Virtual Reality Simulation-Based Training in Image-Guided Breast Intervention in Low- and Middle-Income Countries.

Online education has revolutionized global radiology education for low- and middle-income countries (LMICs). However, procedures requiring hands-on training, such as breast biopsies, are primarily taught through in-person sessions and patient interaction. Virtual reality (VR) offers an immersive way to simulate these sessions remotely. This Viewpoint presents an experience with an ultrasound-guided breast biopsy VR platform that may allow LMIC radiology residents to practice breast interventions and provide all trainees with shared procedural experiences.

Maximizing Mentorship Throughout Your Breast Imaging Career.

Unlike many other subspecialties in radiology, breast radiologists practice in a patient-facing and interdisciplinary environment where team building, communication, and leadership skills are critical. Although breast radiologists can improve these skills over time, strong mentorship can accelerate this process, leading to a more successful and satisfying career. In addition to providing advice, insight, feedback, and encouragement to mentees, mentors help advance the field of breast radiology by contributing to the development of the next generation of leaders. During the mentorship process, mentors continue to hone their listening, problem-solving, and networking skills, which in turn creates a more supportive and nurturing work environment for the entire breast care team. This article reviews important mentorship skills that are essential for all breast radiologists. Although some of the principles apply to all mentoring relationships, ensuring that every breast radiologist has the skills to be both an effective mentor and mentee is key to the future of the profession.

Ultrafast MR imaging findings of 2 different subtypes in a male patient with bilateral breast cancer.

Bilateral breast cancer in males is an exceedingly rare diagnosis. In this case report, we will discuss the ultrafast sequence findings of a bilateral male breast cancer with different subtypes on his staging dynamic contrast enhanced (DCE) MRI with ultrafast technique. A 94-year-old male presented with bilateral palpable complaints in his breasts. Diagnostic mammography and ultrasound images demonstrated bilateral irregular masses with nipple retraction. Biopsies were performed and the histopathologic examination revealed invasive breast carcinoma of no special type in 1 breast and invasive micropapillary carcinoma in the other breast. Staging MRI with ultrafast sequence showed significant enhancement differences between 2 different subtypes, correlating with the different levels of tumor aggressiveness. Different ultrafast metrics, such as time-to-enhancement and maximum slope, may help to differentiate between several subtypes of breast cancer and serve as prognostic indicators. This case report discusses the application of ultrafast sequence in predicting breast cancer subtypes in a male patient with bilateral disease.

Why Start Now? Retrospective Study Evaluating Baseline Screening Mammography in Patients Age 60 and Older.

PURPOSE: Extensive data exist regarding the importance of baseline mammography and screening recommendations in the age range of 40-50 years old, however, less is known about women who start screening at age 60. The purpose of this retrospective study is to assess the characteristics and outcomes of women aged 60 years and older presenting for baseline mammographic screening. METHODS: This is an IRB-approved single institution retrospective review of data from patients aged 60+ receiving baseline screening mammograms between 2010 and 2022 was obtained. Information regarding patient demographics, breast density, and BI-RADS assessment was acquired from Cerner EHR. Of patients with a BI-RADS 0 assessment, imaging, and chart review was performed. Family history, gynecologic history, prior breast biopsy or surgery, and hormone use was reviewed. For those with a category 4 or 5 assessment after diagnostic work-up, biopsy outcomes were reported. Cancer detection rate (CDR), recall rate (RR), positive predictive value 1 (PPV1), PPV2, and PPV3 were calculated. RESULTS: Data was analyzed from 1409 women over age 60 who underwent breast cancer screening. The recall rate was 29.3% (413/1409). The CDR, PPV1, PPV2, and PPV3 were calculated as 15/1000, 5.2% (21/405), 29.2% (21/72), and 31.8% (21/66), respectively. After work-up, 224 diagnostic patients had a 1-year follow-up and none were diagnosed with breast cancer. One (1.4%, 1/71) of the BI-RADS 3 lesions was malignant at 2-year follow-up. Of the patients recalled from screening, 29.6% had a family history of breast cancer, and the majority of both recalled and nonrecalled patients had Category B breast density. There was no statistically significant difference in breast density or race of patients recalled vs not recalled. 93.2% of recalled cases were given BI-RADS descriptors, with mass and focal asymmetry being the most common lesions, and 22.1% of recalled cases included more than one lesion. CONCLUSION: Initiating screening mammography for patients over 60 years old may result in higher recall rates, but also leads to a high CDR of potentially clinically relevant invasive cancers. After a diagnostic work-up, BI-RADS 3 assessments are within standard guidelines. This study provides guidance for radiologists reading baseline mammograms and clinicians making screening recommendations in patients over age 60.

The impact of gamification and potential of kaizen in radiology education.

