-MRI signal over an extended b-value range (up to 3000 s/mm2) theoretically isolates the slowly diffusing (restricted) water component in tissues. Previously, a three-component restriction spectrum imaging (RSI) model demonstrated the ability to distinguish malignant lesions from healthy breast tissue. We further evaluated the utility of this three-component model to differentiate malignant from benign lesions and healthy tissue in 12 patients with known malignancy and synchronous pathology-proven benign lesions. The signal contributions from three distinct diffusion compartments were measured to generate parametric maps corresponding to diffusivity on a voxel-wise basis. The three-component model discriminated malignant from benign and healthy tissue, particularly using the restricted diffusion C1 compartment and product of the restricted and intermediate diffusion compartments (C1 and C2). However, benign lesions and healthy tissue did not significantly differ in diffusion characteristics. Quantitative discrimination of these three tissue types (malignant, benign, and healthy) in non-pre-defined lesions may enhance the clinical utility of DW-MRI in reducing excessive biopsies and aiding in surveillance and surgical evaluation without repeated exposure to gadolinium contrast.

3D Harmonic and Subharmonic Imaging for Characterizing Breast Lesions: A Multi-Center Clinical Trial.

OBJECTIVE: Breast cancer is the most frequent type of cancer among women. This multi-center study assessed the ability of 3D contrast-enhanced ultrasound to characterize suspicious breast lesions using clinical assessments and quantitative parameters. METHODS: Women with suspicious breast lesions scheduled for biopsy were enrolled in this prospective, study. Following 2D grayscale ultrasound and power Doppler imaging (PDI), a contrast agent (Definity; Lantheus) was administrated. Contrast-enhanced 3D harmonic imaging (HI; transmitting/receiving at 5.0/10.0 MHz), as well as 3D subharmonic imaging (SHI; transmitting/receiving at 5.8/2.9 MHz), were performed using a modified Logiq 9 scanner (GE Healthcare). Five radiologists independently scored the imaging modes (including standard-of-care imaging) using a 7-point BIRADS scale as well as lesion vascularity and diagnostic confidence. Parametric volumes were constructed from time-intensity curves for vascular heterogeneity, perfusion, and area under the curve. Diagnostic accuracy was determined relative to pathology using receiver operating characteristic (ROC) and reverse, step-wise logistical regression analyses. The κ-statistic was calculated for inter-reader agreement. RESULTS: Data were successfully acquired in 219 cases and biopsies indicated 164 (75%) benign and 55 (25%) malignant lesions. SHI depicted more anastomoses and vascularity than HI (P < .021), but there were no differences by pathology (P > .27). Ultrasound achieved accuracies of 82 to 85%, which was significantly better than standard-of-care imaging (72%; P < .03). SHI increased diagnostic confidence by 3 to 6% (P < .05), but inter-reader agreements were medium to low (κ < 0.52). The best regression model achieved 97% accuracy by combining clinical reads and parametric SHI. CONCLUSIONS: Combining quantitative 3D SHI parameters and clinical assessments improves the characterization of suspicious breast lesions.

Characterization of the diffusion signal of breast tissues using multi-exponential models.

PURPOSE: Restriction spectrum imaging (RSI) decomposes the diffusion-weighted MRI signal into separate components of known apparent diffusion coefficients (ADCs). The number of diffusion components and optimal ADCs for RSI are organ-specific and determined empirically. The purpose of this work was to determine the RSI model for breast tissues. METHODS: The diffusion-weighted MRI signal was described using a linear combination of multiple exponential components. A set of ADC values was estimated to fit voxels in cancer and control ROIs. Later, the signal contributions of each diffusion component were estimated using these fixed ADC values. Relative-fitting residuals and Bayesian information criterion were assessed. Contrast-to-noise ratio between cancer and fibroglandular tissue in RSI-derived signal contribution maps was compared to DCE imaging. RESULTS: A total of 74 women with breast cancer were scanned at 3.0 Tesla MRI. The fitting residuals of conventional ADC and Bayesian information criterion suggest that a 3-component model improves the characterization of the diffusion signal over a biexponential model. Estimated ADCs of triexponential model were D1,3 = 0, D2,3 = 1.5 × 10-3 , and D3,3 = 10.8 × 10-3 mm2 /s. The RSI-derived signal contributions of the slower diffusion components were larger in tumors than in fibroglandular tissues. Further, the contrast-to-noise and specificity at 80% sensitivity of DCE and a subset of RSI-derived maps were equivalent. CONCLUSION: Breast diffusion-weighted MRI signal was best described using a triexponential model. Tumor conspicuity in breast RSI model is comparable to that of DCE without the use of exogenous contrast. These data may be used as differential features between healthy and malignant breast tissues.

