Feasibility study of a breast density measurement within a direct photon-counting mammography scanner system

Machida, Youichi; Tozaki, Mitsuhiro; Yoshida, Tsuyoshi; Saita, Ai; Yakabe, Mari; Nii, Kanae

doi:10.1007/s11604-014-0333-x

Cited by 9 publications

(9 citation statements)

References 24 publications

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“…Breast density has been established as an independent risk factor for breast cancer. The high reproducibility and accuracy of volumetric breast density (VBD) evaluation techniques from mammographic images have been reported in several studies (Skippage et al 2013 ; Wang et al 2013 ; Hammann-Kloss et al 2014 ; Machida et al 2014 ). Additionally, studies have confirmed a strong correlation between VBD, calculated from mammography, and breast cancer risk (Eng et al 2014 ; Brand et al 2014 ; Trinh et al 2015 ; Schetter et al 2014 ).…”

Section: Introductionmentioning

confidence: 93%

Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version

Machida

Saita

Namba³

et al. 2016

SpringerPlus

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BackgroundA new software version of VolparaDensity (Volpara Algorithm version 1.5.1) is capable of calculating volumetric breast density (VBD) using either full-field digital mammography (FFDM) or digital breast tomosynthesis (DBT) images. In this preliminary study, we evaluated the feasibility and consistency of this new automated software.FindingsRaw data from both DBT and FFDM were acquired from women breast cancer screening at our institution between April and August 2015 using. The DBT and FFDM images obtained under a single compression were collected and VBD was measured using fully automated software. A paired t test was used to analyze differences in the VBD calculated from paired FFDM and DBT images. The correlation coefficient (R value) was calculated and p < 0.05 was considered significant. Dualmodality images were acquired in 160 women; VBD data were available for all but one. There was a significant difference in the VBD of individual breasts calculated from DBT and FFDM and when data were compared per case (<0.001 and p = 0.006, respectively). There were very good to excellent correlations between data from FFDM and from DBT (R = 0.78, p < 0.0001; per breast, R = 0.89, p < 0.0001, per case, R = 0.91, p < 0.0001).ConclusionsVBD from DBT was well correlated to that from FFDM, though significant differences were observed between the two.

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Section: Introductionmentioning

confidence: 93%

Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version

Machida

Saita

Namba³

et al. 2016

SpringerPlus

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“…The Philips Spectral Density Measurement Tool outputs VBD, total fibroglandular volume and total breast volume as well as a “MicroDose Density Score”, analogous to a BI-RADS categorization [65]. However, clinical studies using this method have been small and limited [66,67,68]. …”

Section: Fully-automated Density Assessmentmentioning

confidence: 99%

Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad

Destounis¹,

Arieno²,

Morgan³

et al. 2017

Diagnostics

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Mammographic breast density (MBD) has been proven to be an important risk factor for breast cancer and an important determinant of mammographic screening performance. The measurement of density has changed dramatically since its inception. Initial qualitative measurement methods have been found to have limited consistency between readers, and in regards to breast cancer risk. Following the introduction of full-field digital mammography, more sophisticated measurement methodology is now possible. Automated computer-based density measurements can provide consistent, reproducible, and objective results. In this review paper, we describe various methods currently available to assess MBD, and provide a discussion on the clinical utility of such methods for breast cancer screening.

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“…A direct photon-counting mammography scanner system is able to acquire spectral energy data of incident photon particles of each mammogram without additional radiation or risk of misregistration, and proportions of dense tissue within breasts are calculated out of acquired spectral energy data. Machida et al [43] previously assessed the clinical feasibility of an application within a mammography system using a photon-counting technology, which calculates volumetric glandularity (proportion of fibroglandular tissue within a breast), and showed a high accuracy using this technology.…”

Section: Measuring Breast Composition Using Photoncounting Technologymentioning

confidence: 99%

Breast density: the trend in breast cancer screening

Machida¹,

Tozaki

Shimauchi

et al. 2015

Breast Cancer

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The primary modality for breast cancer screening is mammography. Recent investigations, however, have indicated that an insufficient number of life-threatening cases have been detected by mammography while mammography can often results in a large number of overdiagnoses. To make breast cancer screening more effective, potential factors that influence screening efficacy need to be elucidated. Breast density is one of limiting factors for breast cancer detection using mammography. In this article, influence of breast density on breast screening is explained. Current topics related to breast density, objective assessment of breast density using applications, revision of breast composition classification in Breast Imaging-Reporting and Data System Mammography fifth edition, and legislative movement regarding breast density in the United States, are also mentioned in this review article.

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Feasibility study of a breast density measurement within a direct photon-counting mammography scanner system

Abstract: The calculated volumetric glandularity using this new application should correspond well with the true volumetric density of each breast.

Cited by 9 publications

References 24 publications

Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version

Automated volumetric breast density estimation out of digital breast tomosynthesis data: feasibility study of a new software version

Qualitative Versus Quantitative Mammographic Breast Density Assessment: Applications for the US and Abroad

Breast density: the trend in breast cancer screening

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