Tomosynthesis improves breast cancer detection: our experience.

Breast tomosynthesis (BT) is a novel imaging technology in which an x-ray fan beam sweeps in an arc across the breast, producing tomographic images and it can reduce tissue overlap encountered in conventional two-dimensional (2D) and thus has the potential to improve detection of breast cancer and facilitate accurate differentiation of lesion types. The purpose of this article was to assess the positive predictive value (PPV) of breast cancer with BT versus full-field digital mammography (FFDM) and the assessment of detec- tion of both techniques in the present series.

Quantitative assessment of breast mammographic density with a new objective method.

Women with increased mammographic density (MD) have an increased risk of developing breast cancer. The purpose of our study is to evaluate an experimental method to quantify MD using a program (compatible with Windows XP, Vista and 7) which measures black areas as 0, white areas as 100 and grey scale areas with intermediate values between 0 and 100, depending on the "density" of the area. Digital screening mammograms were directly estimated with this method. Initial idea and steps of the program were based on a Mac utility used by our research team.

Preliminary results of objective assessment of mammographic percent density.

Breast density assessments performed by using the Breast Imaging Reporting and Data System (BI-RADS) have been completely qualitative and the American College of Radiology (ACR) fibroglandular density descriptors are mainly subjective. However, women with increased mammographic density (MD) have an increased risk of developing breast cancer. The purpose of our study was to evaluate an experimental method to quantify MD using a software utility which measures absolutely black areas as zero and absolutely white areas as 100. In grey scale areas, these values range between 0 and 100, depending on the "density" of the area. Digital screening mammograms were directly estimated with this method. We concluded that there is a significant correlation between ACR quartiles and this grey scale percentage method, although several improvements on the original idea are planned.

Maximizing the benefits of screening mammography for women 40-49 years old.

BACKGROUND: While women aged 50 and older are broadly considered to benefit from screening mammograms, the evidence of any similar advantages for younger women are still considered insufficient to form any substantial conclusions on the matter. The primary goal of this study was to examine whether or not the mortality rate of younger women is benefited by mammography, and if so, how can this beneficial effect be maximized. METHODS: The authors have taken into account all available randomized control trials (RCTs) and have conducted a meta-analysis based on those RCTs to study the effect of mammography on the mortality rate of women younger than age 50. Further interpretation on various aspects of the results has also led to separate meta-analyses, with the RCTs included grouped in accordance to the mean time interval between screening mammograms employed by each study. The findings and conclusions of the comparison were used to calculate the number of mammograms necessary to reduce the absolute death risk, depending on the time interval between screening mammograms. RESULTS: The meta-analysis indicated a reduction in breast-cancer mortality in the intervention group, which reached statistical significance (relative risk (RR) 0.81 [95% CI 0.71-0.93] p < 0.01). Furthermore, when the RCTs included were grouped according to their mean time interval between mammograms, there was a definite increase of statistical significance in favor of those RCTs with shorter interval times (RR 0.76 [95% CI 0.64-0.89] p < 0.01). CONCLUSIONS: The significant mortality rate reduction demonstrated by the meta-analytical results is a key indicator of the beneficial effect of mammography on the age group of women younger than 50. Additionally, the increase in the aforesaid significance when combining RCTs with short time intervals between mammograms, as opposed to those RCTs with longer intervals, suggests that the optimal use of mammographic screening lies with the former. This is better demonstrated when taking in account our approach to answering the practical question of "how many screening mammograms will take to save one life?" in correlation with the mean time interval involved.