Breast MRI during Neoadjuvant Chemotherapy: Lack of Background Parenchymal Enhancement Suppression and Inferior Treatment Response.

Background Suppression of background parenchymal enhancement (BPE) is commonly observed after neoadjuvant chemotherapy (NAC) at contrast-enhanced breast MRI. It was hypothesized that nonsuppressed BPE may be associated with inferior response to NAC. Purpose To investigate the relationship between lack of BPE suppression and pathologic response. Materials and Methods A retrospective review was performed for women with menopausal status data who were treated for breast cancer by one of 10 drug arms (standard NAC with or without experimental agents) between May 2010 and November 2016 in the Investigation of Serial Studies to Predict Your Therapeutic Response with Imaging and Molecular Analysis 2, or I-SPY 2 TRIAL (NCT01042379). Patients underwent MRI at four points: before treatment (T0), early treatment (T1), interregimen (T2), and before surgery (T3). BPE was quantitatively measured by using automated fibroglandular tissue segmentation. To test the hypothesis effectively, a subset of examinations with BPE with high-quality segmentation was selected. BPE change from T0 was defined as suppressed or nonsuppressed for each point. The Fisher exact test and the Z tests of proportions with Yates continuity correction were used to examine the relationship between BPE suppression and pathologic complete response (pCR) in hormone receptor (HR)-positive and HR-negative cohorts. Results A total of 3528 MRI scans from 882 patients (mean age, 48 years ± 10 [standard deviation]) were reviewed and the subset of patients with high-quality BPE segmentation was determined (T1, 433 patients; T2, 396 patients; T3, 380 patients). In the HR-positive cohort, an association between lack of BPE suppression and lower pCR rate was detected at T2 (nonsuppressed vs suppressed, 11.8% [six of 51] vs 28.9% [50 of 173]; difference, 17.1% [95% CI: 4.7, 29.5]; P = .02) and T3 (nonsuppressed vs suppressed, 5.3% [two of 38] vs 27.4% [48 of 175]; difference, 22.2% [95% CI: 10.9, 33.5]; P = .003). In the HR-negative cohort, patients with nonsuppressed BPE had lower estimated pCR rate at all points, but the P values for the association were all greater than .05. Conclusions In hormone receptor-positive breast cancer, lack of background parenchymal enhancement suppression may indicate inferior treatment response. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Philpotts in this issue.

Impact of the COVID-19 Pandemic on Breast Imaging Education.

OBJECTIVE: To determine the impact of the COVID-19 pandemic on breast imaging education. METHODS: A 22-item survey addressing four themes during the early pandemic (time on service, structured education, clinical training, future plans) was emailed to Society of Breast Imaging members and members-in-training in July 2020. Responses were compared using McNemar's and Mann-Whitney U tests; a general linear model was used for multivariate analysis. RESULTS: Of 136 responses (136/2824, 4.8%), 96 U.S. responses from radiologists with trainees, residents, and fellows were included. Clinical exposure declined during the early pandemic, with almost no medical students on service (66/67, 99%) and fewer clinical days for residents (78/89, 88%) and fellows (48/68, 71%). Conferences shifted to remote live format (57/78, 73%), with some canceled (15/78, 19%). Compared to pre-pandemic, resident diagnostic (75/78, 96% vs 26/78, 33%) (P < 0.001) and procedural (73/78, 94% vs 21/78, 27%) (P < 0.001) participation fell, as did fellow diagnostic (60/61, 98% vs 47/61, 77%) (P = 0.001) and procedural (60/61, 98% vs 43/61, 70%) (P < 0.001) participation. Most thought that the pandemic negatively influenced resident and fellow screening (64/77, 83% and 43/60, 72%, respectively), diagnostic (66/77, 86% and 37/60, 62%), and procedural (71/77, 92% and 37/61, 61%) education. However, a majority thought that decreased time on service (36/67, 54%) and patient contact (46/79, 58%) would not change residents' pursuit of a breast imaging fellowship. CONCLUSION: The pandemic has had a largely negative impact on breast imaging education, with reduction in exposure to all aspects of breast imaging. However, this may not affect career decisions.

