Faculty Bibliography

OBJECTIVE:The purpose of this study was to investigate county-level geographic patterns of mammographic screening uptake throughout the United States and to determine the impact of rural versus urban settings on breast cancer screening uptake. MATERIALS AND METHODS/METHODS:This descriptive study used County Health Rankings (CHR) data to identify the percentage of Medicare enrollees 67-69 years old per county who had at least one mammogram in 2013 or 2012 (uptake). Uptake was matched with U.S. Department of Agriculture (USDA) Atlas of Rural and Small Town America categorizations along a rural-urban continuum scale from 1 to 9 based on county population size (large urban, population ≥ 20,000 people; small urban, < 20,000 people) and proximity to a metropolitan area. Univariable and multivariable analyses were performed. RESULTS:In all, 2,243,294 Medicare beneficiaries were eligible for mammograms. National mean uptake per county was 60.5% (range, 26.0-86.0%). Uptake was significantly higher in metropolitan and large urban counties in 25 states and lower in only one. County-level mammographic uptake was moderately positively correlated with percentage of residents with some college education (r = 0.40, p < 0.001) and moderately negatively correlated with age-adjusted mortality (r = -0.41, p < 0.001). Multivariable analysis showed that percentage of white and black residents and age-adjusted mortality rate were the strongest significant independent predictors of uptake. CONCLUSION/CONCLUSIONS:Uptake of mammographic screening services in a Medicare population varies widely at the county level and is generally lowest in rural counties and urban counties with fewer than 20,000 people.

PURPOSE/OBJECTIVE:To evaluate transgender patient care, gender inclusivity, and transgender health-related policies at breast imaging facilities across the United States. METHODS:A survey on breast imaging facilities' policies and practices regarding transgender care was distributed to the membership of the Society of Breast Imaging, consisting of approximately 2,500 breast radiologists across the United States. The survey was conducted by e-mail in January 2018. RESULTS:There were 144 survey respondents. Responses showed that 78.5% of facilities have gender-neutral patient bathrooms, 9.0% have a separate waiting area for transgender patients, and 76.4% do not have dominant pink hues in their facilities, although 54.2% have displays with female gender content. Also, 58.0% of intake forms do not ask patients to provide their gender identity, although 25.9% automatically populate with female phrases. Within the electronic health record, 32.9% lack a distinct place to record patients' preferred names and 54.9% lack a distinct place to record patients' gender pronouns. The majority (73.4%) do not have explicit policies related to the care of transgender patients. Only 14.7% of facilities offer lesbian, gay, bisexual, and transgender training. CONCLUSION/CONCLUSIONS:Our national survey demonstrates that many breast imaging facilities do not have structures in place to consistently use patients' preferred names and pronouns, nor provide inclusive environments for transgender patients. All breast imaging facilities should recognize the ways in which their practices may intensify discrimination, exclusivity, and stigma for transgender patients and should seek to improve their transgender health competencies and foster more inclusive environments.

In detection, treatment, and follow-up, male breast cancer has historically lagged behind female breast cancer. On the whole, breast cancer is less common among men than among women, limiting utility of screening, yet the incidence of male breast cancer is rising, and there are men at high risk for breast cancer. While women at high risk for breast cancer are well characterized, with clearly established guidelines for screening, supplemental screening, risk prevention, counseling, and advocacy, men at high risk for breast cancer are poorly identified and represent a blind spot in public health. Today, more standardized genetic counseling and wider availability of genetic testing are allowing identification of high-risk male relatives of women with breast cancer, as well as men with genetic mutations predisposing to breast cancer. This could provide a new opportunity to update our approach to male breast cancer. This article reviews male breast cancer demographics, risk factors, tumor biology, and oncogenetics; recognizes how male breast cancer differs from its female counterpart; highlights its diagnostic challenges; discusses the implications of the widening clinical use of multigene panel testing; outlines current National Comprehensive Cancer Network guidelines (version 1, 2018) for high-risk men; and explores the possible utility of targeted screening and surveillance. Understanding the current state of male breast cancer management and its challenges is important to shape future considerations for care. Shifting the paradigm of male breast cancer detection toward targeted precision medicine may be the answer to improving clinical outcomes of this uncommon disease. ^©RSNA, 2018.

