Breast density measurements with ultrasound tomography: A comparison with film and digital mammography

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/134902/1/mp2057.pd

Mammographic density. Measurement of mammographic density

Mammographic density has been strongly associated with increased risk of breast cancer. Furthermore, density is inversely correlated with the accuracy of mammography and, therefore, a measurement of density conveys information about the difficulty of detecting cancer in a mammogram. Initial methods for assessing mammographic density were entirely subjective and qualitative; however, in the past few years methods have been developed to provide more objective and quantitative density measurements. Research is now underway to create and validate techniques for volumetric measurement of density. It is also possible to measure breast density with other imaging modalities, such as ultrasound and MRI, which do not require the use of ionizing radiation and may, therefore, be more suitable for use in young women or where it is desirable to perform measurements more frequently. In this article, the techniques for measurement of density are reviewed and some consideration is given to their strengths and limitations

Clinical and epidemiological issues and applications of mammographic density

The copyright of this thesis rests with the author and no quotation from it or information derived from it may be published without the prior written consent of the authorMammographic density, the amount of radiodense tissue on a mammogram, is a strong risk factor for breast cancer, with properties that could be an asset in screening and prevention programmes. Its use in risk prediction contexts is currently limited, however, mainly due to di culties in measuring and interpreting density. This research investigates rstly, the properties of density as an independent marker of breast cancer risk and secondly, how density should be measured. The rst question was addressed by analysing data from a chemoprevention trial, a trial of hormonal treatment, and a cohort study of women with a family history of breast cancer . Tamoxifen-induced density reduction was observed to be a good predictor of breast cancer risk reduction in high-risk una ected subjects. Density and its changes did not predict risk or treatment outcome in subjects with a primary invasive breast tumour. Finally absolute density predicted risk better than percent density and showed a potential to improve existing risk-prediction models, even in a population at enhanced familial risk of breast cancer. The second part of thesis focuses on density measurement and in particular evaluates two fully-automated volumetric methods, Quantra and Volpara. These two methods are highly correlated and in both cases absolute density (cm3) discriminated cases from controls better than percent density. Finally, we evaluated and compared di erent measurement methods. Our ndings suggested good reliability of the Cumulus and visual assessments. Quantra volumetric estimates appeared negligibly a ected by measurement error, but were less variable than visual bi-dimensional ones, a ecting their ability to discriminate cases from controls. Overall, visual assessments showed the strongest association with breast cancer risk in comparison to computerised methods. Our research supports the hypothesis that density should have a role in personalising screening programs and risk management. Volumetric density measuring methods, though promising, could be improved.Cancer Research U

Diagnostic Reference Levels for digital mammography in Australia

Aims: In 3 phases, this thesis explores: radiation doses delivered to women during mammography, methods to estimate mean glandular dose (MGD), and the use of mammographic breast density (MBD) in MGD calculations. Firstly, it examines Diagnostic reference levels (DRLs) for digital mammography in Australia, with novel focus on the use of compressed breast thickness (CBT) and detector technologies as a guide when determining patient derived DRLs. Secondly, it analyses the agreement between Organ Dose estimated by different digital mammography units and calculated MGD for clinical data. Thirdly, it explores the novel use of MBD in MGD calculations, suggesting a new dose estimation called the actual glandular dose (AGD), and compares MGD to AGD. Methods: DICOM headers were extracted from 52405 anonymised mammograms using 3rd party software. Exposure and QA information were utilised to calculate MGD using 3 methods. LIBRA software was used to estimate MBD for 31097 mammograms. Median, 75th and 95th percentiles were calculated across MGDs obtained for all included data and according to 9 CBT ranges, average population CBT, and for 3 detector technologies. The significance of the differences, correlations, and agreement between MGDs for different CBT ranges, calculation methods, and different density estimation methods were analysed. Conclusions: This thesis have recommended DRLs for mammography in Australia, it shows that MGD is dependent upon CBT and detector technology, hence DRLs were presented as a table for different CBTs and detectors. The work also shows that Organ Doses reported by vendors vary from that calculated using established methodologies. Data produced also show that the use of MGD calculated using standardised glandularities underestimates dose at lower CBTs compared to AGD by up to 10%, hence, underestimating radiation risk. Finally, AGD was proposed; it considers differences in breast composition for individualised radiation-induced risk assessment

The Role Of Tissue Sound Speed As A Surrogate Marker Of Breast Density

Breast density is one of the strongest predictors of breast cancer risk as women with the densest breasts have a three- to five-fold increase in risk compared to women with the least dense breasts. Breast density is currently measured by using mammography, the current gold standard for breast imaging. There are many shortcomings to using mammography to measure breast density, including the use of ionizing radiation. Ultrasound tomography (UST) does not use ionizing radiation and can create tomographic breast sound speed images. These sound speed images are useful because breast density is proportional to sound speed. The purpose of this work was to assess the ability of UST to measure breast density and its ability to measure changes in breast density over short periods of time. A cohort of 251 patients was examined using both UST and mammography. Many different associations were found between the UST density measurement, the volume averaged sound speed, and the mammographic percent density. Additional associations were found between many other UST and mammographic imaging characteristics. UST density was found to correlate with various patient characteristics in a similar manner to mammographic density. Additionally, UST was used to examine the effects of tamoxifen on breast density. Tamoxifen has been shown to reduce mammographic density and breast cancer risk for some women. Preliminary data for 52 patients has shown promising results so far. UST density has decreased for approximately a similar percentage of patients as has been measured for mammographic density. These changes have been measured over short time frames that could not be achieved using mammography. These results show that UST\u27s ability to measure breast density is consistent with mammography, the current standard of care. UST has the potential to become a safe and effective device that can be used to reliably assess breast density and serial changes in breast density

Comparison of fully and semi-automated area-based methods for measuring mammographic density and predicting breast cancer risk.

BACKGROUND: Mammographic density is a strong risk factor for breast cancer but the lack of valid fully automated methods for quantifying it has precluded its use in clinical and screening settings. We compared the performance of a recently developed automated approach, based on the public domain ImageJ programme, to the well-established semi-automated Cumulus method. METHODS: We undertook a case-control study within the intervention arm of the Age Trial, in which ∼54,000 British women were offered annual mammography at ages 40-49 years. A total of 299 breast cancer cases diagnosed during follow-up and 422 matched (on screening centre, date of birth and dates of screenings) controls were included. Medio-lateral oblique (MLO) images taken closest to age 41 and at least one year before the index case's diagnosis were digitised for each participant. Cumulus readings were performed in the left MLO and ImageJ-based readings in both left and right MLOs. Conditional logistic regression was used to examine density-breast cancer associations. RESULTS: The association between density readings taken from one single MLO and breast cancer risk was weaker for the ImageJ-based method than for Cumulus (age-body mass index-adjusted odds ratio (OR) per one s.d. increase in percent density (95% CI): 1.52 (1.24-1.86) and 1.61 (1.33-1.94), respectively). The ImageJ-based density-cancer association strengthened when the mean of left-right MLO readings was used: OR=1.61 (1.31-1.98). CONCLUSIONS: The mean of left-right MLO readings yielded by the ImageJ-based method was as strong a predictor of risk as Cumulus readings from a single MLO image. The ImageJ-based method, using the mean of two measurements, is a valid automated alternative to Cumulus for measuring density in analogue films