Breast Cancers Detected during a Decade of Screening with Digital Breast Tomosynthesis: Comparison with Digital Mammography.

Background Digital breast tomosynthesis (DBT) has been shown to help increase cancer detection compared with two-dimensional digital mammography (DM). However, it is unclear whether additional tumor detection will improve outcomes or lead to overdiagnosis of breast cancer. Purpose This study aimed to compare cancer types and stages over 3 years of DM screening and 10 years of DBT screening to determine the effect of DBT. Materials and Methods A retrospective search identified breast cancers detected by using screening mammography from August 2008 through July 2021. Data collected included demographic, imaging, and pathologic information. Invasive cancers 2 cm or larger, human epidermal growth factor 2-positive or triple-negative tumors greater than 10 mm, axillary nodes positive for cancer, and distant organ spread were considered advanced cancers. The DBT and DM cohorts were compared and further analyzed by prevalent versus incident examinations. False-negative findings were also assessed. Results A total of 1407 breast cancers were analyzed (142 with DM, 1265 with DBT). DBT showed a higher rate of cancer depiction than DM (5.3 vs four cancers per 1000, respectively; P = .001), with a similar ratio of invasive cancers to ductal carcinomas in situ (76.5%:23.5% [968 and 297 of 1265, respectively] vs 71.1%:28.9% [101 and 41 of 142, respectively]). Mean invasive cancer size did not differ between DM and DBT (1.44 cm ± 0.93 [SD] vs 1.36 cm ± 1.14, respectively; P = .49), but incident DBT cases were smaller than prevalent cases (1.2 cm ± 1.0 vs 1.6 cm ± 1.4, respectively; P < .001). DBT and DM had similar rates of invasive cancer subtypes: low grade (26.5% [243 of 912] vs 29% [28 of 96], respectively), moderate grade (57.2% [522 of 912] vs 51% [49 of 96], respectively), and high grade (16.1% [147 of 912] vs 20% [19 of 96], respectively) (P = .65). The proportion of advanced cancers was lower with DBT than DM (32.6% [316 of 968] vs 43.6% [44 of 101], respectively; P = .04) and between DBT prevalent and incident screening (39.1% [133 of 340] vs 29.1% [183 of 628], respectively; P = .003). There was no difference in interval cancer rates (0.14 per 1000 with DM and 0.2 per 1000 with DBT; P = .42) for both groups. Conclusion DBT helped to increase breast cancer detection rate and depicted invasive cancers with a lower rate of advanced cancers compared with DM, with further improvement observed at incident rounds of screening. © RSNA, 2024 See also the editorial by Kim and Woo in this issue.

NCCN Guidelines® Insights: Breast Cancer Screening and Diagnosis, Version 1.2023.

The NCCN Guidelines for Breast Cancer Screening and Diagnosis provide health care providers with a practical, consistent framework for screening and evaluating a spectrum of clinical presentations and breast lesions. The NCCN Breast Cancer Screening and Diagnosis Panel is composed of a multidisciplinary team of experts in the field, including representation from medical oncology, gynecologic oncology, surgical oncology, internal medicine, family practice, preventive medicine, pathology, diagnostic and interventional radiology, as well as patient advocacy. The NCCN Breast Cancer Screening and Diagnosis Panel meets at least annually to review emerging data and comments from reviewers within their institutions to guide updates to existing recommendations. These NCCN Guidelines Insights summarize the panel's decision-making and discussion surrounding the most recent updates to the guideline's screening recommendations.

PACS-integrated machine learning breast density classifier: clinical validation.

OBJECTIVE: To test the performance of a novel machine learning-based breast density tool. The tool utilizes a convolutional neural network to predict the BI-RADS based density assessment of a study. The clinical density assessments of 33,000 mammographic examinations (164,000 images) from one academic medical center (Site A) were used for training. MATERIALS AND METHODS: This was an IRB approved HIPAA compliant study performed at two academic medical centers. The validation data set was composed of 500 studies from one site (Site A) and 700 from another (Site B). At Site A, each study was assessed by three breast radiologists and the majority (consensus) assessment was used as truth. At Site B, if the tool agreed with the clinical reading, then it was considered to have correctly predicted the clinical reading. In cases where the tool and the clinical reading disagreed, then the study was evaluated by three radiologists and the consensus reading was used as the clinical reading. RESULTS: For the classification into the four categories of the Breast Imaging Reporting and Data System (BI-RADS®), the AI classifier had an accuracy of 84.6% at Site A and 89.7% at Site B. For binary classification (dense vs. non-dense), the AI classifier had an accuracy of 94.4% at Site A and 97.4% at Site B. In no case did the classifier disagree with the consensus reading by more than one category. CONCLUSIONS: The automated breast density tool showed high agreement with radiologists' assessments of breast density.

Mammographic Screening in Older Women: When Is It Time to Stop?

