Automated measurement of volumetric mammographic density: a tool for widespread breast cancer risk assessment.

INTRODUCTION: Mammographic density is a strong risk factor for breast cancer and an important determinant of screening sensitivity, but its clinical utility is hampered due to the lack of objective and automated measures. We evaluated the performance of a fully automated volumetric method (Volpara). METHODS: A prospective cohort study included 41,102 women attending mammography screening, of whom 206 were diagnosed with breast cancer after a median follow-up of 15.2 months. Percent and absolute dense volumes were estimated from raw digital mammograms. Genotyping was performed in a subset of the cohort (N = 2,122). We examined the agreement by side and view and compared density distributions across different mammography systems. We also studied associations with established density determinants and breast cancer risk. RESULTS: The method showed good agreement by side and view, and distributions of percent and absolute dense volume were similar across mammography systems. Volumetric density was positively associated with nulliparity, age at first birth, hormone use, benign breast disease, and family history of breast cancer, and negatively with age and postmenopausal status. Associations were also observed with rs10995190 in the ZNF365 gene (P < 1.0 × 10(-6)) and breast cancer risk [HR for the highest vs. lowest quartile, 2.93; 95% confidence interval, 1.73-4.96 and 1.63 (1.10-2.42) for percent and absolute dense volume, respectively]. CONCLUSIONS: In a high-throughput setting, Volpara performs well and in accordance with the behavior of established density measures. IMPACT: Automated measurement of volumetric mammographic density is a promising tool for widespread breast cancer risk assessment.

High-throughput mammographic-density measurement: a tool for risk prediction of breast cancer.

INTRODUCTION: Mammographic density (MD) is a strong, independent risk factor for breast cancer, but measuring MD is time consuming and reader dependent. Objective MD measurement in a high-throughput fashion would enable its wider use as a biomarker for breast cancer. We use a public domain image-processing software for the fully automated analysis of MD and penalized regression to construct a measure that mimics a well-established semiautomated measure (Cumulus). We also describe measures that incorporate additional features of mammographic images for improving the risk associations of MD and breast cancer risk. METHODS: We randomly partitioned our dataset into a training set for model building (733 cases, 748 controls) and a test set for model assessment (765 cases, 747 controls). The Pearson product-moment correlation coefficient (r) was used to compare the MD measurements by Cumulus and our automated measure, which mimics Cumulus. The likelihood ratio test was used to validate the performance of logistic regression models for breast cancer risk, which included our measure capturing additional information in mammographic images. RESULTS: We observed a high correlation between the Cumulus measure and our measure mimicking Cumulus (r = 0.884; 95% CI, 0.872 to 0.894) in an external test set. Adding a variable, which includes extra information to percentage density, significantly improved the fit of the logistic regression model of breast cancer risk (P = 0.0002). CONCLUSIONS: Our results demonstrate the potential to facilitate the integration of mammographic density measurements into large-scale research studies and subsequently into clinical practice.

Digital versus screen-film mammography: a retrospective comparison in a population-based screening program.

BACKGROUND: Digital radiography has several advantages over screen-film radiography in data storage and retrieval, making it an attractive alternative to screen-film radiography in screening mammography programs, if it performs as well. METHODS: We retrospectively compared screen-film mammography, photon-counting direct radiography, and computed radiography with population-based screening data from the Breast Unit at Helsingborg Hospital, Sweden, collected between January 2000 and February 2005. Outcomes were cancer detection rates, recall rates, and positive predictive values for breast cancer detection in women reappearing for screening. RESULTS: Data were available for 52,172 two-view mammography examinations of 24,875 women. No initial screening (prevalence) examinations were included. Cancer detection rates based on mammographic findings were 0.31% (81/25,901) for film, 0.49% (48/9841) for photon-counting, and 0.38% (63/16,430) for computed radiography. The recall rate for film was 1.4%, which was significantly higher than that for PC-DR (1.0%; P<0.001) and computed radiography (1.0%; P<0.001). The positive predictive value was lower for film (22%) than for photon-counting (47%; P<0.001) and computed radiography (39%; P<0.001). In addition, the average glandular dose was 1.1mGy for film, 0.28mGy for photon-counting and 0.92mGy for computed radiography. Thus, photon-counting provided a 75% dose reduction, and computed radiography a 16% dose reduction, over film. CONCLUSIONS: Digital radiography, especially photon-counting, performs as well as or better than screen-film radiography. Given the advantages related to improved data storage and communication, digital radiography seems to be a valid alternative to screen-film radiography.

Average glandular dose in routine mammography screening using a Sectra MicroDose Mammography unit.

The Sectra MicroDose Mammography system is based on direct photon counting (with a solid-state detector), and a substantially lower dose to the breast than when using conventional systems can be expected. In this work absorbed dose measurements have been performed for the first unit used in routine mammography screening (at the Hospital of Helsingborg, Sweden). Two European protocols on dosimetry in mammography have been followed. Measurement of half value layer (HVL) cannot be performed as prescribed, but this study has demonstrated that non-invasive measurements of HVL can be performed accurately with a sensitive and well collimated solid-state detector with simultaneous correction for the energy dependence. The average glandular dose for a 50 mm standard breast with 50% glandularity, simulated by 45 mm polymethylmethacrylate, was found to be 0.21 and 0.28 mGy in March and December 2004, respectively. These values are much lower than for any other mammography system on the market today. It has to be stressed that the measurements were made using the current clinical settings and that no systematic optimisation of the relationship between absorbed dose and diagnostic image quality has been performed within the present study. In order to further increase the accuracy of absorbed dose measurements for this unit, the existing dose protocols should be revised to account also for the tungsten/aluminium anode/filter combination, the multi-slit pre-collimator device and the occurrence of a dose profile in the scanning direction.