Current Status and Future of BI-RADS in Multimodality Imaging, From the AJR Special Series on Radiology Reporting and Data Systems.

BI-RADS is a communication and data tracking system that has evolved since its inception as a brief mammography lexicon and reporting guide into a robust structured reporting platform and comprehensive quality assurance tool for mammography, ultrasound, and MRI. Consistent and appropriate use of the BI-RADS lexicon terminology and assessment categories effectively communicates findings, estimates the risk of malignancy, and provides management recommendations to patients and referring clinicians. The impact of BI-RADS currently extends internationally through six language translations. A condensed version has been proposed to facilitate a phased implementation of BI-RADS in resource-constrained regions. The primary advance of the 5th edition of BI-RADS is harmonization of the lexicon terms across mammography, ultrasound, and MRI. Harmonization has also been achieved across these modalities for the reporting structure, assessment categories, management recommendations, and data tracking system. Areas for improvement relate to certain common findings that lack lexicon descriptors and a need for further clarification of proper use of category 3. BI-RADS is anticipated to continue to evolve for application to a range of emerging breast imaging modalities.

Discrimination of Breast Cancer from Healthy Breast Tissue Using a Three-component Diffusion-weighted MRI Model.

PURPOSE: Diffusion-weighted MRI (DW-MRI) is a contrast-free modality that has demonstrated ability to discriminate between predefined benign and malignant breast lesions. However, how well DW-MRI discriminates cancer from all other breast tissue voxels in a clinical setting is unknown. Here we explore the voxelwise ability to distinguish cancer from healthy breast tissue using signal contributions from the newly developed three-component multi-b-value DW-MRI model. EXPERIMENTAL DESIGN: Patients with pathology-proven breast cancer from two datasets (n = 81 and n = 25) underwent multi-b-value DW-MRI. The three-component signal contributions C 1 and C 2 and their product, C 1 C 2, and signal fractions F 1, F 2, and F 1 F 2 were compared with the image defined on maximum b-value (DWI max), conventional apparent diffusion coefficient (ADC), and apparent diffusion kurtosis (K app). The ability to discriminate between cancer and healthy breast tissue was assessed by the false-positive rate given a sensitivity of 80% (FPR80) and ROC AUC. RESULTS: Mean FPR80 for both datasets was 0.016 [95% confidence interval (CI), 0.008-0.024] for C 1 C 2, 0.136 (95% CI, 0.092-0.180) for C 1, 0.068 (95% CI, 0.049-0.087) for C 2, 0.462 (95% CI, 0.425-0.499) for F 1 F 2, 0.832 (95% CI, 0.797-0.868) for F 1, 0.176 (95% CI, 0.150-0.203) for F 2, 0.159 (95% CI, 0.114-0.204) for DWI max, 0.731 (95% CI, 0.692-0.770) for ADC, and 0.684 (95% CI, 0.660-0.709) for K app. Mean ROC AUC for C 1 C 2 was 0.984 (95% CI, 0.977-0.991). CONCLUSIONS: The C 1 C 2 parameter of the three-component model yields a clinically useful discrimination between cancer and healthy breast tissue, superior to other DW-MRI methods and obliviating predefining lesions. This novel DW-MRI method may serve as noncontrast alternative to standard-of-care dynamic contrast-enhanced MRI.

Adaptations of Breast Imaging Centers to the COVID-19 Pandemic: A Survey of California and Texas.