Gamification is an emerging tool in medical education that has been increasingly adopted in the field of radiology. The purpose of this non-systematic review is to explore the use of gamification in medical education with a particular focus on new generations of learners and radiology education. This manuscript begins by examining the effectiveness of gamification in improving learning outcomes in medicine and radiology. Future research recommendations and the potential impact of gamification on new learners are discussed. Finally, this review provides insight into a gaming platform, Kaizen, as a promising approach to enhance education by improving motivation and increasing interest in radiology knowledge.

A pictorial guide to artifacts on contrast mammography: How to avoid pitfalls and improve interpretation.

Contrast-enhanced mammography (CEM) is an increasingly accepted emerging imaging modality that demonstrates a similar sensitivity to MRI but has the advantage of being less time consuming and inexpensive. The use of CEM continues to expand as it is recognized and utilized as a valuable tool for diagnostic and potentially screening examinations. As with any radiologic examination, artifacts occur and knowledge of these is important for adequate image interpretation. The purpose of this paper is to provide a pictorial review the common artifacts encountered on CEM examinations and identify causes and potential resolutions.

Classifying Breast Cancer Metastasis Based on Imaging of Tumor Primary and Tumor Biology.

The molecular classification of breast cancer has allowed for a better understanding of both prognosis and treatment of breast cancer. Imaging of the different molecular subtypes has revealed that biologically different tumors often exhibit typical features in mammography, ultrasound, and MRI. Here, we introduce the molecular classification of breast cancer and review the typical imaging features of each subtype, examining the predictive value of imaging with respect to distant metastases.

Analysis of simplicial complexes to determine when to sample for quantitative DCE MRI of the breast.

PURPOSE: A method is presented to select the optimal time points at which to measure DCE-MRI signal intensities, leaving time in the MR exam for high-spatial resolution image acquisition. THEORY: Simplicial complexes are generated from the Kety-Tofts model pharmacokinetic parameters Ktrans and ve . A geometric search selects optimal time points for accurate estimation of perfusion parameters. METHODS: The DCE-MRI data acquired in women with invasive breast cancer (N = 27) were used to retrospectively compare parameter maps fit to full and subsampled time courses. Simplicial complexes were generated for a fixed range of Kety-Tofts model parameters and for the parameter ranges weighted by estimates from the fully sampled data. The largest-area manifolds determined the optimal three time points for each case. Simulations were performed along with retrospectively subsampled data fits. The agreement was computed between the model parameters fit to three points and those fit to all points. RESULTS: The optimal three-point sample times were from the data-informed simplicial complex analysis and determined to be 65, 204, and 393 s after arrival of the contrast agent to breast tissue. In the patient data, tumor-median parameter values fit using all points and the three selected time points agreed with concordance correlation coefficients of 0.97 for Ktrans and 0.67 for ve . CONCLUSION: It is possible to accurately estimate pharmacokinetic parameters from three properly selected time points inserted into a clinical DCE-MRI breast exam. This technique can provide guidance on when to capture images for quantitative data between high-spatial-resolution DCE-MRI images.

Breast Cancer Genomics: Primary and Most Common Metastases.

Specific genomic alterations have been found in primary breast cancer involving driver mutations that result in tumorigenesis. Metastatic breast cancer, which is uncommon at the time of disease onset, variably impacts patients throughout the course of their disease. Both the molecular profiles and diverse genomic pathways vary in the development and progression of metastatic breast cancer. From the most common metastatic site (bone), to the rare sites such as orbital, gynecologic, or pancreatic metastases, different levels of gene expression indicate the potential involvement of numerous genes in the development and spread of breast cancer. Knowledge of these alterations can, not only help predict future disease, but also lead to advancement in breast cancer treatments. This review discusses the somatic landscape of breast primary and metastatic tumors.

Childbearing in radiology training and early career: Challenges, opportunities, and finding the best time for you.

For many women, radiology residency occurs during the childbearing years and they often question when is the best time to have children. Anxiety regarding fertility and pregnancy-related complications contribute to early career burnout in women physicians and many have fertility regrets. Supporting radiologists in training and early in their career as they navigate pregnancy and childbearing is critical to achieving a diverse workforce and leadership. Herein, we explore career-related challenges of childbearing and highlight opportunities for radiologists in residency, fellowship, and early in their career, so that they can make an informed childbearing decision.

Breast papillomas in the United States: single institution data on underrepresented minorities with a multi-institutional update on incidence.

