Rhodes, Deborah J.

PURPOSE To determine the sensitivity and specificity of genetic testing criteria for the detection of germline pathogenic variants in women with breast cancer. MATERIALS AND METHODS Women with breast cancer enrolled in a breast cancer registry at a tertiary cancer center between 2000 and 2016 were evaluated for germline pathogenic variants in 9 breast cancer predisposition genes ( ATM , BRCA1, BRCA2, CDH1, CHEK2, NF1, PALB2, PTEN, and TP53). The performance of the National Comprehensive Cancer Network (NCCN) hereditary cancer testing criteria was evaluated relative to testing of all women as recommended by the American Society of Breast Surgeons. RESULTS Of 3,907 women, 1,872 (47.9%) meeting NCCN criteria were more likely to carry a pathogenic variant in 9 predisposition genes compared with women not meeting criteria (9.0% v 3.5%; P < .001). Of those not meeting criteria (n = 2,035), 14 (0.7%) had pathogenic variants in BRCA1 or BRCA2. The sensitivity of NCCN criteria was 70% for 9 predisposition genes and 87% for BRCA1 and BRCA2, with a specificity of 53%. Expansion of the NCCN criteria to include all women diagnosed with breast cancer at ≤ 65 years of age achieved > 90% sensitivity for the 9 predisposition genes and > 98% sensitivity for BRCA1 and BRCA2. CONCLUSION A substantial proportion of women with breast cancer carrying germline pathogenic variants in predisposition genes do not qualify for testing by NCCN criteria. Expansion of NCCN criteria to include all women diagnosed at ≤ 65 years of age improves the sensitivity of the selection criteria without requiring testing of all women with breast cancer.

AbstractObjectiveWe evaluated the accuracy of molecular breast imaging (MBI)—a nuclear medicine technique that employs dedicated dual-detector, cadmium zinc telluride gamma cameras to image the functional uptake of a radiopharmaceutical (typically Tc-99m sestamibi) in the breast—in patients with suspicious calcifications on mammography.MethodsWomen scheduled for stereotactic biopsy of calcifications detected on 2D digital mammography were prospectively enrolled to undergo MBI before biopsy. Molecular breast imaging was performed with injection of Tc-99m sestamibi and a dual-detector, cadmium zinc telluride gamma camera. Positive findings on either modality were biopsied. High-risk and malignant biopsy findings were excised.ResultsIn 71 participants, 76 areas of calcifications were recommended for biopsy after mammography, and 24 (32%) were malignant, including 20 cases of ductal carcinoma in situ (DCIS) and 4 cases of invasive ductal cancer. Prebiopsy MBI was positive in 17 of the 76 (22%) calcifications, including 10 of 20 (50%) DCISs and 2 of 4 (50%) invasive cancers. The median pathologic size for MBI–positive cancers was 1.5 cm (range 0.5–3.2 cm) compared with 0.9 cm (range 0.1–2.0 cm) for MBI–negative cancers (P = 0.09).Non-mass uptake on MBI led to additional biopsies of 6 sites in 6 patients, and 2 of 6 (33%) MBI–detected incidental lesions showed malignancy; both DCIS contralateral to the mammographically detected calcifications. The overall per-lesion positive and negative predictive values of MBI in this prebiopsy setting were 61% (14 of 23) and 80% (47 of 59), respectively.ConclusionMolecular breast imaging has insufficient negative predictive value to identify calcifications in which biopsy could be avoided. However, among women presenting for biopsy of suspicious calcifications, MBI revealed additional sites of mammographically occult breast cancer.To avoid biopsy of suspicious calcifications on mammography, negative findings on MBI should not be used.

