Volpara Density Research Articles

Breast Cancer Risk and Mammographic Density Assessed with Semiautomated and Fully Automated Methods and BI-RADS.

Purpose To compare three metrics of breast density on full-field digital mammographic (FFDM) images as predictors of future breast cancer risk. Materials and Methods This institutional review board-approved study included 125 women with invasive breast cancer and 274 age- and race-matched control subjects who underwent screening FFDM during 2004-2013 and provided informed consent. The percentage of density and dense area were assessed semiautomatically with software (Cumulus 4.0; University of Toronto, Toronto, Canada), and volumetric percentage of density and dense volume were assessed automatically with software (Volpara; Volpara Solutions, Wellington, New Zealand). Clinical Breast Imaging Reporting and Data System (BI-RADS) classifications of breast density were extracted from mammography reports. Odds ratios and 95% confidence intervals (CIs) were estimated by using conditional logistic regression stratified according to age and race and adjusted for body mass index, parity, and menopausal status, and the area under the receiver operating characteristic curve (AUC) was computed. Results The adjusted odds ratios and 95% CIs for each standard deviation increment of the percentage of density, dense area, volumetric percentage of density, and dense volume were 1.61 (95% CI: 1.19, 2.19), 1.49 (95% CI: 1.15, 1.92), 1.54 (95% CI: 1.12, 2.10), and 1.41 (95% CI: 1.11, 1.80), respectively. Odds ratios for women with extremely dense breasts compared with those with scattered areas of fibroglandular density were 2.06 (95% CI: 0.85, 4.97) and 2.05 (95% CI: 0.90, 4.64) for BI-RADS and Volpara density classifications, respectively. Clinical BI-RADS was more accurate (AUC, 0.68; 95% CI: 0.63, 0.74) than Volpara (AUC, 0.64; 95% CI: 0.58, 0.70) and continuous measures of percentage of density (AUC, 0.66; 95% CI: 0.60, 0.72), dense area (AUC, 0.66; 95% CI: 0.60, 0.72), volumetric percentage of density (AUC, 0.64; 95% CI: 0.58, 0.70), and density volume (AUC, 0.65; 95% CI: 0.59, 0.71), although the AUC differences were not statistically significant. Conclusion Mammographic density on FFDM images was positively associated with breast cancer risk by using the computer assisted methods and BI-RADS. BI-RADS classification was as accurate as computer-assisted methods for discrimination of patients from control subjects. © RSNA, 2016.

Impact of errors in recorded compressed breast thickness measurements on volumetric density classification using volpara v1.5.0 software.

Mammographic density has been demonstrated to predict breast cancer risk. It has been proposed that it could be used for stratifying screening pathways and recommending additional imaging. Volumetric density tools use the recorded compressed breast thickness (CBT) of the breast measured at the x-ray unit in their calculation; however, the accuracy of the recorded thickness can vary. The aim of this study was to investigate whether inaccuracies in recorded CBT impact upon volumetric density classification and to examine whether the current quality control (QC) standard is sufficient for assessing mammographic density. Raw data from 52 digital screening mammograms were included in the study. For each image, the clinically recorded CBT was artificially increased and decreased in increments of 1 mm to simulate measurement error, until ±15% from the recorded CBT was reached. New images were created for each 1 mm step in thickness resulting in a total of 974 images which then had volpara density grade (VDG) and volumetric density percentage assigned. A change in VDG was observed in 38.5% (n = 20) of mammograms when applying ±15% error to the recorded CBT and 11.5% (n = 6) was within the QC standard prescribed error of ±5 mm. The current QC standard of ±5 mm error in recorded CBT creates the potential for error in mammographic density measurement. This may lead to inaccurate classification of mammographic density. The current QC standard for assessing mammographic density should be reconsidered.

Inter-observer variability in mammographic density assessmentusing Royal Australian and New Zealand College ofRadiologists (RANZCR) synoptic scales.

The aim of this study was to evaluate observer variability in mammographic density assessment as measured using the Royal Australian and New Zealand College of Radiologists (RANZCR) synoptic scales. Visual assessment of mammographic density by radiologists is commonly used in clinical practice; however, these assessments have been shown to be more subjective than quantitative methods. The study included 40 cases of left cranial-caudal (CC) and mediolateral oblique (MLO) radiographs from 20 women. RANZCR-registered radiologists (n=26) estimated mammographic breast density of the same images according to RANZCR synoptic scales 1-4. All images had their volumetric density classified using Volpara Density Grade (VDG) and Average Volumetric Breast Density percentage (AvBD%). The results showed that the radiologists sampled had specialized for 17.18years (sd 12.03) and read 2072 (sd 2441) mammograms per year on average. Inter-observer agreement using RANZCR synoptic scales had an average Kappa of 0.360; (95% CI=0.308-0.412) and a range of 0.078-0.499. Radiologists estimated percentage density was lower by 0.37 than VDG, with their mean being 2.18 and the mean VDG was 2.55 (Z=-3.873; P<0.001). VDG and RANZCR showed a positive strong correlation (ρ=0.898; P<0.001). AvBD% and RANZCR also showed a positive strong correlation (ρ=0.904; P<0.001). The inter-observer agreement with RANZCR synoptic scales was fair. Wide inter-observer variability was observed. Continued research on appropriate assessment methods for mammographic density assessment is required to avoid unnecessary variations.

