Assessing breast cancer risk within the general screening population: developing a breast cancer risk model to identify higher risk women at mammographic screening.

OBJECTIVES: To develop a breast cancer risk model to identify women at mammographic screening who are at higher risk of breast cancer within the general screening population. METHODS: This retrospective nested case-control study used data from a population-based breast screening program (2009-2015). All women aged 40-75 diagnosed with screen-detected or interval breast cancer (n = 1882) were frequency-matched 3:1 on age and screen-year with women without screen-detected breast cancer (n = 5888). Image-derived risk factors from the screening mammogram (percent mammographic density [PMD], breast volume, age) were combined with core biopsy history, first-degree family history, and other clinical risk factors in risk models. Model performance was assessed using the area under the receiver operating characteristic curve (AUC). Classifiers assigning women to low- versus high-risk deciles were derived from risk models. Agreement between classifiers was assessed using a weighted kappa. RESULTS: The AUC was 0.597 for a risk model including only image-derived risk factors. The successive addition of core biopsy and family history significantly improved performance (AUC = 0.660, p < 0.001 and AUC = 0.664, p = 0.04, respectively). Adding the three remaining risk factors did not further improve performance (AUC = 0.665, p = 0.45). There was almost perfect agreement (kappa = 0.97) between risk assessments based on a classifier derived from image-derived risk factors, core biopsy, and family history compared with those derived from a model including all available risk factors. CONCLUSIONS: Women in the general screening population can be risk-stratified at time of screen using a simple model based on age, PMD, breast volume, and biopsy and family history. KEY POINTS: • A breast cancer risk model based on three image-derived risk factors as well as core biopsy and first-degree family history can provide current risk estimates at time of screen. • Risk estimates generated from a combination of image-derived risk factors, core biopsy history, and first-degree family history may be more valid than risk estimates that rely on extensive self-reported risk factors. • A simple breast cancer risk model can avoid extensive clinical risk factor data collection.

Breast density scales: the metric matters.

OBJECTIVE: Measures of percent mammographic density (PMD) are often categorized using various density scales. The purpose of this study was to examine information loss associated with the use of categorical density scales. METHODS: Baseline PMD was assessed at 1% precision for 2,374 females. The data were used to create 21-category, 4-category and 2-category density scales. R-squared and root mean square error were used to evaluate the effect of categorizing PMD. The area under the receiver operator characteristic curves were compared between cancer risk models employing solely categorical PMD scales and solely baseline PMD for a subset of females (424 cases, 848 controls). RESULTS: R-squared value decreased from 1.00 (1% PMD) to 0.56 (2-category scale), while root mean square error increased from 0.00 (1% PMD) to 10.83 (2-category scale). The area under the receiver operator characteristic curve decreased from 0.64 for a cancer risk model using 1% PMD to 0.58 for a risk model using a 21-category density scale (p < 0.0001), 0.55 for a 4-category Breast Imaging, Reporting and Data System-like scale (p < 0.0001) and 0.50 for a 2-category Breast Imaging, Reporting and Data System-like scale (high vs low) (p < 0.0001). CONCLUSION: Categorizing PMD measures into categorical density scales leads to a significant loss of information. Indeed, a simple high versus low split of PMD using a 50% cut point yields a cancer risk model with no discriminatory power. Advances in knowledge: Use of categorical mammographic density scales rather than continuous percent mammographic density measures leads to significant loss of information. Breast cancer risk models using categorical mammographic density scales perform more poorly than models using continuous PMD measures.

Consistency of visual assessments of mammographic breast density from vendor-specific "for presentation" images.

Discussions of percent breast density (PD) and breast cancer risk implicitly assume that visual assessments of PD are comparable between vendors despite differences in technology and display algorithms. This study examines the extent to which visual assessments of PD differ between mammograms acquired from two vendors. Pairs of "for presentation" digital mammography images were obtained from two mammography units for 146 women who had a screening mammogram on one vendor unit followed by a diagnostic mammogram on a different vendor unit. Four radiologists independently visually assessed PD from single left mediolateral oblique view images from the two vendors. Analysis of variance, intra-class correlation coefficients (ICC), scatter plots, and Bland-Altman plots were used to evaluate PD assessments between vendors. The mean radiologist PD for each image was used as a consensus PD measure. Overall agreement of the PD assessments was excellent between the two vendors with an ICC of 0.95 (95% confidence interval: 0.93 to 0.97). Bland-Altman plots demonstrated narrow upper and lower limits of agreement between the vendors with only a small bias (2.3 percentage points). The results of this study support the assumption that visual assessment of PD is consistent across mammography vendors despite vendor-specific appearances of "for presentation" images.

Utility of relative and absolute measures of mammographic density vs clinical risk factors in evaluating breast cancer risk at time of screening mammography.

OBJECTIVE: Various clinical risk factors, including high breast density, have been shown to be associated with breast cancer. The utility of using relative and absolute area-based breast density-related measures was evaluated as an alternative to clinical risk factors in cancer risk assessment at the time of screening mammography. METHODS: Contralateral mediolateral oblique digital mammography images from 392 females with unilateral breast cancer and 817 age-matched controls were analysed. Information on clinical risk factors was obtained from the provincial breast-imaging information system. Breast density-related measures were assessed using a fully automated breast density measurement software. Multivariable logistic regression was conducted, and area under the receiver-operating characteristic (AUROC) curve was used to evaluate the performance of three cancer risk models: the first using only clinical risk factors, the second using only density-related measures and the third using both clinical risk factors and density-related measures. RESULTS: The risk factor-based model generated an AUROC of 0.535, while the model including only breast density-related measures generated a significantly higher AUROC of 0.622 (p < 0.001). The third combined model generated an AUROC of 0.632 and performed significantly better than the risk factor model (p < 0.001) but not the density-related measures model (p = 0.097). CONCLUSION: Density-related measures from screening mammograms at the time of screen may be superior predictors of cancer compared with clinical risk factors. ADVANCES IN KNOWLEDGE: Breast cancer risk models based on density-related measures alone can outperform risk models based on clinical factors. Such models may support the development of personalized breast-screening protocols.

