Faculty Bibliography

PURPOSE/OBJECTIVE:Sodium MRI has shown promise for monitoring neoadjuvant chemotherapy response in breast cancer. The purpose of this work was to build a dual-tuned bilateral proton/sodium breast coil for 7T MRI that provides sufficient SNR to enable sodium breast imaging in less than 10 minutes. METHODS:The proton/sodium coil consists of 2 shielded unilateral units: 1 for each breast. Each unit consists of 3 nested layers: (1) a 3-loop solenoid for sodium excitation, (2) a 3-loop solenoid for proton excitation and signal reception, and (3) a 4-channel receive array for sodium signal reception. Benchmark measurements were performed in phantoms with and without the sodium receive array insert. In vivo images were acquired on a healthy volunteer. RESULTS:The sodium receive array boosted 1.5 to 3 times the SNR compared with the solenoid. Proton SNR loss due to residual interaction with the sodium array was less than 10%. The coil enabled sodium imaging in vivo with 2.8-mm isotropic nominal resolution (~5-mm real resolution) in 9:36 minutes. CONCLUSION/CONCLUSIONS:The coil design that we propose addresses challenges associated with sodium's low SNR from a hardware perspective and offers the opportunity to investigate noninvasively breast tumor metabolism as a function of sodium concentration in patients undergoing neoadjuvant chemotherapy.

Deep learning models designed for visual classification tasks on natural images have become prevalent in medical image analysis. However, medical images differ from typical natural images in many ways, such as significantly higher resolutions and smaller regions of interest. Moreover, both the global structure and local details play important roles in medical image analysis tasks. To address these unique properties of medical images, we propose a neural network that is able to classify breast cancer lesions utilizing information from both a global saliency map and multiple local patches. The proposed model outperforms the ResNet-based baseline and achieves radiologist-level performance in the interpretation of screening mammography. Although our model is trained only with image-level labels, it is able to generate pixel-level saliency maps that provide localization of possible malignant findings.

Although computer-aided diagnosis (CAD) is widely used in mammography, conventional CAD programs that use prompts to indicate potential cancers on the mammograms have not led to an improvement in diagnostic accuracy. Because of the advances in machine learning, especially with use of deep (multilayered) convolutional neural networks, artificial intelligence has undergone a transformation that has improved the quality of the predictions of the models. Recently, such deep learning algorithms have been applied to mammography and digital breast tomosynthesis (DBT). In this review, the authors explain how deep learning works in the context of mammography and DBT and define the important technical challenges. Subsequently, they discuss the current status and future perspectives of artificial intelligence-based clinical applications for mammography, DBT, and radiomics. Available algorithms are advanced and approach the performance of radiologists-especially for cancer detection and risk prediction at mammography. However, clinical validation is largely lacking, and it is not clear how the power of deep learning should be used to optimize practice. Further development of deep learning models is necessary for DBT, and this requires collection of larger databases. It is expected that deep learning will eventually have an important role in DBT, including the generation of synthetic images.

Background Male breast cancer incidence is rising. There may be a potential role in selective screening in men at elevated risk for breast cancer, but the effectiveness of such screening remains unexplored. Purpose To evaluate patterns of male breast imaging utilization, to determine high-risk screening outcomes, and to delineate risk factors associated with cancer diagnosis. Materials and Methods This retrospective study reviewed consecutive male breast imaging examinations over a 12-year period (between 2005-2017). Examination indications, biopsy recommendations, and pathologic results were correlated with patient characteristics. Fisher exact test, Mann-Whitney test, Spearman correlation, and logistic regression were used for statistical analysis. Results A total of 1869 men (median age, 55 years; range, 18-96 years) underwent 2052 examinations yielding 2304 breast lesions and resulting in 149 (6.5%) biopsies in 133 men; 41 (27.5%) were malignant and 108 (72.5%) were benign. There were 1781 (86.8%) diagnostic and 271 (13.2%) screening examinations. All men undergoing screening had personal or family history of breast cancer and/or genetic mutations. There was a significant increase in the number of examinations in men relative to the number of examinations in women over time (Spearman correlation, r = 0.85; P < .001). Five node-negative cancers resulted from screening mammography, yielding a cancer detection rate of 18 per 1000 examinations (95% confidence interval [CI]: 7, 41), with cancers diagnosed on average after 4 person-years of screening (range, 1-10 person-years). Mammographic screening sensitivity, specificity, and positive predictive value of biopsy were 100% (95% CI: 50%, 100%), 95.0% (95% CI: 93.1%, 98%), and 50% (95% CI: 22.2%, 77.8%). Older age (P < .001), Ashkenazi descent (P < .001), genetic mutations (P = .006), personal history (P < .001), and first-degree family history (P = .03) were associated with breast cancer. Non-first-degree family history was not associated with cancer (P = .09). Conclusion There is potential benefit in screening men at high risk for developing breast cancer. Such screening may have increased over time. © RSNA, 2019.