Abstract P6-10-12: Volumetric breast density better predicts tumour characteristics associated with poor prognosis compared to visual BI-RADS

Abstract Purpose: Early detection of breast cancer through mammography screening reduces breast cancer mortality. To improve outcomes from screening, more than half of invasive cancers and a third of high grade cancers should be small at detection (&amp;lt;15mm), and more than 70% of all cancers should be node negative at diagnosis. Although breast density is associated with reduced mammographic sensitivity, it is unclear whether certain tumor characteristics associated with poorer prognosis are more prevalent in women with denser breasts. The study investigated associations between visually- or volumetrically-assessed breast density and tumor characteristics related to poor prognosis. Methods: Our IRB-approved study included 755 DCIS, invasive ductal or invasive lobular breast cancers diagnosed in women (aged over 40) between January 2009 and December 2012. Information on the patients' tumor characteristics including stage, size, receptor, grade and lymph node status was collected retrospectively. Women were excluded if they had a previous history of breast cancer or breast surgery, or if they were missing tumour size data or raw digital mammograms taken within 24 months of the cancer diagnosis. For women with multiple cancers, only the first diagnosed cancer was included. Breast density was assessed using visual BI-RADS density categories and Volpara Density Grades (VDG; an automated equivalent to 4th Edition BI-RADS, assigned using preset cut-offs of volumetric breast density: 4.5, 7.5, 15.5 and &amp;gt;15.5%). VDG was calculated from both breasts if the prior negative mammogram was available, and the contralateral breast for positive mammograms. Results: Overall, 55% of invasive tumors and 33% of grade 3 tumors were smaller than 15 mm and 83% were node negative. Mean tumor size increased significantly with increasing VDG (VDG 1 = 12.8, 2 = 14.7, 3 = 16.1, 4 = 20.4 mm, p&amp;lt;0.001) and increasing BI-RADS (1 = 12.2, 2 = 13.9, 3 = 16.8, 4 = 18.2 mm, p=0.01). The proportion of node positive tumors also increased significantly with increasing VDG (5.1%, 12.8%, 19.3%, 26.1%, p&amp;lt;0.001) and BI-RADS (0%, 10.6%, 19.5%, 26%, p=0.01). There was a significant increase in grade 3 tumors (11%, 16.1%, 21.7%, 21.7%, p =0.02) and HER-2 positive tumors (5.6%, 10.5%, 13.3%, 14.3%, p=0.02) with increasing VDG that was not seen with visual BI-RADS assessment (p=0.4). Increasing VDG was also significantly associated with increased proportions of larger (i.e. &amp;gt;15mm) node positive cancers (1.7%, 6.3%, 10.5%, 16%, p=0.004) that were not seen with BI-RADS (p=0.2). Conclusion: We found that tumour size and node status differed significantly with breast density as measured by VDG and visual BI-RADS. However, grade 3, HER-2 positive and large/node-positive cancers were all significantly associated with increasing VDG, but not BI-RADS density grade. Further research is needed to investigate whether automated volumetric breast density can be used to predict which women are more likely to be diagnosed with tumours that have poorer prognostic features. Citation Format: Johnston L, Chan A, Arieno A, Morgan R, Highnam R, Destounis S. Volumetric breast density better predicts tumour characteristics associated with poor prognosis compared to visual BI-RADS. [abstract]. In: Proceedings of the Thirty-Eighth Annual CTRC-AACR San Antonio Breast Cancer Symposium: 2015 Dec 8-12; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2016;76(4 Suppl):Abstract nr P6-10-12.

Breast Density Estimation with Fully Automated Volumetric Method:: Comparison to Radiologists' Assessment by BI-RADS Categories

The objective of our study was to calculate mammographic breast density with a fully automated volumetric breast density measurement method and to compare it to breast imaging reporting and data system (BI-RADS) breast density categories assigned by two radiologists. A total of 476 full-field digital mammography examinations with standard mediolateral oblique and craniocaudal views were evaluated by two blinded radiologists and BI-RADS density categories were assigned. Using a fully automated software, mean fibroglandular tissue volume, mean breast volume, and mean volumetric breast density were calculated. Based on percentage volumetric breast density, a volumetric density grade was assigned from 1 to 4. The weighted overall kappa was 0.895 (almost perfect agreement) for the two radiologists' BI-RADS density estimates. A statistically significant difference was seen in mean volumetric breast density among the BI-RADS density categories. With increased BI-RADS density category, increase in mean volumetric breast density was also seen (P < 0.001). A significant positive correlation was found between BI-RADS categories and volumetric density grading by fully automated software (ρ = 0.728, P < 0.001 for first radiologist and ρ = 0.725, P < 0.001 for second radiologist). Pairwise estimates of the weighted kappa between Volpara density grade and BI-RADS density category by two observers showed fair agreement (κ = 0.398 and 0.388, respectively). In our study, a good correlation was seen between density grading using fully automated volumetric method and density grading using BI-RADS density categories assigned by the two radiologists. Thus, the fully automated volumetric method may be used to quantify breast density on routine mammography.