RATIONALE AND OBJECTIVES/OBJECTIVE:The present study aims to assess associations of Medicare beneficiary screening mammography rates with local mammography facility and radiologist availability. MATERIALS AND METHODS/METHODS:Mammography screening rates for Medicare fee-for-service beneficiaries were obtained for US counties using the County Health Rankings data set. County-level certified mammography facility counts were obtained from the United States Food and Drug Administration. County-level mammogram-interpreting radiologist and breast imaging subspecialist counts were determined using Centers for Medicare & Medicaid Services fee-for-service claims files. Spearman correlations and multivariable linear regressions were performed using counties' facility and radiologist counts, as well as counts normalized to counties' Medicare fee-for-service beneficiary volume and land area. RESULTS:Across 3035 included counties, average screening mammography rates were 60.5% ± 8.2% (range 26%-88%). Correlations between county-level screening rates and total mammography facilities, facilities per 100,000 square mile county area, total mammography-interpreting radiologists, and mammography-interpreting radiologists per 100,000 county-level Medicare beneficiaries were all weak (r = 0.22-0.26). Correlations between county-level screening rates and mammography rates per 100,000 Medicare beneficiaries, total breast imaging subspecialist radiologists, and breast imaging subspecialist radiologists per 100,000 Medicare beneficiaries were all minimal (r = 0.06-0.16). Multivariable analyses overall demonstrated radiologist supply to have a stronger independent effect than facility supply, although effect sizes remained weak for both. CONCLUSION/CONCLUSIONS:Mammography facility and radiologist supply-side factors are only weakly associated with county-level Medicare beneficiary screening mammography rates, and as such, screening mammography may differ from many other health-care services. Although efforts to enhance facility and radiologist supply may be helpful, initiatives to improve screening mammography rates should focus more on demand-side factors, such as patient education and primary care physician education and access.

BACKGROUND: Screening breast MRI has been shown to preferentially detect high-grade ductal carcinoma in situ (DCIS) and invasive carcinoma, likely due to increased angiogenesis resulting in early initial uptake of contrast. As interest grows in abbreviated screening breast MRI (AB-MRI), markers of early contrast washin that can predict tumor grade and potential aggressiveness are of clinical interest. PURPOSE: To evaluate the feasibility of using the initial enhancement ratio (IER) as a surrogate marker for tumor grade, hormone receptor status, and prognostic markers, as an initial step to being incorporated into AB-MRI. STUDY TYPE: Retrospective. SUBJECTS: In all, 162 women (mean 55.0 years, range 32.8-87.7 years) with 187 malignancies imaged January 2012-November 2015. FIELD STRENGTH/SEQUENCE: Images were acquired at 3.0T with a T1 -weighted gradient echo fat-suppressed-volume interpolated breath-hold sequence. ASSESSMENT: Subjects underwent dynamic contrast-enhanced breast MRI with a 7-channel breast coil. IER (% signal increase over baseline at the first postcontrast acquisition) was assessed and correlated with background parenchymal enhancement, washout curves, stage, and final pathology. STATISTICAL TESTS: Chi-square test, Spearman rank correlation, Mann-Whitney U-tests, Bland-Altman analysis, and receiver operating characteristic curve analysis. RESULTS: IER was higher for invasive cancer than for DCIS (R1/R2, P < 0.001). IER increased with tumor grade (R1: r = 0.56, P < 0.001, R2: r = 0.50, P < 0.001), as ki-67 increased (R1: r = 0.35, P < 0.001; R2 r = 0.35, P < 0.001), and for node-positive disease (R1/R2, P = 0.001). IER was higher for human epidermal growth factor receptor two-positive and triple negative cancers than for estrogen receptor-positive / progesterone receptor-positive tumors (R1 P < 0.001-0.002; R2 P = 0.0.001-0.011). IER had higher sensitivity (80.6% vs. 75.5%) and specificity (55.8% vs. 48.1%) than washout curves for positive nodes, higher specificity (48.1% vs. 36.5%) and positive predictive value (70.2% vs. 66.7%) for high ki-67, and excellent interobserver agreement (intraclass correlation coefficient = 0.82). DATA CONCLUSION: IER, a measurement of early contrast washin, is associated with higher-grade malignancies and tumor aggressiveness and might be potentially incorporated into an AB-MRI protocol. LEVEL OF EVIDENCE: 3 Technical Efficacy Stage 2 J. Magn. Reson. Imaging 2017.