Background Although previous studies have focused on rural disparities in the use of screening mammography, city-level use throughout the United States has not been well evaluated even though more than 30 million women live in the 500 largest cities. Purpose To evaluate disparities in the city-level use of screening mammography and to identify factors that have an impact on screening utilization. Materials and Methods This retrospective study used data from large publicly available databases, the American Community Survey and Robert Wood Johnson Foundation 500 Cities Project, which includes screening mammography utilization data from the Behavioral Risk Factor Surveillance System. Databases were searched from January to March 2018. The use of screening mammography was evaluated at the city level by census region and division by using the Mann-Whitney U test. Univariable Spearman rank correlation and multivariable regression analysis were performed to determine the impact of factors on screening use, including population size, health-related variables (use of Papanicolaou test, obesity), income variables (median household income, poverty status, health insurance), and race. Results Overall mean city-level screening mammography use rate was 77.7% (range, 62.8%-88.9%). The highest mean utilization occurred in coastal cities, with the highest overall utilization in the New England area (82.7%). The lowest utilization rate was in Mountain states (73.6%). City-level utilization showed a positive correlation with Papanicolaou test use (r = 0.75, P < .001), median household income (r = 0.44, P < .001), and percentage Asian population (r = 0.38, P < .001) and a negative correlation with obesity (r = -0.36, P < .001), the lack of health insurance (r = -0.44, P < .001), and poverty (r = -0.30, P < .001). Multivariable analysis showed the strongest independent predictors of utilization to be percentage of women screened with the Papanicolaou test, Asian race, private insurance, and census division (R² = 68%). Conclusion Disparities in the utilization of preventive health care services exist at the large city level, with the highest use in New England cities and lowest in Mountain cities. Predictors of higher than average utilization include census division and percentage of inhabitants who are up to date with the Papanicolaou test, are of Asian race, and have private insurance. © RSNA, 2019.

Multiple studies in the first decade of the 21^st century have established contrast-enhanced breast MRI as a screening modality for women with a hereditary or familial increased risk for the development of breast cancer. In recent studies, in women with various risk profiles, the sensitivity ranges between 81% and 100%, which is approximately twice as high as the sensitivity of mammography. The specificity increases in follow-up rounds to around 97%, with positive predictive values for biopsy in the same range as for mammography. MRI preferentially detects the more aggressive/invasive types of breast cancer, but has a higher sensitivity than mammography for any type of cancer. This performance implies that in women screened with breast MRI, all other examinations must be regarded as supplemental. Mammography may yield ~5% additional cancers, mostly ductal carcinoma in situ, while slightly decreasing specificity and increasing the costs. Ultrasound has no supplemental value when MRI is used. Evidence is mounting that in other groups of women the performance of MRI is likewise superior to more conventional screening techniques. Particularly in women with a personal history of breast cancer, the gain seems to be high, but also in women with a biopsy history of lobular carcinoma in situ and even women at average risk, similar results are reported. Initial outcome studies show that breast MRI detects cancer earlier, which induces a stage-shift increasing the survival benefit of screening. Cost-effectiveness is still an issue, particularly for women at lower risk. Since costs of the MRI scan itself are a driving factor, efforts to reduce these costs are essential. The use of abbreviated MRI protocols may enable more widespread use of breast MRI for screening. Level of Evidence: 1 Technical Efficacy: Stage 5 J. Magn. Reson. Imaging 2019.

