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Kusumaningtyas N, Supit NISH, Murtala B, Muis M, Chandra M, Sanjaya E, Octavius GS. A systematic review and meta-analysis of correlation of automated breast density measurement. Radiography (Lond) 2024; 30:1455-1467. [PMID: 39164186 DOI: 10.1016/j.radi.2024.08.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2024] [Revised: 07/22/2024] [Accepted: 08/05/2024] [Indexed: 08/22/2024]
Abstract
INTRODUCTION Breast cancer is the most common cancer in women and a leading cause of mortality. This systematic review and meta-analysis aims to evaluate the correlation between breast density measurements obtained from various software and visual assessments by radiologists using full-field digital mammography (FFDM). METHODS Following the PRISMA 2020 guidelines, five databases (Pubmed, Google Scholar, Science Direct, Cochrane Library, and MEDLINE) were searched for studies correlating volumetric breast density with breast cancer risk. The Newcastle-Ottawa Scale and the Joanna Briggs Institute Checklist were used to assess the quality of the included studies. Meta-analysis of correlation was applied to aggregate correlation coefficients using a random-effects model using MedCalc Statistical Software version 19.2.6. RESULTS The review included 22 studies with a total of 58,491 women. The pooled correlation coefficient for volumetric breast density amongst Volpara™ and Quantra™ was found to be 0.755 (95% CI 0.496-0.890, p < 0.001), indicating a high positive correlation, albeit with a significant heterogeneity (I2 = 99.89%, p < 0.0001). Subgroup analyses based on study origin, quality, and methodology were performed but did not reveal the heterogeneity cause. Egger's and Begg's tests showed no significant publication bias. CONCLUSION Volumetric breast density is strongly correlated with breast cancer risk, underscoring the importance of accurate breast density assessment in screening programs. Automated volumetric measurement tools like Volpara™ and Quantra™ provide reliable assessments, potentially improving breast cancer risk prediction and management. IMPLICATIONS FOR PRACTICE Implementing fully automated breast density assessment tools could enhance consistency in clinical practice, minimizing observer variability and improving screening accuracy. These tools should be further validated against standardized criteria to ensure reliability in diverse clinical settings.
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Affiliation(s)
- N Kusumaningtyas
- Woman Imaging Division, Department of Radiology, Faculty of Universitas Pelita Harapan, Tangerang, Indonesia; Department of Radiology of Siloam Hospital MRCCC, Jakarta, Indonesia.
| | - N I S H Supit
- Woman Imaging Division, Department of Radiology, Faculty of Universitas Pelita Harapan, Tangerang, Indonesia; Department of Radiology of Siloam Hospital MRCCC, Jakarta, Indonesia
| | - B Murtala
- Department of Radiology of Universitas Hasanuddin, South Sulawesi, Makassar, Indonesia
| | - M Muis
- Department of Radiology of Universitas Hasanuddin, South Sulawesi, Makassar, Indonesia
| | - M Chandra
- Radiology Resident, Faculty of Universitas Pelita Harapan, Tangerang, Indonesia
| | - E Sanjaya
- Radiology Resident, Faculty of Universitas Pelita Harapan, Tangerang, Indonesia
| | - G S Octavius
- Radiology Resident, Faculty of Universitas Pelita Harapan, Tangerang, Indonesia
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Gennaro G, Bucchi L, Ravaioli A, Zorzi M, Falcini F, Russo F, Caumo F. The risk-based breast screening (RIBBS) study protocol: a personalized screening model for young women. LA RADIOLOGIA MEDICA 2024; 129:727-736. [PMID: 38512619 PMCID: PMC11088554 DOI: 10.1007/s11547-024-01797-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/15/2023] [Accepted: 02/02/2024] [Indexed: 03/23/2024]
Abstract