Breast density, fibroglandular tissue, and background parenchymal enhancement (BPE) are recognized independent biomarkers for breast cancer risk. For this reason, reproducibility and consistency in objective assessment of these parameters at mammography (breast density) and at magnetic resonance imaging (fibroglandular tissue and BPE) are clinically relevant. However, breast density, fibroglandular tissue, and BPE are manifestations of dynamic physiologic processes and may change in response to both endogenous and exogenous hormonal stimulation. It is therefore important for the radiologist to recognize settings in which hormonal stimulation may alter the appearance of these biomarkers at imaging and to appreciate how such changes may affect risk assessment, cancer detection, and even prognosis. The purpose of this review article is therefore to review key features and means of evaluating breast density, fibroglandular tissue, and BPE at imaging; to detail how endogenous and exogenous hormonal stimuli may affect breast density, fibroglandular tissue, and BPE, potentially affecting radiologic interpretation; and, finally, to provide an update regarding current hormone treatment guidelines and indications that may result in imaging changes through hormone modulation. ^©RSNA, 2018.

Precision medicine is medicine optimized to the genotypic and phenotypic characteristics of an individual and, when present, his or her disease. It has a host of targets, including genes and their transcripts, proteins, and metabolites. Studying precision medicine involves a systems biology approach that integrates mathematical modeling and biology genomics, transcriptomics, proteomics, and metabolomics. Moreover, precision medicine must consider not only the relatively static genetic codes of individuals, but also the dynamic and heterogeneous genetic codes of cancers. Thus, precision medicine relies not only on discovering identifiable targets for treatment and surveillance modification, but also on reliable, noninvasive methods of identifying changes in these targets over time. Imaging via radiomics and radiogenomics is poised for a central role. Radiomics, which extracts large volumes of quantitative data from digital images and amalgamates these together with clinical and patient data into searchable shared databases, potentiates radiogenomics, which is the combination of genetic and radiomic data. Radiogenomics may provide voxel-by-voxel genetic information for a complete, heterogeneous tumor or, in the setting of metastatic disease, set of tumors and thereby guide tailored therapy. Radiogenomics may also quantify lesion characteristics, to better differentiate between benign and malignant entities, and patient characteristics, to better stratify patients according to risk for disease, thereby allowing for more precise imaging and screening. This report provides an overview of precision medicine and discusses radiogenomics specifically in breast cancer. ^© RSNA, 2018.

Purpose Our aim was to evaluate the accuracy of a new algorithm to automatically delineate the breast region from the chest on T1-weighted, non-fat-suppressed MR images. This process is also referred to as the chest wall detection. There is a general agreement that this step is very difficult to automate. At the same time it is crucially needed for clinically important processing workflows [1]. These workflows include 3D measurement of breast density and of the breast parenchymal enhancement. Both measures reveal patients at risk of breast cancer [2]. Manually traced chest wall was used as the ground truth when estimating the segmentation errors. Segmentation accuracy was evaluated using the Hausdorff distance and the volumetric error. We also estimated the inter-observer agreement in defining the chest wall surface. Methods The program starts by generating the mid-sagittal 2D section by averaging the signal across 20 mm thick mid-sagittal slab. We determine the chest wall boundary on this image by modeling the signal profiles along the antero-posterior direction as a sequence of three tissues: background air, skin and fat layer, muscle. Non-uniformity correction is then applied to the entire 3D volume. The mid-sagittal boundary, represented as a polyline P, is then propagated in two opposite (left and right) directions. At each sagittal section the algorithm adjusts the control points of the polyline received from an adjacent slice. The adjustment is estimated from the weighted sum of six measures that combine specific local and global signal statistics. These include: the local gradient, the signal uniformity, the gradient similarity, the contour-gradient consistency, the global contour uniformity and the normal vector consistency. At each iteration we form a candidate shift vector, we apply it to shift P to its new position, and then we smooth the resulting polyline. The process terminates when the magnitude of the shift becomes negligible or when the specified number of iterations is exceeded. Two metrics were used to estimate accuracy. The conventional volumetric error was obtained by dividing the volume DV of misclassified breast voxels over the true breast volume V. The Hausdorff distance, HD, is the distance between each voxel on the true breast/ chest wall border and the closest boundary voxel produced by the algorithm. HD is averaged over the entire chest wall surface. From a clinical database of screening breast MRIs acquired at our medical center we have randomly selected 16 test exams. The selection was constrained to enforce that there were four exams in each of the four breast density categories [3]. Bilateral breasts were imaged on Siemens 3T Magnetom Trio equipped with a 7-element surface breast coil. The parameters of the T1-weighted non-fat-suppressed sequence were: TR = 4.74 ms, TE = 1.79 ms, FOV = 320 mm2, matrix = 448 9 358 9*150, 0.7 9 0.7 9 1.1 mm voxels, TA = 2-3 min. Three experts in breast and chest anatomy drew contours to separate the chest wall from the breast (Fig. 1). The pectoralis fascia and pectoralis muscles were used as reference points for the anterolateral borders. The medial border of the axilla was the posterolateral boundary. The axillary tail was considered as the breast tissue. The ground truth references were constructed by a software designed to perform voxel-based ROI averaging [4]. (Figure Presented) Results The border distance error HD was 0.84 +/- 0.8 mm (average +/- standard deviation) and ranged from 0.57 to 2.45 mm. The volume error DV/V was 6.43 +/- 6.82%. There was no correlation between the HD and DV/V (R2 = 0.23, p = 0.12). The test cases covered a wide range 411-3439 ml of breast volumes. There was a significant positive correlation (R2 = 0.40, p = 0.02) between volumetric error and the true breast volume V, but there was no correlation between HD and V (R2 = 0.08, p = 0.44). The average execution time was under 1.5 min per case on a standard 8-core workstation. The inter-observer agreement measured in term of HD was 0.56 +/- 0.15 mm (average +/- standard deviation). The agreement expressed in terms of volumetric discrepancy (relative to breast volume) was 1.61% +/- 0.71%. Conclusion Breast density, defined as fraction of fibroglandular tissue, and postcontrast enhancement, are considered significant risk factors for breast cancer. These MRI measures are recommended for radiologic reports and are promising cancer biomarkers. Radiologists currently visually estimate these measure. Unfortunately, readers agreement for qualitative evaluation is only fair, requiring better standardization and reproducibility. Computer-assisted quantitative assessment is needed, but the task is challenging due to image nonuniformity (breast coils cause loss of MR signal in remote regions) and to the anatomical complexity of chest wall boundary (Fig. 2). (Figure Presented) Given its accuracy and speed, our breast segmentation method appears to be ready for clinical use as a part of larger workflow to generate routine diagnostic reports

