Faculty Bibliography

PURPOSE/OBJECTIVE:To develop a digital reference object (DRO) toolkit to generate realistic breast DCE-MRI data for quantitative assessment of image reconstruction and data analysis methods. METHODS: RESULTS: CONCLUSION/CONCLUSIONS:We have developed a DRO toolkit that includes realistic morphology of tumor lesions along with the expected pharmacokinetic parameter ranges. This simulation framework can generate many images for quantitative assessment of DCE-MRI reconstruction and analysis methods.

PURPOSE/OBJECTIVE:The impact of opportunistic screening mammography in the United States is difficult to quantify, partially due to lack of inclusion regarding method of detection (MOD) in national registries. This study sought to determine the feasibility of MOD collection in a multicenter community registry and to compare outcomes and characteristics of breast cancer based on MOD. METHODS:We conducted a retrospective study of breast cancer patients from a multicenter tumor registry in Missouri from January 2004 - December 2018. Registry data were extracted by certified tumor registrars and included MOD, clinicopathologic information, and treatment. MOD was assigned as screen-detected or clinically detected. Data were analyzed at the patient level. Chi-squared tests were used for categorical variable comparison and Mann-Whitney-U test was used for numerical variable comparison. RESULTS:5351 women (median age, 63 years; interquartile range, 53-73 years) were included. Screen-detected cancers were smaller than clinically detected cancers (median size 12 mm vs. 25 mm; P < .001) and more likely node-negative (81% vs. 54%; P < .001), lower grade (P < .001), and lower stage (P < .001). Screen-detected cancers were more likely treated with lumpectomy vs. mastectomy (73% vs. 41%; P < .001) and less likely to require chemotherapy (24% vs. 52%; P < .001). Overall survival for patients with invasive breast cancer was higher for screen-detected cancers (89% vs. 74%, P < .0001). CONCLUSION/CONCLUSIONS:MOD can be routinely collected and linked to breast cancer outcomes through tumor registries, with demonstration of significant differences in outcome and characteristics of breast cancers based on MOD. Routine inclusion of MOD in US tumor registries would help quantify the impact of opportunistic screening mammography in the US.

PURPOSE/OBJECTIVE:There are insufficient large-scale studies comparing the performance of screening mammography in women of different races. This study aims to compare the screening performance metrics across racial and age groups in the National Mammography Database (NMD). METHODS:). RESULTS:. CONCLUSIONS:with advancing age. African American women have poorer outcomes from screening mammography (higher RR and lower CDR), compared to White and all women in the NMD. Racial disparity can be partly explained by higher rate of African American women lost to follow up.

3D imaging enables accurate diagnosis by providing spatial information about organ anatomy. However, using 3D images to train AI models is computationally challenging because they consist of 10x or 100x more pixels than their 2D counterparts. To be trained with high-resolution 3D images, convolutional neural networks resort to downsampling them or projecting them to 2D. We propose an effective alternative, a neural network that enables efficient classification of full-resolution 3D medical images. Compared to off-the-shelf convolutional neural networks, our network, 3D Globally-Aware Multiple Instance Classifier (3D-GMIC), uses 77.98%-90.05% less GPU memory and 91.23%-96.02% less computation. While it is trained only with image-level labels, without segmentation labels, it explains its predictions by providing pixel-level saliency maps. On a dataset collected at NYU Langone Health, including 85,526 patients with full-field 2D mammography (FFDM), synthetic 2D mammography, and 3D mammography, 3D-GMIC achieves an AUC of 0.831 (95% CI: 0.769-0.887) in classifying breasts with malignant findings using 3D mammography. This is comparable to the performance of GMIC on FFDM (0.816, 95% CI: 0.737-0.878) and synthetic 2D (0.826, 95% CI: 0.754-0.884), which demonstrates that 3D-GMIC successfully classified large 3D images despite focusing computation on a smaller percentage of its input compared to GMIC. Therefore, 3D-GMIC identifies and utilizes extremely small regions of interest from 3D images consisting of hundreds of millions of pixels, dramatically reducing associated computational challenges. 3D-GMIC generalizes well to BCS-DBT, an external dataset from Duke University Hospital, achieving an AUC of 0.848 (95% CI: 0.798-0.896).

BACKGROUND:Monoexponential apparent diffusion coefficient (ADC) and biexponential intravoxel incoherent motion (IVIM) analysis of diffusion-weighted imaging is helpful in the characterization of breast tumors. However, repeatability/reproducibility studies across scanners and across sites are scarce. PURPOSE/OBJECTIVE:)) within and across sites employing MRI scanners from different vendors utilizing 16-channel breast array coils in a breast diffusion phantom. STUDY TYPE/METHODS:Phantom repeatability. PHANTOM/UNASSIGNED:A breast phantom containing tubes of different polyvinylpyrrolidone (PVP) concentrations, water, fat, and sponge flow chambers, together with an MR-compatible liquid crystal (LC) thermometer. FIELD STRENGTH/SEQUENCE/UNASSIGNED:Bipolar gradient twice-refocused spin echo sequence and monopolar gradient single spin echo sequence at 3 T. ASSESSMENT/RESULTS:Studies were performed twice in each of two scanners, located at different sites, on each of 2 days, resulting in four studies per scanner. ADCs of the PVP and water were normalized to the vendor-provided calibrated values at the temperature indicated by the LC thermometer for repeatability/reproducibility comparisons. STATISTICAL TESTS/METHODS:ADC and IVIM repeatability and reproducibility within and across sites were estimated via the within-system coefficient of variation (wCV). Pearson correlation coefficient (r) was also computed between IVIM metrics and flow speed. A P value <0.05 was considered statistically significant. RESULTS:correlations with flow speed were significant at both sites. DATA CONCLUSION/CONCLUSIONS:. LEVEL OF EVIDENCE/METHODS:2 TECHNICAL EFFICACY: Stage 1.

OBJECTIVE/UNASSIGNED:Given variability in how practices manage patients on antithrombotic medications, we undertook this study to understand the current practice of antithrombotic management for patients undergoing percutaneous breast and axillary procedures. METHODS/UNASSIGNED:A 20-item survey with multiple-choice and write-in options was emailed to 2094 active North American members of the Society of Breast Imaging (SBI) in March 2021. Data were collected anonymously and analyzed quantitatively, with free-text responses categorized by themes. RESULTS/UNASSIGNED: < 0.001). Up to 50.2% (100/199) on warfarin and 33.6% (66/196) on direct oral anticoagulants had medications withheld more stringently than guidelines suggest. CONCLUSION/UNASSIGNED:Based on a survey of SBI members, breast imaging practices vary widely in antithrombotic management for image-guided breast and axillary procedures. Of the 60% who withhold antithrombotic medications, a minority comply with recommended withhold guidelines, placing at least some patients at potential risk for thrombotic events. Breast imaging radiologists should weigh the risks and benefits of withholding these medications, and if they elect to withhold should closely follow evidence-based guidelines to minimize the risks of this practice.