Comparison of Hologic’s Quantra Volumetric Assessment to MRI Breast Density

Wang, Jeff; Aziz, Ania; Newitt, David; Joe, Bonnie N.; Hylton, Nola M.; Shepherd, John

doi:10.1007/978-3-642-31271-7_80

Cited by 3 publications

(3 citation statements)

References 3 publications

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“…Both of the automated density measurement tools used in this study have been shown to correlate with measurements made with MR imaging (17,19,24), with methods using a calibration phantom (21) and with visual assessment using Breast Imaging Reporting and Data System categories (17,30). Correlation, however, does not necessarily mean agreement between methods.…”

Section: Breast Imaging: Quantitative Evaluation Of Breast Density Momentioning

confidence: 80%

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Mammographic Breast Density: Comparison of Methods for Quantitative Evaluation

Morrish¹,

Tucker²,

Black³

et al. 2015

Radiology

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Purpose:To evaluate the results from two software tools for measurement of mammographic breast density and compare them with observer-based scores in a large cohort of women. Materials and Methods:Following written informed consent, a data set of 36 281 mammograms from 8867 women were collected from six United Kingdom centers in an ethically approved trial. Breast density was assessed by one of 26 readers on a visual analog scale and with two automated density tools. Mean differences were calculated as the mean of all the individual percentage differences between each measurement for each case (woman). Agreement in total breast volume, fibroglandular volume, and percentage density was assessed with the Bland-Altman method. Association with observer's scores was calculated by using the Pearson correlation coefficient (r). Results:Correlation between the Quantra and Volpara outputs for total breast volume was r = 0.97 (P , .001), with a mean difference of 43.5 cm 3 for all cases representing 5.0% of the mean total breast volume. Correlation of the two measures was lower for fibroglandular volume (r = 0.86, P , .001). The mean difference was 30.3 cm 3 for all cases representing 21.2% of the mean fibroglandular tissue volume result. Quantra gave the larger value and the difference tended to increase with volume. For the two measures of percentage volume density, the mean difference was 1.61 percentage points (r = 0.78, P , .001).Comparison of observer's scores with the area-based density given by Quantra yielded a low correlation (r = 0.55, P , .001). Correlations of observer's scores with the volumetric density results gave r values of 0.60 (P , .001) and 0.63 (P , .001) for Quantra and Volpara, respectively. Conclusion:Automated techniques for measuring breast density show good correlation, but these are poorly correlated with observer's scores. However automated techniques do give different results that should be considered when informing patient personalized imaging. Note: This copy is for your personal non-commercial use only. To order presentation-ready copies for distribution to your colleagues or clients, contact us at www.rsna.org/rsnarights. (11) or within discrete ranges, such as the four-point Breast Imaging Reporting and Data System, BI-RADS (12), scale or the Boyd five-point scale (5). Studies suggest that training and experience are essential in ensuring that the scores are accurate and reproducible (12,13).The introduction of full-field digital mammography technologies has provided an opportunity to implement automated breast density measurement algorithms, which had been initially developed for digitized analog mammograms (11,14). These algorithms work by applying thresholds to the pixel values within the digital image to identify the area of the image that contains the breast and to then determine the proportion of that breast which contains fibroglandular tissue. For example, the pixel values with the highest signal (radiation dose detected by the pixel) can identify the areas of the image where ...

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Section: Breast Imaging: Quantitative Evaluation Of Breast Density Momentioning

confidence: 80%

“…Further differences might be the way that skin and fibroglandular tissue are differentiated in the assessment of dense tissue (18,24,25). significantly influence fibroglandular tissue volumes and volumetric densities.…”

Section: Breast Imaging: Quantitative Evaluation Of Breast Density Momentioning

confidence: 99%

Mammographic Breast Density: Comparison of Methods for Quantitative Evaluation

Morrish¹,

Tucker²,

Black³

et al. 2015

Radiology

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“…[33][34][35][36][37] Examples of automated VBD measurement systems which are available commercially include Quantra (Hologic, Bedford, MA) and Volpara® (Matakina Technology Ltd, Wellington, New Zealand). From previous studies, it appears 10 and Volpara 18 appears to be a further implementation of that original work along with ideas from van Engeland et al 24 Results vs breast MRI appear to suggest that volumetric techniques are now approaching clinical utility, [39][40][41][42] but no thorough sensitivity and robustness analyses appear to have been carried out, to the best of our knowledge, except the one reported by Volpara developers during its early stage of development. 18 Owing to the widespread use of breast density and recent legislative activities in the USA where the laws require females to be informed about their breast density in the mammographic report, it is important that breast density measurement tools are able to provide accurate, consistent and reliable results.…”

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confidence: 95%

Volumetric breast density measurement: sensitivity analysis of a relative physics approach

Lau¹,

Ng²,

Aziz³

2016

BJR

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Gaussian noise was generated and introduced into the original images.Results: Errors in filter thickness, mAs, detector gain and offset had limited effects on FGV, BV and VBD. Significant effects in VBD were observed when CBT, kVp, detector offset and image noise were varied (p , 0.0001). Maximum shifts in the mean (1.2%) and median (1.1%) VBD of the study population occurred when CBT was varied. Conclusion: Volpara was robust to expected clinical variations, with errors in most investigated parameters giving limited changes in results, although extreme variations in CBT and kVp could lead to greater errors. Advances in knowledge: Despite Volpara's robustness, rigorous quality control is essential to keep the parameter errors within reasonable bounds. Volpara appears robust within those bounds, albeit for more advanced applications such as tracking density change over time, it remains to be seen how accurate the measures need to be.

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Volumetric Breast Density Estimation from Full-Field Digital Mammograms: A Validation Study

et al. 2014

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ObjectivesTo objectively evaluate automatic volumetric breast density assessment in Full-Field Digital Mammograms (FFDM) using measurements obtained from breast Magnetic Resonance Imaging (MRI).Material and MethodsA commercially available method for volumetric breast density estimation on FFDM is evaluated by comparing volume estimates obtained from 186 FFDM exams including mediolateral oblique (MLO) and cranial-caudal (CC) views to objective reference standard measurements obtained from MRI.ResultsVolumetric measurements obtained from FFDM show high correlation with MRI data. Pearson’s correlation coefficients of 0.93, 0.97 and 0.85 were obtained for volumetric breast density, breast volume and fibroglandular tissue volume, respectively.ConclusionsAccurate volumetric breast density assessment is feasible in Full-Field Digital Mammograms and has potential to be used in objective breast cancer risk models and personalized screening.

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Comparison of Hologic’s Quantra Volumetric Assessment to MRI Breast Density

Cited by 3 publications

References 3 publications

Mammographic Breast Density: Comparison of Methods for Quantitative Evaluation

Mammographic Breast Density: Comparison of Methods for Quantitative Evaluation

Volumetric breast density measurement: sensitivity analysis of a relative physics approach

Volumetric Breast Density Estimation from Full-Field Digital Mammograms: A Validation Study

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