Benign and Malignant Male Breast Diseases: Radiologic and Pathologic Correlation.

Male breast disease comprises a wide spectrum of benign and malignant processes. We present the spectrum of diseases encountered at our institution over the past 7 years (2007-2013) and correlate their radiological and histopathological appearances. Gynaecomastia is the most frequently encountered disease due to its association with a variety of causes. Male breast malignancies, though rare, must be considered. The most frequently encountered pathological characteristic is invasive and the predominant histologic subtypes are infiltrating ductal carcinomas.

Atypical Femoral Fractures: A Teaching Perspective.

This article provides an overview of atypical femoral fractures with a highlight on their radiographic findings. Potent antiresorptive agents such as bisphosphonates or denosumab have been associated with the development of such fractures. However, at this time, a causal association has not been conclusively established. Atypical femoral fractures are insufficiency fractures, which frequently present with bone pain. Early identification of characteristic radiographic features and withdrawal of antiresorptive therapy may prevent the development of completed atypical femoral fractures.

Ten years of breast screening in the Nova Scotia Breast Screening Program, 1991-2001. experience: use of an adaptable stereotactic device in the diagnosis of screening-detected abnormalities.

OBJECTIVE: To evaluate and present 10-year outcomes of the Nova Scotia Breast Screening Program (NSBSP), a population-based screening program in the province of Nova Scotia, Canada, total population 900 000. SETTING: Organized Breast Screening Program in Nova Scotia, Canada. METHODS: Rates of participation, abnormal referrals, cancer detection rates, and benign:malignant (B:M) rates for core biopsy and surgical biopsy were calculated for asymptomatic women receiving a mammogram through the NSBSP 1991-2001. RESULTS: Of 192 454 mammograms performed on 71 317 women, 33% were aged 40 to 49 years, 39% aged 50 to 59 years, 23% aged 60 to 69 years, and 5% aged 70 years and over. Cancer detection rate increased in each age group respectively: 3.7, 5.8, 9.7, and 13.5 per 1000 population on first-time screens. The positive predictive value of an abnormal screen increased with increasing age groups. Benign breast surgery decreased with increased use of needle core breast biopsy (NCBB). Open surgery decreased from 25 to 6 surgeries per 1000 screens. Of 1519 open surgical procedures (1328 women), 878 cancers were removed, with 37% 10 mm or less, and 61% 15 mm or less. In 613 women in whom the node status was assessed, 79% were negative. CONCLUSION: A quality screening program incorporating NCBB in the diagnostic work-up is effective in the early detection of breast cancer and results in less open surgery, particularly in younger women.

Technology review: the use of electrical impedance scanning in the detection of breast cancer.

The present paper focuses on electrical impedance scanning. The basic science behind the new modality, measurements of breast tissue impedance in vivo and in vitro, and the studies performed with a newly available commercial machine are discussed. Electrical impedance scanning has been generating interest for several reasons, including comfort to the patient, the relatively low cost, and studies suggest that it may be effective in detecting disease in mammographically dense breasts.

Quantitative assessment of myocardial ischemia by electrocardiographic and scintigraphic imaging.

We calculated distributions of epicardial potentials from body-surface electrocardiograms (ECGs) recorded during controlled myocardial ischemia and compared them with scintigraphic estimates of ischemia's extent/severity. The study population consisted of patients suffering from single-vessel coronary artery disease, referred for elective percutaneous transluminal coronary angioplasty of either the left anterior descending (n=7), the right coronary (n=9), or the left circumflex (n=2) artery. After the target vessel had been dilated, a 1960s "study" inflation was performed with a non-perfusion-type balloon catheter; at its commencement, technetium-99m sestamibi was injected via a femoral-vein catheter, and ECGs were recorded throughout the inflation from 120 leads. Single photon emission computed tomographic imaging was performed one hour after the injection of radionuclide to obtain an "occlusion image", and again one hour after a repeat injection 24 hours later to obtain a "control image"; the latter image was subtracted from the former, to derive a scintigraphic difference map (Delta map). The ECGs were signal-averaged over a 10-s window at preinflation and peak-inflation states, the preinflation averaged complexes were subtracted from the peak-inflation ones to produce body-surface Delta maps, and the corresponding Delta maps of epicardial potentials were calculated by applying the electrocardiographic inverse solution; this procedure is referred to as electrocardiographic imaging. The ECG-derived epicardial Delta maps related spatially to the scintigraphic Delta maps in all patients. The percent areas and surface integrals of positive values in ECG-derived Delta maps were found to be very good single-variable predictors of the extent (r=0.73; p=0.0006) and severity (r=0.72; p=0.0008) of the scintigraphically-estimated perfusion defect; a regression equation using two ECG-derived predictors further improved the agreement with scintigraphic estimates (r=0.81; p=0.0004 for estimates of severity). These findings suggest that noninvasive electrocardiographic imaging might provide quantitative estimates of the extent/severity of myocardial ischemia that agree closely with those provided by scintigraphic techniques.