Radioactive seed localization of foreign body.

Radioactive seed localization is a method widely used within breast cancer treatment. This case represents a 43-year-old male patient with a foreign body in his left axilla. We used radioactive seed localization for marking the foreign body, which made the subsequent surgery possible, quick, and minimal invasive.

Risk stratification of women with false-positive test results in mammography screening based on mammographic morphology and density: A case control study.

BACKGROUND: The long-term risk of breast cancer is increased in women with false-positive (FP) mammography screening results. We investigated whether mammographic morphology and/or density can be used to stratify these women according to their risk of future breast cancer METHODS: We undertook a case-control study nested in the population-based screening programme in Copenhagen, Denmark. We included 288 cases and 288 controls based on a cohort of 4743 women with at least one FP-test result in 1991-2005 who were followed up until 17 April 2008. Film-based mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, the Tabár classification, and two automated techniques quantifying percentage mammographic density (PMD) and mammographic texture (MTR), respectively. The association with breast cancer was estimated using binary logistic regression calculating Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs) adjusted for birth year and age and invitation round at the FP-screen RESULTS: Significantly increased ORs were seen for BI-RADS D(density)2-D4 (OR 1.94; 1.30-2.91, 2.36; 1.51-3.70 and 4.01; 1.67-9.62, respectively), Tabár's P(pattern)IV (OR 1.83; 1.16-2.89), PMD Q(quartile)2-Q4 (OR 1.71; 1.02-2.88, 1.97; 1.16-3.35 and 2.43; 1.41-4.19, respectively) and MTR Q4 (1.97; 1.12-3.46) using the lowest/fattiest category as reference CONCLUSION: All four methods, capturing either mammographic morphology or density, could segregate women with FP-screening results according to their risk of future breast cancer - using already available screening mammograms. Our findings need validation on digital mammograms, but may inform potential future risk stratification and tailored screening strategies.

Mammographic density and structural features can individually and jointly contribute to breast cancer risk assessment in mammography screening: a case-control study.

BACKGROUND: Mammographic density is a well-established risk factor for breast cancer. We investigated the association between three different methods of measuring density or parenchymal pattern/texture on digitized film-based mammograms, and examined to what extent textural features independently and jointly with density can improve the ability to identify screening women at increased risk of breast cancer. METHODS: The study included 121 cases and 259 age- and time matched controls based on a cohort of 14,736 women with negative screening mammograms from a population-based screening programme in Denmark in 2007 (followed until 31 December 2010). Mammograms were assessed using the Breast Imaging-Reporting and Data System (BI-RADS) density classification, Tabár's classification on parenchymal patterns and a fully automated texture quantification technique. The individual and combined association with breast cancer was estimated using binary logistic regression to calculate Odds Ratios (ORs) and the area under the receiver operating characteristic (ROC) curves (AUCs). RESULTS: Cases showed significantly higher BI-RADS and texture scores on average than controls (p < 0.001). All three methods were individually able to segregate women into different risk groups showing significant ORs for BI-RADS D3 and D4 (OR: 2.37; 1.32-4.25 and 3.93; 1.88-8.20), Tabár's PIII and PIV (OR: 3.23; 1.20-8.75 and 4.40; 2.31-8.38), and the highest quartile of the texture score (3.04; 1.63-5.67). AUCs for BI-RADS, Tabár and the texture scores (continuous) were 0.63 (0.57-0-69), 0.65 (0.59-0-71) and 0.63 (0.57-0-69), respectively. Combining two or more methods increased model fit in all combinations, demonstrating the highest AUC of 0.69 (0.63-0.74) when all three methods were combined (a significant increase from standard BI-RADS alone). CONCLUSION: Our findings suggest that the (relative) amount of fibroglandular tissue (density) and mammographic structural features (texture/parenchymal pattern) jointly can improve risk segregation of screening women, using information already available from normal screening routine, in respect to future personalized screening strategies.

Inter-observer agreement according to three methods of evaluating mammographic density and parenchymal pattern in a case control study: impact on relative risk of breast cancer.

BACKGROUND: Mammographic breast density and parenchymal patterns are well-established risk factors for breast cancer. We aimed to report inter-observer agreement on three different subjective ways of assessing mammographic density and parenchymal pattern, and secondarily to examine what potential impact reproducibility has on relative risk estimates of breast cancer. METHODS: This retrospective case-control study included 122 cases and 262 age- and time matched controls (765 breasts) based on a 2007 screening cohort of 14,736 women with negative screening mammograms from Bispebjerg Hospital, Copenhagen. Digitised randomized film-based mammograms were classified independently by two readers according to two radiological visual classifications (BI-RADS and Tabár) and a computerized interactive threshold technique measuring area-based percent mammographic density (denoted PMD). Kappa statistics, Intraclass Correlation Coefficient (ICC) (equivalent to weighted kappa), Pearson's linear correlation coefficient and limits-of-agreement analysis were used to evaluate inter-observer agreement. High/low-risk agreement was also determined by defining the following categories as high-risk: BI-RADS's D3 and D4, Tabár's PIV and PV and the upper two quartiles (within density range) of PMD. The relative risk of breast cancer was estimated using logistic regression to calculate odds ratios (ORs) adjusted for age, which were compared between the two readers. RESULTS: Substantial inter-observer agreement was seen for BI-RADS and Tabár (κ=0.68 and 0.64) and agreement was almost perfect when ICC was calculated for the ordinal BI-RADS scale (ICC=0.88) and the continuous PMD measure (ICC=0.93). The two readers judged 5% (PMD), 10% (Tabár) and 13% (BI-RADS) of the women to different high/low-risk categories, respectively. Inter-reader variability showed different impact on the relative risk of breast cancer estimated by the two readers on a multiple-category scale, however, not on a high/low-risk scale. Tabár's pattern IV demonstrated the highest ORs of all density patterns investigated. CONCLUSIONS: Our study shows the Tabár classification has comparable inter-observer reproducibility with well tested density methods, and confirms the association between Tabár's PIV and breast cancer. In spite of comparable high inter-observer agreement for all three methods, impact on ORs for breast cancer seems to differ according to the density scale used. Automated computerized techniques are needed to fully overcome the impact of subjectivity.