Full Field Digital Mammography (FFDM) versus CMOS Technology versus Tomosynthesis (DBT) - Which System Increases the Quality of Intraoperative Imaging?

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Aim: This prospective clinical study aimed to evaluate whether it would be possible to reduce the rate of re-excisions using CMOS technology, a specimen radiography system (SRS) or digital breast tomosynthesis (DBT) compared to a conventional full field digital mammography (FFDM) system. Material and Method: Between 12/2012 and 2/ 2013 50 patients were diagnosed with invasive breast cancer (BI-RADS™ 5). After histological verification, all patients underwent breast-conserving therapy with intraoperative imaging using 4 different systems and differing magnifications: 1.

supporting

confidence: 85%

Full Field Digital Mammography (FFDM) versus CMOS Technology, Specimen Radiography System (SRS) and Tomosynthesis (DBT) - Which System Can Optimise Surgical Therapy?

Schulz‐Wendtland

Dilbat

Bani

et al. 2013

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“…It has been hypothesized that the absolute dense area (DA) is an indicator of breast cancer risk as well, because a higher amount of dense breast tissue could directly correlate to a higher probability of one of the cells within the dense area to progress to a malig-nant cell. Furthermore DA has not been as strongly associated with BMI, thus maybe providing some additional information about breast cancer risk, that is more independent from BMI [21,22]. Therefore the aim of our study was to assess the percent mammographic density as a risk factor in a recent German case-control study for breast cancer and to assess whether breast cancer risk can be described more accurately by adding the measurement of the dense area to the prediction model.…”

mentioning

confidence: 99%

Percent Mammographic Density and Dense Area as Risk Factors for Breast Cancer

Rauh

Hack

Häberle

et al. 2012

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!Purpose: Mammographic characteristics are known to be correlated to breast cancer risk. Percent mammographic density (PMD), as assessed by computer-assisted methods, is an established risk factor for breast cancer. Along with this assessment the absolute dense area (DA) of the breast is reported as well. Aim of this study was to assess the predictive value of DA concerning breast cancer risk in addition to other risk factors and in addition to PMD. Methods: We conducted a case control study with hospital-based patients with a diagnosis of invasive breast cancer and healthy women as controls. A total of 561 patients and 376 controls with available mammographic density were included into this study. We describe the differences concerning the common risk factors BMI, parital status, use of hormone replacement therapy (HRT) and menopause between cases and controls and estimate the odds ratios for PMD and DA, adjusted for the mentioned risk factors. Furthermore we compare the prediction models with each other to find out whether the addition of DA improves the model. Results: Mammographic density and DA were highly correlated with each other. Both variables were as well correlated to the commonly known risk factors with an expected direction and strength, however PMD (ρ = −0.56) was stronger correlated to BMI than DA (ρ = −0.11). The group of women within the highest quartil of PMD had an OR of 2.12 (95 % CI: 1.25-3.62). This could not be seen for the fourth quartile concerning DA. However the assessment of breast cancer risk could be improved by including DA in a prediction model in addition to common risk factors and PMD.

“…two observersʼ values for percentage mammographic density (PMD) was used for this analysis, into which only measurements of contralateral cranio-caudal (CC) images were included [36,37].…”

Section: Mammographic Density Measuresmentioning

confidence: 99%

Mammographic Density and Prediction of Nodal Status in Breast Cancer Patients

Hack

Häberle

Geisler

et al. 2013

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!Aim: Nodal status remains one of the most important prognostic factors in breast cancer. The cellular and molecular reasons for the spread of tumor cells to the lymph nodes are not well understood and there are only few predictors in addition to tumor size and multifocality that give an insight into additional mechanisms of lymphatic spread. Aim of our study was therefore to investigate whether breast characteristics such as mammographic density (MD) add to the predictive value of the presence of lymph node metastases in patients with primary breast cancer. Methods: In this retrospective study we analyzed primary, metastasis-free breast cancer patients from one breast center for whom data on MD and staging information were available. A total of 1831 patients were included into this study. MD was assessed as percentage MD (PMD) using a semiautomated method and two readers for every patient. Multiple logistic regression analyses with nodal status as outcome were used to investigate the predictive value of PMD in addition to age, tumor size, Ki-67, estrogen receptor (ER), progesterone receptor (PR), grading, histology, and multi-focality. Results: Multifocality, tumor size, Ki-67 and grading were relevant predictors for nodal status. Adding PMD to a prediction model which included these factors did not significantly improve the prediction of nodal status (p = 0.24, likelihood ratio test). Conclusion: Nodal status could be predicted quite well with the factors multifocality, tumor size, Ki-67 and grading. PMD does not seem to play a role in the lymphatic spread of tumor cells. It could be concluded that the amount of extracellular matrix and stromal cell content of the breast which is reflected by MD does not influence the probability of malignant breast cells spreading from the primary tumor to the lymph nodes. Zusammenfassung