Mammographic Breast Density Assessment Using Automated Volumetric Software and Breast Imaging Reporting and Data System (BIRADS) Categorization by Expert Radiologists

To investigate agreement on mammographic breast density (MD) assessment between automated volumetric software and Breast Imaging Reporting and Data System (BIRADS) categorization by expert radiologists. Forty cases of left craniocaudal and mediolateral oblique mammograms from 20 women were used. All images had their volumetric density classified using Volpara density grade (VDG) and average volumetric breast density percentage. The same images were then classified into BIRADS categories (I-IV) by 20 American Board of Radiology examiners. The results demonstrated a moderate agreement (κ = 0.537; 95% CI = 0.234-0.699) between VDG classification and radiologists' BIRADS density assessment. Interreader agreement using BIRADS also demonstrated moderate agreement (κ = 0.565; 95% CI = 0.519-0.610) ranging from 0.328 to 0.669. Radiologists' average BIRADS was lower than average VDG scores by 0.33, with their mean being 2.13, whereas the mean VDG was 2.48 (U = -3.742; P < 0.001). VDG and BIRADS showed a very strong positive correlation (ρ = 0.91; P < 0.001) as did BIRADS and average volumetric breast density percentage (ρ = 0.94; P < 0.001). Automated volumetric breast density assessment shows moderate agreement and very strong correlation with BIRADS; interreader variations still exist within BIRADS. Because of the increasing importance of MD measurement in clinical management of patients, widely accepted, reproducible, and accurate measures of MD are required.

Mammographic density measurements are not affected by mammography system.

Mammographic density (MD) is a significant risk factor for breast cancer and has been shown to reduce the sensitivity of mammography screening. Knowledge of a woman's density can be used to predict her risk of developing breast cancer and personalize her imaging pathway. However, measurement of breast density has proven to be troublesome with wide variations in density recorded using radiologists' visual Breast Imaging Reporting and Data System (BIRADS). Several automated methods for assessing breast density have been proposed, each with their own source of measurement error. The use of differing mammographic imaging systems further complicates MD measurement, especially for the same women imaged over time. The purpose of this study was to investigate whether having a mammogram on differing manufacturer's equipment affects a woman's MD measurement. Raw mammographic images were acquired on two mammography imaging systems (General Electric and Hologic) one year apart and processed using VolparaDensity™ to obtain the Volpara Density Grade (VDG) and average volumetric breast density percentage (AvBD%). Visual BIRADS scores were also obtained from 20 expert readers. BIRADS scores for both systems showed strong positive correlation ([Formula: see text]; [Formula: see text]), while the VDG ([Formula: see text]; [Formula: see text]) and AvBD% ([Formula: see text]; [Formula: see text]) showed stronger positive correlations. Substantial agreement was shown between the systems for BIRADS ([Formula: see text]; [Formula: see text]), however, the systems demonstrated an almost perfect agreement for VDG ([Formula: see text]; [Formula: see text]).

TU-F-18C-06: Which Women Based On Clinical Benefits and Dose Should Be Considered For Breast Screening with Tomosynthesis?

Purpose: To consider, on a patient specific basis according to volumetric breast density (VBD) the mean glandular dose (MGD) imparted by mammography and tomosynthesis so as to determine which women might benefit from tomosynthesis in consideration with the clinical benefits. Methods: For a set of 23 Hologic combo-mode images, MGD was calculated for the tomosynthesis and mammogram acquisitions, with glandularity derived from a personalised measure of VBD. The doses for each acquisition type were compared as a function of VBD, and correlated with breast thickness. Results: For dense breasts - precisely, those with a Volpara Density Grade (VDG) (analogous to BI-RADS) of 3 and 4 - the MGDs were approximately equal for both tomosynthesis and mammography. However, for low density breasts - those with a VDG of 1 and 2 - the MGD was significantly greater in the tomosynthesis examination than for the mammogram. The compressed breast thickness was generally greater for the lower density (VDG 1 and 2) breasts, than for higher density (VDG 3 and 4) breasts. Conclusion: In breasts of low VBD, examination by mammography offers a lower patient specific MGD than tomosynthesis, sometimes substantially. In breasts of high VBD, the MGD values are approximately equal. The lower MGD is likely due to the increased compressed breast thickness observed in the low density cases. This causes such images to be acquired at a higher MGD in tomosynthesis in order to obtain a satisfactory contrast-to-noise ratio. This results from fundamental differences in the characteristics of the function relating contrast-to-noise ratio to dose between the techniques. Since the possibility of lesion masking arising from tissue superposition is limited in low density breasts, clinicians need to consider the diagnostic benefits versus the apparent increased dose in fatty breasts, which will remain even if the 2D component is stopped. Volpara Solutions Ltd market software for measuring volumetric breast density (Volpara Density), and measuring personalised mean glandular dose (Volpara Dose).