149 research outputs found

    Joint Registration and Limited-Angle Reconstruction of Digital Breast Tomosynthesis

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    Digital breast tomosynthesis (DBT), an emerging imaging modality, provides a pseudo-3D image of the breast. Algorithms to aid the human observer process these large datasets involve two key tasks: reconstruction and registration. Previous studies separated these steps, solving each task independently. This can be effective if reconstructing using a complete set of data, e.g., in cone beam CT, assuming that only simple deformations exist. However, for ill-posed limited-angle problems such as DBT, estimating the deformation is complicated by the significant artefacts associated with DBT reconstructions, leading to severe inaccuracies in the registration. In this paper, we present an innovative algorithm, which combines reconstruction of a pair of temporal DBT acquisitions with their simultaneous registration. Using various computational phantoms and in vivo DBT simulations, we show that, compared to the conventional sequential method, jointly estimating image intensities and transformation parameters gives superior results with respect to reconstruction fidelity and registration accuracy

    Mammography Facility Characteristics Associated With Interpretive Accuracy of Screening Mammography

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    BackgroundAlthough interpretive performance varies substantially among radiologists, such variation has not been examined among mammography facilities. Understanding sources of facility variation could become a foundation for improving interpretive performance.MethodsIn this cross-sectional study conducted between 1996 and 2002, we surveyed 53 facilities to evaluate associations between facility structure, interpretive process characteristics, and interpretive performance of screening mammography (ie, sensitivity, specificity, positive predictive value [PPV1], and the likelihood of cancer among women who were referred for biopsy [PPV2]). Measures of interpretive performance were ascertained prospectively from mammography interpretations and cancer data collected by the Breast Cancer Surveillance Consortium. Logistic regression and receiver operating characteristic (ROC) curve analyses estimated the association between facility characteristics and mammography interpretive performance or accuracy (area under the ROC curve [AUC]). All P values were two-sided.ResultsOf the 53 eligible facilities, data on 44 could be analyzed. These 44 facilities accounted for 484 463 screening mammograms performed on 237 669 women, of whom 2686 were diagnosed with breast cancer during follow-up. Among the 44 facilities, mean sensitivity was 79.6% (95% confidence interval [CI] = 74.3% to 84.9%), mean specificity was 90.2% (95% CI = 88.3% to 92.0%), mean PPV1 was 4.1% (95% CI = 3.5% to 4.7%), and mean PPV2 was 38.8% (95% CI = 32.6% to 45.0%). The facilities varied statistically significantly in specificity (P < .001), PPV1 (P < .001), and PPV2 (P = .002) but not in sensitivity (P = .99). AUC was higher among facilities that offered screening mammograms alone vs those that offered screening and diagnostic mammograms (0.943 vs 0.911, P = .006), had a breast imaging specialist interpreting mammograms vs not (0.932 vs 0.905, P = .004), did not perform double reading vs independent double reading vs consensus double reading (0.925 vs 0.915 vs 0.887, P = .034), or conducted audit reviews two or more times per year vs annually vs at an unknown frequency (0.929 vs 0.904 vs 0.900, P = .018).ConclusionMammography interpretive performance varies statistically significantly by facility

    Breast cancer risk factors in relation to breast density (United States)

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    OBJECTIVES: Evaluate known breast cancer risk factors in relation to breast density. METHODS: We examined factors in relation to breast density in 144,018 New Hampshire (NH) women with at least one mammogram recorded in a statewide mammography registry. Mammographic breast density was measured by radiologists using the BI-RADS classification; risk factors of interest were obtained from patient intake forms and questionnaires. RESULTS: Initial analyses showed a strong inverse influence of age and body mass index (BMI) on breast density. In addition, women with late age at menarche, late age at first birth, premenopausal women, and those currently using hormone therapy (HT) tended to have higher breast density, while those with greater parity tended to have less dense breasts. Analyses stratified on age and BMI suggested interactions, which were formally assessed in a multivariable model. The impact of current HT use, relative to nonuse, differed across age groups, with an inverse association in younger women, and a positive association in older women (p < 0.0001 for the interaction). The positive effects of age at menarche and age at first birth, and the inverse influence of parity were less apparent in women with low BMI than in those with high BMI (p = 0.04, p < 0.0001 and p = 0.01, respectively, for the interactions). We also noted stronger positive effects for age at first birth in postmenopausal women (p = 0.004 for the interaction). The multivariable model indicated a slight positive influence of family history of breast cancer. CONCLUSIONS: The influence of age at menarche and reproductive factors on breast density is less evident in women with high BMI. Density is reduced in young women using HT, but increased in HT users of age 50 or more
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