PURPOSE: To assess the percentage of papillomas from all biopsies performed, comparing differences in patient age and race at a single institution. To assess trends in biopsied papillomas at institutions throughout the United States (US). METHODS: This is a HIPPA-compliant IRB-approved single-institution (Southern1) retrospective review to assess race and age of all-modality-biopsied non-malignant papillomas as a percentage of all biopsies (percentage papillomas calculated as papilloma biopsies/all biopsies) from January 2012 to December 2019. To assess national variation, several academic or large referral centers were contacted to provide data regarding papilloma percentages, biopsy modalities, and trends in case numbers. Trends were estimated using the method of analysis of variance (ANOVA). Comparisons of differences in trends were assessed. RESULTS: Southern1 institution demonstrated a significant association between race and percentage of papillomas (p < 0.0001). After adjustment for multiple comparisons with Bonferroni correction at 5% type I family error, the percentage of biopsied papillomas in Black and Asian patients remained significantly higher than in White patients (p < 0.0001 and p = 0.0032, respectively) using a Chi-square test. The regional variation in percentage of papillomas was found to be 3-9%. Southern1 institution showed a 7-year significant trend of increase in percentage of papillomas. Other institutions showed a decreasing trend (p < 0.05). CONCLUSION: Black and Asian women had significantly higher papilloma percentages compared to white patients in our single institution review. This institution also showed a statistically significant trend of increasing percentage papillomas from 2012 to 2019. Multi-institutional survey found regional variation in percentage papillomas, ranging from 3% to 9%.

From the Reading Room to Operating Room: Retrospective Data and Pictorial Review After 806 SCOUT Placements.

OBJECTIVE: Non-wire localization techniques are becoming more common. SCOUT surgical guidance system has been shown to increase flexibility in scheduling patients for surgery. The objective of this article is to provide institutional experiences with pictorial review after placement of 806 SCOUT devices. MATERIALS AND METHODS: Radiology procedure reports of SCOUT device placements from January 11, 2018 to May 19, 2020 were reviewed to assess demographics of patient population, imaging method of placement, size of reflector delivery system used, placement approach, and time spent in the radiology suite or Turn Around Time (TAT). TAT was compared to that of wire placement using a Two-tailed Mann-Whitney U Test. Reports were assessed for those with absent signal at time of placement. In cases where signal was absent, migration was found, or complications noted, further case review was performed using the Electronic Medical Record to assess whether the devices were successfully retrieved. RESULTS: There were 806 total SCOUT placements identified from radiology procedure reports in patients aged 12-92 with 64.3% (518/806) placed using ultrasound-guidance and 35.7% (288/806) by mammographic-guidance. The most common delivery device was a 7.5 cm needle. Only 0.9% (7/806) of SCOUT reflectors were >1cm from target, all of which were successfully excised. After radiology placement, signal was not heard in 1.4% (9/806) of cases and individual case review revealed that all were successfully excised. In 2019, TATs of SCOUT procedures were significantly lower than TATs from wire localizations (P = 0.00024). CONCLUSIONS: SCOUT localization for breast surgery can provide solutions to problems encountered by patients and providers. A year after implementation, SCOUT use was found to result in shorter TATs in radiology. In addition, 100% of devices that were either migrated or inaudible at the time of radiology placement were successfully excised.

Quantitative multiparametric MRI predicts response to neoadjuvant therapy in the community setting.

BACKGROUND: The purpose of this study was to determine whether advanced quantitative magnetic resonance imaging (MRI) can be deployed outside of large, research-oriented academic hospitals and into community care settings to predict eventual pathological complete response (pCR) to neoadjuvant therapy (NAT) in patients with locally advanced breast cancer. METHODS: Patients with stage II/III breast cancer (N = 28) were enrolled in a multicenter study performed in community radiology settings. Dynamic contrast-enhanced (DCE) and diffusion-weighted (DW)-MRI data were acquired at four time points during the course of NAT. Estimates of the vascular perfusion and permeability, as assessed by the volume transfer rate (Ktrans) using the Patlak model, were generated from the DCE-MRI data while estimates of cell density, as assessed by the apparent diffusion coefficient (ADC), were calculated from DW-MRI data. Tumor volume was calculated using semi-automatic segmentation and combined with Ktrans and ADC to yield bulk tumor blood flow and cellularity, respectively. The percent change in quantitative parameters at each MRI scan was calculated and compared to pathological response at the time of surgery. The predictive accuracy of each MRI parameter at different time points was quantified using receiver operating characteristic curves. RESULTS: Tumor size and quantitative MRI parameters were similar at baseline between groups that achieved pCR (n = 8) and those that did not (n = 20). Patients achieving a pCR had a larger decline in volume and cellularity than those who did not achieve pCR after one cycle of NAT (p < 0.05). At the third and fourth MRI, changes in tumor volume, Ktrans, ADC, cellularity, and bulk tumor flow from baseline (pre-treatment) were all significantly greater (p < 0.05) in the cohort who achieved pCR compared to those patients with non-pCR. CONCLUSIONS: Quantitative analysis of DCE-MRI and DW-MRI can be implemented in the community care setting to accurately predict the response of breast cancer to NAT. Dissemination of quantitative MRI into the community setting allows for the incorporation of these parameters into the standard of care and increases the number of clinical community sites able to participate in novel drug trials that require quantitative MRI.