Abstract Background High mammographic breast density is the primary reason for missed cancers or delayed detection on mammography, and is associated with a higher rate of advanced and interval cancers which increase breast cancer mortality. Digital breast tomosynthesis (DBT) has been shown to reduce false positive findings relative to 2D mammography but does not eliminate the potential for tumor masking in dense breasts due to the similar x-ray attenuation characteristics of tumors and normal fibroglandular tissue. Molecular Breast Imaging (MBI) performed with a dedicated gamma camera to detect functional uptake of a radiotracer, Tc-99m sestamibi, has been shown to reveal breast cancers obscured by density on mammography. In single-institution studies, adding MBI to 2D mammography in women with dense breasts detected an additional 5 to10 invasive cancers per 1000 screened, with modest increases in recall rate (6 to 8%) at a lower cost-per-cancer detected than mammography alone. Despite this promising evidence, the lack of multicenter trial data has limited wider acceptance. Also, MBI has yet to be compared to DBT, which in some centers has replaced 2D mammography screening. We present interim results from a multicenter trial comparing cancer detection rate of DBT and MBI in screening of women with mammographically dense breasts. Methods In this ongoing, prospective, multicenter clinical trial, asymptomatic women aged 40-75 years with dense breasts on prior mammogram and no prior history of supplemental screening are invited to undergo two annual rounds of concurrent DBT and MBI. MBI is performed with injection of 300 MBq Tc-99m sestamibi with a dual-head semiconductor-based gamma camera. Screening tests are interpreted independently. Here, preliminary cancer detection rates (cancers per 1000 women screened), recall rates, and biopsy rates of DBT and MBI for initial screening are reported. Results In 537 women out of a planned 3000 who have completed the first round of screening, 7 cancers were detected: one by DBT only and 6 by MBI only, giving cancer detection rates of 1.9 for DBT vs. 11.2 for MBI and incremental cancer detection rate of 9.3 for MBI. The one DBT-only cancer was a node-negative 0.8 cm invasive lobular carcinoma. All 6 cancers detected by MBI were invasive; 5 of 6 were node negative (median size 1.0 cm; range 0.6 to 2.6 cm). Recall rate was 11% (60/537) for DBT alone; 16% (84/537) for MBI alone, and 21% (115/537) for the combination. Biopsy was prompted by DBT in 13 patients (PPV 8% [1/13]); by MBI in 23 patients (PPV 26% [6/23]); and by the combination of modalities in 33 (PPV 21% [7/33]). Conclusion These preliminary results demonstrate that MBI detects invasive breast cancers occult on DBT in dense breasts. Data from a second screening round will allow calculation of sensitivity and specificity, and determination of the impact of screening MBI in reducing advanced (&gt; 2 cm) and interval cancers. Additional planned analyses will evaluate a denoising algorithm for further reduction in MBI radiation dose to match that of DBT. Citation Format: Rhodes D, Hunt K, Conners A, Zingula S, Whaley D, Ellis R, Gasal Spilde J, Mehta R, Polley M-Y, O'Connor M, Hruska C. Molecular breast imaging and tomosynthesis to eliminate the reservoir of undetected cancer in dense breasts: The Density MATTERS trial [abstract]. In: Proceedings of the 2018 San Antonio Breast Cancer Symposium; 2018 Dec 4-8; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2019;79(4 Suppl):Abstract nr PD4-05.

PURPOSE Background parenchymal uptake (BPU), which describes the level of radiotracer uptake in normal fibroglandular tissue on molecular breast imaging (MBI), has been identified as a breast cancer risk factor. Our objective was to develop and validate a deep learning model using image convolution to automatically categorize BPU on MBI. METHODS MBI examinations obtained for clinical and research purposes from 2004 to 2015 were reviewed to classify the BPU pattern using a standardized five-category scale. Two expert radiologists provided interpretations that were used as the reference standard for modeling. The modeling consisted of training and validating a convolutional neural network to predict BPU. Model performance was summarized in data reserved to test the performance of the algorithm at the per-image and per-breast levels. RESULTS Training was performed on 24,639 images from 3,133 unique patients. The model performance on the withheld testing data (6,172 images; 786 patients) was evaluated. Using direct matching on the predicted classification resulted in an accuracy of 69.4% (95% CI, 67.4% to 71.3%), and if prediction within one category was considered, accuracy increased to 96.0% (95% CI, 95.2% to 96.7%). When considering the breast-level prediction of BPU, the accuracy remained strong, with 70.3% (95% CI, 68.0% to 72.6%) and 96.2% (95% CI, 95.3% to 97.2%) for the direct match and allowance for one category, respectively. CONCLUSION BPU provided a robust target for training a convolutional neural network. A validated computer algorithm will allow for objective, reproducible encoding of BPU to foster its integration into risk-stratification algorithms.

Key Clinical Message This case highlights the role of molecular breast imaging (MBI) in evaluating persistent clinical concerns after a negative diagnostic mammogram and ultrasound. MBI is especially useful in the diagnosis of invasive lobular carcinoma due to its occult nature on conventional imaging modalities.

AbstractObjective: To better understand clinician information needs and learning opportunities by exploring the use of best-practice algorithms across different training levels and specialties.Methods: We developed interactive online algorithms (care process models [CPMs]) that integrate current guidelines, recent evidence, and local expertise to represent cross-disciplinary best practices for managing clinical problems. We reviewed CPM usage logs from January 2014 to June 2015 and compared usage across specialty and provider type.Results: During the study period, 4009 clinicians (2014 physicians in practice, 1117 resident physicians, and 878 nurse practitioners/physician assistants [NP/PAs]) viewed 140 CPMs a total of 81 764 times. Usage varied from 1 to 809 views per person, and from 9 to 4615 views per CPM. Residents and NP/PAs viewed CPMs more often than practicing physicians. Among 2742 users with known specialties, generalists (N = 1397) used CPMs more often (mean 31.8, median 7 views) than specialists (N = 1345; mean 6.8, median 2; P &lt; .0001). The topics used by specialists largely aligned with topics within their specialties. The top 20% of available CPMs (28/140) collectively accounted for 61% of uses. In all, 2106 clinicians (52%) returned to the same CPM more than once (average 7.8 views per topic; median 4, maximum 195). Generalists revisited topics more often than specialists (mean 8.8 vs 5.1 views per topic; P &lt; .0001).Conclusions: CPM usage varied widely across topics, specialties, and individual clinicians. Frequently viewed and recurrently viewed topics might warrant special attention. Specialists usually view topics within their specialty and may have unique information needs.