OBJECTIVE: To determine the early impact of the COVID-19 pandemic on breast imaging centers in California and Texas and compare regional differences. METHODS: An 11-item survey was emailed to American College of Radiology accredited breast imaging facilities in California and Texas in August 2020. A question subset addressed March-April government restrictions on elective services ("during the shutdown" and "after reopening"). Comparisons were made between states with chi-square and Fisher's tests, and timeframes with McNemar's and paired t-tests. RESULTS: There were 54 respondents (54/240, 23%, 26 California, 28 Texas). Imaging volumes fell during the shutdown and remained below pre-pandemic levels after reopening, with reduction in screening greatest (ultrasound 12% of baseline, mammography 13%, MRI 23%), followed by diagnostic MRI (43%), procedures (44%), and diagnostics (45%). California reported higher volumes during the shutdown (procedures, MRI) and after reopening (diagnostics, procedures, MRI) versus Texas (P = 0.001-0.02). Most screened patients (52/54, 96% symptoms and 42/54, 78% temperatures), and 100% (53/53) modified check-in and check-out. Reading rooms or physician work were altered for social distancing (31/54, 57%). Physician mask (45/48, 94%), gown (15/48, 31%), eyewear (22/48, 46%), and face shield (22/48, 46%) use during procedures increased after reopening versus pre-pandemic (P < 0.001-0.03). Physician (47/54, 87%) and staff (45/53, 85%) financial impacts were common, but none reported terminations. CONCLUSION: Breast imaging volumes during the early pandemic fell more severely in Texas than in California. Safety measures and financial impacts on physicians and staff were similar in both states.

Predicting breast cancer response to neoadjuvant treatment using multi-feature MRI: results from the I-SPY 2 TRIAL.

Dynamic contrast-enhanced (DCE) MRI provides both morphological and functional information regarding breast tumor response to neoadjuvant chemotherapy (NAC). The purpose of this retrospective study is to test if prediction models combining multiple MRI features outperform models with single features. Four features were quantitatively calculated in each MRI exam: functional tumor volume, longest diameter, sphericity, and contralateral background parenchymal enhancement. Logistic regression analysis was used to study the relationship between MRI variables and pathologic complete response (pCR). Predictive performance was estimated using the area under the receiver operating characteristic curve (AUC). The full cohort was stratified by hormone receptor (HR) and human epidermal growth factor receptor 2 (HER2) status (positive or negative). A total of 384 patients (median age: 49 y/o) were included. Results showed analysis with combined features achieved higher AUCs than analysis with any feature alone. AUCs estimated for the combined versus highest AUCs among single features were 0.81 (95% confidence interval [CI]: 0.76, 0.86) versus 0.79 (95% CI: 0.73, 0.85) in the full cohort, 0.83 (95% CI: 0.77, 0.92) versus 0.73 (95% CI: 0.61, 0.84) in HR-positive/HER2-negative, 0.88 (95% CI: 0.79, 0.97) versus 0.78 (95% CI: 0.63, 0.89) in HR-positive/HER2-positive, 0.83 (95% CI not available) versus 0.75 (95% CI: 0.46, 0.81) in HR-negative/HER2-positive, and 0.82 (95% CI: 0.74, 0.91) versus 0.75 (95% CI: 0.64, 0.83) in triple negatives. Multi-feature MRI analysis improved pCR prediction over analysis of any individual feature that we examined. Additionally, the improvements in prediction were more notable when analysis was conducted according to cancer subtype.

Noncontrast MRI with advanced diffusion weighted imaging for breast cancer detection in a lactating woman.

Magnetic resonance imaging (MRI) is used for preoperative evaluation, high-risk screening, and other select indications for breast cancer. However, the interpretation of breast MR images in pregnant and lactating women is complicated by physiologic changes of the breast that may result in marked background enhancement. Breast MRI with contrast administration is contraindicated in pregnancy. Restriction spectrum imaging (RSI) is an advanced diffusion-weighted (DW)-MRI method that theoretically reflects signal from cells with high nuclear-to-cytoplasm ratio without gadolinium-based contrast. This report describes a case in which RSI notably increased tumor conspicuity in a lactating woman, compared to contrast-enhanced (CE)-MRI and conventional DW-MRI.