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.

Out With the Old and in With the New? Factors Involved in Migration of Older and Newer Generation Stereotactic Breast Biopsy Markers.

OBJECTIVE: The purpose of this study was to investigate four commonly used stereotactic biopsy markers, two older and two newer generation, assessing percentage migration and factors influencing migration distance. METHODS: This was an IRB-approved retrospective review of upright stereotactic breast biopsies from May 2018 to May 2020 involving either older (Cork, Hourglass) or newer (Vision, X-shaped) generation markers. Markers were assessed for migration rate by two-sample Z-test and migration distance by analysis of variance. Univariate analysis was used to assess relationships between marker type and generation, patient characteristics, breast composition and thickness, procedure techniques, trainee involvement, and complications, correlating with migration distance. Multivariable analysis was performed for variables with P-value < 0.1 on univariate analysis. Tukey's test was used to compare groups (P < 0.05). RESULTS: In total, 732 stereotactic biopsies were performed with 508 using a Cork, Hourglass, Vision, or X-shaped marker. Overall migration rate was 181/508 (35.6%) with no difference between markers. Breast thickness and density were negatively associated with migration distance in univariate analysis. Older marker migration distance was greater than newer (2.6 cm vs 1.9 cm, respectively), which was significant after adjusting for breast thickness and density (P = 0.037). Density was a significant factor in migration distance, comparing fatty to nonfatty breasts (P < 0.05) in univariate analysis. CONCLUSION: No difference in migration rate was seen between the four markers. Vision and X-shaped markers demonstrate lower migration distance than Cork and Hourglass in multivariate analysis. There is an inverse relationship between breast density and marker migration distance.

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.

Imaging for Response Assessment in Cancer Clinical Trials.

The use of biomarkers is integral to the routine management of cancer patients, including diagnosis of disease, clinical staging and response to therapeutic intervention. Advanced imaging metrics with computed tomography (CT), magnetic resonance imaging (MRI), and positron emission tomography (PET) are used to assess response during new drug development and in cancer research for predictive metrics of response. Key components and challenges to identifying an appropriate imaging biomarker are selection of integral vs integrated biomarkers, choosing an appropriate endpoint and modality, and standardization of the imaging biomarkers for cooperative and multicenter trials. Imaging biomarkers lean on the original proposed quantified metrics derived from imaging such as tumor size or longest dimension, with the most commonly implemented metrics in clinical trials coming from the Response Evaluation Criteria in Solid Tumors (RECIST) criteria, and then adapted versions such as immune-RECIST (iRECIST) and Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) for immunotherapy response and PET imaging, respectively. There have been many widely adopted biomarkers in clinical trials derived from MRI including metrics that describe cellularity and vascularity from diffusion-weighted (DW)-MRI apparent diffusion coefficient (ADC) and Dynamic Susceptibility Contrast (DSC) or dynamic contrast enhanced (DCE)-MRI (Ktrans, relative cerebral blood volume (rCBV)), respectively. Furthermore, Fluorodexoyglucose (FDG), fluorothymidine (FLT), and fluoromisonidazole (FMISO)-PET imaging, which describe molecular markers of glucose metabolism, proliferation and hypoxia have been implemented into various cancer types to assess therapeutic response to a wide variety of targeted- and chemotherapies. Recently, there have been many functional and molecular novel imaging biomarkers that are being developed that are rapidly being integrated into clinical trials (with anticipation of being implemented into clinical workflow in the future), such as artificial intelligence (AI) and machine learning computational strategies, antibody and peptide specific molecular imaging, and advanced diffusion MRI. These include prostate-specific membrane antigen (PSMA) and trastuzumab-PET, vascular tumor burden extracted from contrast-enhanced CT, diffusion kurtosis imaging, and CD8 or Granzyme B PET imaging. Further excitement surrounds theranostic procedures such as the combination of 68Ga/111In- and 177Lu-DOTATATE to use integral biomarkers to direct care and personalize therapy. However, there are many challenges in the implementation of imaging biomarkers that remains, including understand the accuracy, repeatability and reproducibility of both acquisition and analysis of these imaging biomarkers. Despite the challenges associated with the biological and technical validation of novel imaging biomarkers, a distinct roadmap has been created that is being implemented into many clinical trials to advance the development and implementation to create specific and sensitive novel imaging biomarkers of therapeutic response to continue to transform medical oncology.