Faculty Bibliography

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.

PURPOSE: To capture shifts in breast imaging through 21years of scientific meeting abstracts. MATERIALS AND METHODS: RSNA meeting programs (1995-2015) were searched to identify breast imaging scientific oral abstracts. Abstract year, author gender and degree, country, state, study design, modality, topic, funding and disclosures were recorded. Spearman correlation was performed. RESULTS: There was an increase in %women first authors (rs=0.81, p<0.001), in %international abstracts (rs=-0.64, p=0.0002) and in industry funding (rs=0.766, p<0.001). CONCLUSION: %Women first author presenters and %international presence and %industry support increased over time. These areas of flux may be useful for continued tracking.

This article reviews new developments in breast imaging. There is growing interest in creating a shorter, less expensive MR protocol with broader applicability. There is an increasing focus on and consideration for the additive impact that functional analysis of breast pathology have on identifying and characterizing lesions. These developments apply to MR imaging and molecular imaging. This article reviews evolving breast imaging techniques with attention to strengths, weaknesses, and applications of these approaches. We aim to give the reader familiarity with the state of current developments in the field and to increase awareness of what to expect in breast imaging.

Breast implant imaging varies depending on patient age, implant type, and symptoms. For asymptomatic patients (any age, any implant), imaging is not recommended. Rupture of saline implants is often clinically evident, as the saline is resorbed and there is a change in breast contour. With saline implants and equivocal clinical findings, ultrasound (US) is the examination of choice for patients less than 30 years of age, either mammography/digital breast tomosynthesis or US may be used for those 30 to 39 years of age, and mammography/digital breast tomosynthesis is used for those 40 years and older. For patients with suspected silicone implant complication, MRI without contrast or US is used for those less than 30 years of age; MRI without contrast, mammography/digital breast tomosynthesis, or US may be used for those 30 to 39 years of age; and MRI without contrast or mammography/digital breast tomosynthesis is used for those 40 years and older. Patients with unexplained axillary adenopathy and silicone implants (current or prior) are evaluated with axillary US. For patients 30 years and older, mammography/digital breast tomosynthesis is performed in conjunction with US. Last, patients with suspected breast implant-associated anaplastic large-cell lymphoma are first evaluated with US, regardless of age or implant type. The American College of Radiology Appropriateness Criteria are evidence-based guidelines for specific clinical conditions that are reviewed annually by a multidisciplinary expert panel. The guideline development and revision include an extensive analysis of current medical literature from peer reviewed journals and the application of well-established methodologies (RAND/UCLA Appropriateness Method and Grading of Recommendations Assessment, Development, and Evaluation or GRADE) to rate the appropriateness of imaging and treatment procedures for specific clinical scenarios. In those instances where evidence is lacking or equivocal, expert opinion may supplement the available evidence to recommend imaging or treatment.

RATIONALE AND OBJECTIVES/OBJECTIVE:To assess associations between screening mammography utilization and Medicare beneficiaries' relationships with, and impressions of, their primary care physicians. MATERIALS AND METHODS/METHODS:Using the Medicare Current Beneficiary Survey Access to Care Public Use File, we retrospectively studied responses from a national random cross section of Medicare beneficiaries surveyed in 2013 regarding perceptions of their primary care physicians and their screening mammography utilization. Statistical analysis accounted for subject weighting factors to estimate national screening utilization. RESULTS:Among 7492 female Medicare beneficiaries, 62.0% (95% confidence interval 59.8%-64.2%) underwent screening mammography. Utilization was higher for beneficiaries having (vs. not) a regular medical practice or clinic (63.2% vs. 34.6%) and a usual physician (63.8% vs. 50.3%). Utilization was higher for beneficiaries very satisfied (vs. very dissatisfied) with the overall quality of care they received (66.0% vs. 35.8%), their ease of getting to a doctor (67.7% vs. 43.2%), and their physician's concerns for their health (65.7% vs. 53.4%), as well as for beneficiaries strongly agreeing (vs. strongly disagreeing) that their physician is competent (66.0% vs. 54.1%), understands what is wrong (66.3% vs. 47.1%), answers all questions (67.0% vs. 46.7%), and fosters confidence (66.0% vs. 50.6%). Independent predictors of screening mammography utilization (P < .05) were satisfaction with quality of care, having a regular practice or clinic, and satisfaction with ease of getting to their physician. CONCLUSIONS:Screening mammography utilization is higher among Medicare beneficiaries with established primary physician relationships, particularly when those relationships are favorable. To optimize screening mammography utilization, breast imagers are encouraged to support initiatives to enhance high-quality primary care relationships.

PURPOSE/OBJECTIVE:To evaluate whether false-positive stereotactic vacuum-assisted breast biopsy (SVAB) affects subsequent mammographic screening adherence. MATERIALS AND METHODS/METHODS:tests. RESULTS:There were 913 SVABs performed in 2012 to 2014 for imaging detected lesions; of these, malignant or high-risk lesions or biopsies resulting in a recommendation of surgical excision were excluded, leaving 395 SVABs yielding benign pathology in 395 women. Findings were matched with a control population consisting of 45,126 women who had a BI-RADS 1 or 2 screening mammogram and did not undergo breast biopsy. In all, 191 of 395 (48.4%) women with a biopsy with benign results and 22,668 of 45,126 (50.2%) women without biopsy returned for annual follow-up >9 months and ≤18 months after the index examination (P = .479). In addition, 57 of 395 (14.4%) women with a biopsy with benign results and 3,336 of 45,126 (7.4%) women without biopsy returned for annual follow-up >18 months after the index examination (P < .001). Older women, women with personal history of breast cancer, and women with postbiopsy complication after benign SVAB were more likely to return for screening (P = .026, P = .028, and P = .026, respectively). CONCLUSION/CONCLUSIONS:The findings in our study suggest that SVABs with benign results do not negatively impact screening mammography adherence. The previously described "harms" of false-positive mammography and biopsy may be exaggerated.

Early detection decreases breast cancer mortality. The ACR recommends annual mammographic screening beginning at age 40 for women of average risk. Higher-risk women should start mammographic screening earlier and may benefit from supplemental screening modalities. For women with genetics-based increased risk (and their untested first-degree relatives), with a calculated lifetime risk of 20% or more or a history of chest or mantle radiation therapy at a young age, supplemental screening with contrast-enhanced breast MRI is recommended. Breast MRI is also recommended for women with personal histories of breast cancer and dense tissue, or those diagnosed by age 50. Others with histories of breast cancer and those with atypia at biopsy should consider additional surveillance with MRI, especially if other risk factors are present. Ultrasound can be considered for those who qualify for but cannot undergo MRI. All women, especially black women and those of Ashkenazi Jewish descent, should be evaluated for breast cancer risk no later than age 30, so that those at higher risk can be identified and can benefit from supplemental screening.