Breast Imaging Reporting and Data System

Berg, Wendie A.; Campassi, C; Langenberg, Patricia; Sexton, Mary

doi:10.2214/ajr.174.6.1741769

Cited by 477 publications

(93 citation statements)

References 29 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…The moderate inter-reader agreement for the morphology and distribution of microcalcifications seen in this study has previously been described for mammography [14] and tomosynthesis [3]. We found that this also holds true for INSIGHT3D without significant differences with respect to SM or the standard stack reconstruction.…”

Section: Discussionsupporting

confidence: 84%

Multiple Angulated Mammography Reconstructions in Digital Breast Tomosynthesis for the Diagnosis of Microcalcifications – Added Value to Standard Stack Reconstructions and Synthesized Mammography

Neubauer

Wicklein

et al. 2018

Fortschr Röntgenstr

View full text Add to dashboard Cite

ZUSAMMENFASSUNGZweck Vergleich der Bildqualitätsbewertungen, diagnostischen Genauigkeit und Läsionscharakterisierung von synthetischer Mammografie (SM), mehrfach angulierten Mammografierekonstruktionen (INSIGHT3D) und StandardSchicht-Rekonstruktionen für Mikroverkalkungen in der digitalen Brust-Tomosynthese. This document was downloaded for personal use only. Unauthorized distribution is strictly prohibited. Materialen und Methoden ABSTR AC TPurpose To compare ratings regarding the depiction, diagnostic accuracy and lesion characterization of conventional synthesized mammography (SM), multiple angulated mammography reconstructions (INSIGHT3D), and standard stack reconstructions in digital breast tomosynthesis for microcalcifications.Materials and Methods This is a retrospective, multicase, multireader study. We included patients with digital breast tomosynthesis (DBT), microcalcifications and histology over a period of four months in our institution and the same number of normal cases. Three radiologists, who were blinded to patient data, independently rated the depiction, distribution, morphology and BI-RADS score of microcalcifications in SM, INSIGHT3D and standard stack reconstructions. Deidentified images were presented in random order. Reading time was measured. Friedman and post hoc Nemenyi tests, Cochrane's Q and post hoc Wilcoxon signed rank tests, Fleiss' kappa and receiver operating characteristics were used for statistical analysis.Results We included 41 histopathologically proven and 41 normal cases. Depiction of microcalcifications was rated better in INSIGHT3D than in SM and better in stack reconstructions than in INSIGHT3D and SM (P < 0.001). The reading time was lower in SM and INSIGHT3D compared to stack reconstructions (P < 0.001). The diagnostic accuracy and inter-rater correlation were comparable between all tested modes of reconstruction.Conclusions INSIGHT3D has higher ratings regarding the depiction of microcalcifications compared to SM while maintaining a short reading time. Our preliminary assessment suggests that INSIGHT3D provides added value to SM. Fortschr Röntgenstr 2018; 190: 433-440

show abstract

Section: Discussionsupporting

confidence: 84%

Multiple Angulated Mammography Reconstructions in Digital Breast Tomosynthesis for the Diagnosis of Microcalcifications – Added Value to Standard Stack Reconstructions and Synthesized Mammography

Neubauer

Wicklein

et al. 2018

Fortschr Röntgenstr

View full text Add to dashboard Cite

show abstract

“…At the present time, this classification is a primarily subjective estimate of quartiles from almost entirely fat, to extremely dense. There is marked inter observer variability between radiologists (28, 29), raising concern for integrating this information into clinical use.…”

Section: Automated Breast Densitymentioning

confidence: 99%

Beyond Mammography: New Frontiers in Breast Cancer Screening

Drukteinis

Mooney

Flowers

et al. 2013

The American Journal of Medicine

179

109

View full text Add to dashboard Cite

Breast cancer screening remains a subject of intense and, at times, passionate debate. Mammography has long been the mainstay of breast cancer detection and is the only screening test proven to reduce mortality. Although it remains the gold standard of breast cancer screening, there is increasing awareness of subpopulations of women for whom mammography has reduced sensitivity. Mammography has also undergone increased scrutiny for false positives and excessive biopsies, which increase radiation dose, cost and patient anxiety. In response to these challenges, new technologies for breast cancer screening have been developed, including; low dose mammography; contrast enhanced mammography, tomosynthesis, automated whole breast ultrasound, molecular imaging and MRI. Here we examine some of the current controversies and promising new technologies that may improve detection of breast cancer both in the general population and in high-risk groups, such as women with dense breasts. We propose that optimal breast cancer screening will ultimately require a personalized approach based on metrics of cancer risk with selective application of specific screening technologies best suited to the individual’s age, risk, and breast density.

show abstract

“…16, 30 Subjectively rating mammographic density based on the BIRADS standard is often not accurate or reliable due to the large intra- and inter-reader variability. 3 In addition, many useful mammographic density features, such as tissue spiculation patterns and bilateral asymmetry cannot be quantitatively evaluated and compared using subjective (visual) assessment.…”

Section: Introductionmentioning

confidence: 99%

Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk

Tan

Cheng

et al. 2015

Ann Biomed Eng

View full text Add to dashboard Cite

The purpose of this study was to develop and assess a new quantitative four-view mammographic image feature based fusion model to predict the near-term breast cancer risk of the individual women after a negative screening mammography examination of interest. The dataset included fully-anonymized mammograms acquired on 870 women with two sequential full-field digital mammography (FFDM) examinations. For each woman, the first “prior” examination in the series was interpreted as negative (not recalled) during the original image reading. In the second “current” examination, 430 women were diagnosed with pathology verified cancers and 440 remained negative (“cancer-free”). For each of four bilateral craniocaudal and mediolateral oblique view images of left and right breasts, we computed and analyzed eight groups of global mammographic texture and tissue density image features. A risk prediction model based on three artificial neural networks was developed to fuse image features computed from two bilateral views of four images. The risk model performance was tested using a ten-fold cross-validation method and a number of performance evaluation indices including the area under the receiver operating characteristic curve (AUC) and odds ratio (OR). The highest AUC = 0.725±0.026 was obtained when the model was trained by gray-level run length statistics (RLS) texture features computed on dense breast regions, which was significantly higher than the AUC values achieved using the model trained by only two bilateral one-view images (p < 0.02). The adjustable OR values monotonically increased from 1.0 to 11.8 as model-generated risk score increases. The regression analysis of OR values also showed a significant increase trend in slope (p < 0.01). As a result, this preliminary study demonstrated that a new four-view mammographic image feature based risk model could provide useful and supplementary image information to help predict the near-term breast cancer risk.

show abstract

Breast Imaging Reporting and Data System

Abstract: Inter- and intraobserver variability in mammographic interpretation is substantial for both feature analysis and management. Continued development of methods to improve standardization in mammographic interpretation is needed.

Cited by 477 publications

References 29 publications

Multiple Angulated Mammography Reconstructions in Digital Breast Tomosynthesis for the Diagnosis of Microcalcifications – Added Value to Standard Stack Reconstructions and Synthesized Mammography

Multiple Angulated Mammography Reconstructions in Digital Breast Tomosynthesis for the Diagnosis of Microcalcifications – Added Value to Standard Stack Reconstructions and Synthesized Mammography

Beyond Mammography: New Frontiers in Breast Cancer Screening

Assessment of a Four-View Mammographic Image Feature Based Fusion Model to Predict Near-Term Breast Cancer Risk

Contact Info

Product

Resources

About