The optimal mammography screening strategy for women aged 45-49 years is a matter of debate. We present the RIBBS study protocol, a quasi-experimental, prospective, population-based study comparing a risk- and breast density-stratified screening model (interventional cohort) with annual digital mammography (DM) screening (observational control cohort) in a real-world setting. The interventional cohort consists of 10,269 women aged 45 years enrolled between 2020 and 2021 from two provinces of the Veneto Region (northen Italy). At baseline, participants underwent two-view digital breast tomosynthesis (DBT) and completed the Tyrer-Cuzick risk prediction model. Volumetric breast density (VBD) was calculated from DBT and the lifetime risk (LTR) was estimated by including VBD among the risk factors. Based on VBD and LTR, women were classified into five subgroups with specific screening protocols for subsequent screening rounds: (1) LTR ≤ 17% and nondense breast: biennial DBT; (2) LTR ≤ 17% and dense breast: biennial DBT and ultrasound; (3) LTR 17-30% or LTR > 30% without family history of BC, and nondense breast: annual DBT; (4) LTR 17-30% or > 30% without family history of BC, and dense breast: annual DBT and ultrasound; and (5) LTR > 30% and family history of BC: annual DBT and breast MRI. The interventional cohort is still ongoing. An observational, nonequivalent control cohort of 43,000 women aged 45 years participating in an annual DM screening programme was recruited in three provinces of the neighbouring Emilia-Romagna Region. Cumulative incidence rates of advanced BC at three, five, and ten years between the two cohorts will be compared, adjusting for the incidence difference at baseline.Trial registration This study is registered on Clinicaltrials.gov (NCT05675085).
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Affiliation(s)
| | - Lauro Bucchi
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy.
| | - Alessandra Ravaioli
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy
| | - Manuel Zorzi
- SER - Servizio Epidemiologico Regionale e Registri, Azienda Zero, Padua, Italy
| | - Fabio Falcini
- Emilia-Romagna Cancer Registry, Romagna Cancer Institute, IRCCS Istituto Romagnolo per lo Studio dei Tumori (IRST) Dino Amadori, Meldola, Forlì, Italy
- Cancer Prevention Unit, Local Health Authority, Forlì, Italy
| | - Francesca Russo
- Direzione Prevenzione, Sicurezza Alimentare, Veterinaria, Regione del Veneto, Venice, Italy
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Quantitative Breast Density in Contrast-Enhanced Mammography. J Clin Med 2021; 10:jcm10153309. [PMID: 34362092 PMCID: PMC8348046 DOI: 10.3390/jcm10153309] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/18/2021] [Revised: 07/20/2021] [Accepted: 07/22/2021] [Indexed: 11/16/2022] Open
Abstract
Contrast-enhanced mammography (CEM) demonstrates a potential role in personalized screening models, in particular for women at increased risk and women with dense breasts. In this study, volumetric breast density (VBD) measured in CEM images was compared with VBD obtained from digital mammography (DM) or tomosynthesis (DBT) images. A total of 150 women who underwent CEM between March 2019 and December 2020, having at least a DM/DBT study performed before/after CEM, were included. Low-energy CEM (LE-CEM) and DM/DBT images were processed with automatic software to obtain the VBD. VBDs from the paired datasets were compared by Wilcoxon tests. A multivariate regression model was applied to analyze the relationship between VBD differences and multiple independent variables certainly or potentially affecting VBD. Median VBD was comparable for LE-CEM and DM/DBT (12.73% vs. 12.39%), not evidencing any statistically significant difference (p = 0.5855). VBD differences between LE-CEM and DM were associated with significant differences of glandular volume, breast thickness, compression force and pressure, contact area, and nipple-to-posterior-edge distance, i.e., variables reflecting differences in breast positioning (coefficient of determination 0.6023; multiple correlation coefficient 0.7761). Volumetric breast density was obtained from low-energy contrast-enhanced spectral mammography and was not significantly different from volumetric breast density measured from standard mammograms.