Mammographic screening guidelines in women aged 75 and older are inconsistent due to a lack of data from prospective randomized controlled trials, such as those that exist for women between 40-74 years of age. In addition, older women are perceived as less likely to benefit from early detection due to increased comorbidities and a greater proportion of biologically favorable cancers. With increasing life expectancy and quality of life in the elderly, the question of when to stop mammographic screening merits renewed discussion. Observational data support a survival benefit from regular screening in older women with no severe comorbidities. In addition, screening mammography in this age group has been shown to perform better than in younger age groups, tipping the balance toward greater benefits than harms. Early studies of digital breast tomosynthesis (DBT) in older women suggest that performance metrics are further improved with DBT screening. While a biennial schedule in older women preserves some of the benefit of screening, annual mammography achieves the greatest reductions in breast cancer mortality and morbidity. As the medical community strives to offer personalized care for all age groups, health care providers are well positioned to offer shared decision-making based on existing data and tailored to each woman's individual risk profile, comorbid conditions, and personal values.

Digital Breast Tomosynthesis: What Have We Learned?

Digital breast tomosynthesis (DBT) is increasingly recognized as a superior breast imaging technology compared with 2D digital mammography (DM) alone. Accumulating data confirm increased sensitivity and specificity in the screening setting, resulting in higher cancer detection rates and lower abnormal interpretation (recall) rates. In the diagnostic environment, DBT simplifies the diagnostic work-up and improves diagnostic accuracy. Initial concern about increased radiation exposure resulting from the DBT acquisition added onto a 2D mammogram has been largely alleviated by the development of synthesized 2D mammography (SM). Continued research is underway to reduce artifacts associated with SM, and improve its comparability to DM. Breast cancers detected with DBT are most often small invasive carcinomas with a preponderance for grade 1 histology and luminal A molecular characteristics. Recent data suggest that higher-grade cancers are also more often node negative when detected with DBT. A meta-analysis of early single-institution studies of the effect of DBT on interval cancers has shown a modest decrease when multiple data sets are combined. Because of the greater conspicuity of lesions on DBT imaging, detection of subtle architectural distortion is increased. Such findings include both spiculated invasive carcinomas and benign etiologies such as radial scars. The diagnostic evaluation of architectural distortion seen only with DBT can pose a challenge. When no sonographic correlate can be identified, DBT-guided biopsy and/or localization capability is essential. Initial experience with DBT-guided procedures suggests that DBT biopsy equipment may improve the efficiency of percutaneous breast biopsy with less radiation.

Breast Cancer Screening and Diagnosis, Version 3.2018, NCCN Clinical Practice Guidelines in Oncology.

The NCCN Guidelines for Breast Cancer Screening and Diagnosis have been developed to facilitate clinical decision making. This manuscript discusses the diagnostic evaluation of individuals with suspected breast cancer due to either abnormal imaging and/or physical findings. For breast cancer screening recommendations, please see the full guidelines on NCCN.org.

Advances in Digital Breast Tomosynthesis.

OBJECTIVE: Digital breast tomosynthesis (DBT) has rapidly emerged as an important new imaging tool that reduces the masking effect of overlapping fibroglandular tissue, thereby improving breast cancer detection. This article will review key features of DBT including technique, clinical implementation, and benign and malignant imaging findings. We will also present the benefits of DBT in screening, diagnostic workup, and image-guided biopsy. CONCLUSION: Tomosynthesis improves interpretive performance and will likely replace conventional 2D mammography in clinical practice.

Knowledge of Density and Screening Ultrasound.

To determine breast density awareness and attitudes regarding supplemental breast ultrasound screening since implementation of the nation's first breast density notification law, Connecticut Public Act 09-41. A self-administered survey was distributed at a Connecticut academic breast imaging center between February 2013 and February 2014. Women with prior mammography reports describing heterogeneous or extremely dense breast tissue were invited to participate when presenting for screening mammography, screening ultrasound, or both. Data were collected on breast density awareness, history of prior ultrasounds, attitudes toward ultrasound and breast-cancer risk, and demographics. Data were collected from 950 completed surveys. The majority of surveyed women (92%) were aware of their breast density, and 77% had undergone a prior screening ultrasound. Forty-three percent of participants who were aware of their breast density also expressed increased anxiety about developing breast cancer due to having dense breast tissue. Caucasian race and higher education were significantly associated (p < 0.05) with knowledge of personal breast density (93% and 95%, respectively) and having a prior screening breast ultrasound (79% and 80%, respectively). Patients with less than a college degree (82%) were significantly more likely to rely exclusively on their provider's recommendation regarding obtaining screening ultrasound (p < 0.05). Breast density awareness is strongly associated with higher education, higher income, and Caucasian race. Non-Caucasian patients and those with less than a college education rely more heavily on their physicians' recommendations regarding screening ultrasound. Among women aware of their increased breast density, nearly half reported associated increased anxiety regarding the possibility of developing breast cancer.

Oncologic Imaging in Patients Undergoing Breast Reduction.

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