Purpose To assess adherence with annual or biennial screening mammography after a diagnosis of high-risk lesion(s) at stereotactic biopsy with or without surgical excision and to identify clinical factors that may affect screening adherence after a high-risk diagnosis. Materials and Methods This institutional review board-approved HIPAA-compliant retrospective study included 208 patients who underwent stereotactic biopsy between January 2012 and December 2014 that revealed a high-risk lesion. Whether the patient underwent surgical excision and/or follow-up mammography was documented. Adherence of these women to a protocol of subsequent mammography within 1 year (9-18 months) or within 2 years (9-30 months) was compared with that of 45 508 women with normal screening mammograms who were imaged during the same time period at the same institution. Possible factors relevant to postdiagnosis management and screening adherence were assessed. Consultation with a breast surgeon was identified by reviewing clinical notes. Uptake of pharmacologic chemoprevention following diagnosis (patient decision to take chemopreventive medications) was assessed. The Fisher exact test was used to compare annual or biennial screening adherence rates. Binary logistic regression was used to identify factors predictive of whether women returned for screening within selected time frames. Results In total, 913 (1.3%) of 67 874 women were given a recommendation to undergo stereotactic biopsy, resulting in diagnosis of 208 (22.8%) of 913 high-risk lesions. Excluding those with a prior personal history of breast cancer or upgrade to cancer at surgery, 124 (66.7%) of 186 women underwent surgery and 62 (33.3%) did not. Overall post-high-risk diagnosis adherence to annual or biennial mammography was similar to that in control subjects (annual, 56.4% vs 50.8%, P = .160; biennial, 62.0% vs 60.1%, P = .630). Adherence was significantly better in the surgical group than in the nonsurgical group for annual mammography (70.0% vs 32.0%; odds ratio [OR] = 5.0; 95% confidence interval [CI]: 2.4, 10.1; P < .001) and for biennial mammography (74.3% vs 40.0%; OR = 4.3; 95% CI: 2.1, 8.8; P < .001). Among the patients in the nonsurgical group, those adherent to annual or biennial mammography were significantly more likely to have seen a breast surgeon than the nonadherent women (annual, 77.3% vs 35.7%, P = .005; biennial, 67.9% vs 36.4%, P = .045). All patients receiving chemopreventive agents underwent a surgical consultation (100%; n = 21). Conclusion Although diagnosis of a high-risk lesion at stereotactic breast biopsy did not compromise overall adherence to subsequent mammographic screening, patients without surgical excision, particularly those who did not undergo a surgical consultation, had significantly lower imaging adherence and chemoprevention uptake as compared with their counterparts who underwent surgery, suggesting that specialist care may be important in optimizing management. © RSNA, 2018.