MRI of the breast has the highest sensitivity for breast cancer detection among current clinical imaging modalities and is indispensable for breast imaging practice. While the basis of breast MRI consists of T1-weighted contrast-enhanced imaging, T2-weighted, ultrafast, and diffusion-weighted imaging may be used to improve lesion characterization. Such multiparametric assessment of breast lesions allows for excellent discrimination between benign and malignant breast lesions. Indications for breast MRI are expanding. In preoperative staging, multiple studies confirm the superiority of MRI to other imaging modalities for tumor size estimation and detection of additional tumor foci in the ipsilateral and contralateral breast. Ongoing studies show that in experienced hands this can be used to improve breast cancer surgery, although there is no evidence of improved long-term outcomes. Screening indications are likewise growing as evidence is accumulating that OncologicRI depicts cancers at an earlier stage than mammography in all women. To manage the associated costs for screening, the use of abbreviated protocols may be beneficial. In patients treated with neoadjuvant chemotherapy, MRI is used to document response. It is essential to realize that oncologic and surgical response are different, and evaluation should be adapted to the underlying question.

PURPOSE/OBJECTIVE:To assess the association of fatty acid levels in mammary adipose tissue of postmenopausal women with the presence of breast cancer using the Gradient-echo Spectroscopic Imaging (GSI). MATERIALS AND METHODS/METHODS:test, one-way analysis of variance (ANOVA) with Tukey-Kramer multiple comparison tests, and linear regression. RESULTS:Postmenopausal women with malignancies had significantly higher SFA (0.336 ± 0.038) in mammary adipose tissue compared to those with benign disease (0.283 ± 0.046, p = 0.0008) and to those with a history of breast cancer (0.287 ± 0.050, p = 0.0038). Postmenopausal women with malignant lesions had significantly lower MUFA (0.352 ± 0.041) compared to those with benign disease (0.401 ± 0.043, p = 0.0032) and with history of breast cancer (0.388 ± 0.055, p = 0.0484). The history of cancer group had a significant correlation (r = 0.60, p = 0.006) between SFA and BMI, and the cancer group had a significant correlation (r = 0.57, p = 0.010) between PUFA and BMI. CONCLUSIONS:Fatty acid composition of mammary adipose tissue, particularly higher SFA and lower MUFA, may be associated with breast cancer. The GSI method utilizes an automated voxel-based analysis to measure fatty acid composition, and may be used to assess the role of mammary adipose tissue in cancer development and progress.

MRI of the breast is the most sensitive test for breast cancer detection and outperforms conventional imaging with mammography, digital breast tomosynthesis, or ultrasound. However, the long scan time and relatively high costs limit its widespread use. Hence, it is currently only routinely implemented in the screening of women at an increased risk of breast cancer. To overcome these limitations, abbreviated dynamic contrast-enhanced (DCE)-MRI protocols have been introduced that substantially shorten image acquisition and interpretation time while maintaining a high diagnostic accuracy. Efforts to develop abbreviated MRI protocols reflect the increasing scrutiny of the disproportionate contribution of radiology to the rising overall healthcare expenditures. Healthcare policy makers are now focusing on curbing the use of advanced imaging examinations such as MRI while continuing to promote the quality and appropriateness of imaging. An important cornerstone of value-based healthcare defines value as the patient's outcome over costs. Therefore, the concept of a fast, abbreviated MRI exam is very appealing, given its high diagnostic accuracy coupled with the possibility of a marked reduction in the cost of an MRI examination. Given recent concerns about gadolinium-based contrast agents, unenhanced MRI techniques such as diffusion-weighted imaging (DWI) are also being investigated for breast cancer diagnosis. Although further larger prospective studies, standardized imaging protocol, and reproducibility studies are necessary, initial results with abbreviated MRI protocols suggest that it seems feasible to offer screening breast DCE-MRI to a broader population. This article aims to give an overview of abbreviated and fast breast MRI protocols, their utility for breast cancer detection, and their emerging role in the new value-based healthcare paradigm that has replaced the fee-for-service model.

Contrast-enhanced breast MRI is a standard evidence-based component of supplemental screening in conjunction with mammography for higher-risk populations because of its high sensitivity for detecting breast cancer; the use of breast MRI for screening in high-risk populations is recommended in multiple national and international guidelines. The current MRI exam, however, is expensive relative to other screening technologies such as mammography, and relatively more time-intensive. Recent investigations have focused on techniques that have the potential for improving efficiency of the breast MRI exam, decreasing acquisition and reading times, without impacting diagnostic accuracy. The purpose of this article is therefore to provide an overview of current MRI guidelines for screening for breast cancer and to discuss evolving technological approaches to breast MRI, in particular abbreviated and ultrafast MRI protocols, as well as MRI protocols without contrast that have the potential to improve MRI screening. Level of Evidence: 5 Technical Efficacy Stage: 2 J. Magn. Reson. Imaging 2019.