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Quantification of water and lipid density with dual-energy mammography: validation in postmortem breasts. Eur Radiol 2020; 31:938-946. [PMID: 32845386 DOI: 10.1007/s00330-020-07179-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/03/2020] [Revised: 06/23/2020] [Accepted: 08/11/2020] [Indexed: 10/23/2022]
Abstract
OBJECTIVES Breast cancer is the most common cancer in women and the second leading cause of cancer death. It is well known that breast density is an important risk factor for breast cancer and also can be used to personalize screening and for assessment of treatment response. Breast density has previously been correlated to volumetric water density. The purpose of this study is to validate the accuracy and precision of dual-energy mammography in measuring water density in postmortem breasts. METHODS Twenty pairs of postmortem breasts were imaged using dual-energy mammography with energy-sensitive photon-counting detectors. Chemical analysis was used as the reference standard to assess the accuracy of dual-energy mammography in measuring volumetric water and lipid density. Images from different views and contralateral breasts were used to assess estimate of precision for water and lipid volumetric density measurements. RESULTS The measured volumetric water and lipid density from dual-energy mammography and chemical analysis were in good agreement, where the standard errors of estimates (SEE) of both were calculated to be 2.1%. Volumetric water and lipid density measurements from different views were also in good agreement, with a SEE of 1.3% and 1.1%, respectively. CONCLUSIONS The results indicate that dual-energy mammography can be used to accurately measure volumetric water and lipid density in breast tissue. Accurate quantification of volumetric water density is expected to enhance its utility as a risk factor for breast cancer and for assessment of response to therapy. KEY POINTS • Dual-energy mammography can be used to accurately measure water and lipid volumetric density in breast tissue. • Improved quantification of volumetric water density is expected to enhance its utility for assessment of response to therapy and as a risk factor for breast cancer.
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Fieselmann A, Förnvik D, Förnvik H, Lång K, Sartor H, Zackrisson S, Kappler S, Ritschl L, Mertelmeier T. Volumetric breast density measurement for personalized screening: accuracy, reproducibility, consistency, and agreement with visual assessment. J Med Imaging (Bellingham) 2019; 6:031406. [PMID: 30746394 PMCID: PMC6362711 DOI: 10.1117/1.jmi.6.3.031406] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/28/2018] [Accepted: 12/27/2018] [Indexed: 01/22/2023] Open
Abstract
Assessment of breast density at the point of mammographic examination could lead to optimized breast cancer screening pathways. The onsite breast density information may offer guidance of when to recommend supplemental imaging for women in a screening program. A software application (Insight BD, Siemens Healthcare GmbH) for fast onsite quantification of volumetric breast density is evaluated. The accuracy of the method is assessed using breast tissue equivalent phantom experiments resulting in a mean absolute error of 3.84%. Reproducibility of measurement results is analyzed using 8427 exams in total, comparing for each exam (if available) the densities determined from left and right views, from cranio-caudal and medio-lateral oblique views, from full-field digital mammograms (FFDM) and digital breast tomosynthesis (DBT) data and from two subsequent exams of the same breast. Pearson correlation coefficients of 0.937, 0.926, 0.950, and 0.995 are obtained. Consistency of the results is demonstrated by evaluating the dependency of the breast density on women's age. Furthermore, the agreement between breast density categories computed by the software with those determined visually by 32 radiologists is shown by an overall percentage agreement of 69.5% for FFDM and by 64.6% for DBT data. These results demonstrate that the software delivers accurate, reproducible, and consistent measurements that agree well with the visual assessment of breast density by radiologists.
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Affiliation(s)
| | - Daniel Förnvik
- Lund University and Skåne University Hospital, Department of Translational Medicine, Malmö, Sweden
| | - Hannie Förnvik
- Lund University and Skåne University Hospital, Department of Translational Medicine, Malmö, Sweden
| | - Kristina Lång
- Lund University and Skåne University Hospital, Department of Translational Medicine, Malmö, Sweden
- Institute for Biomedical Engineering, ETH Zurich, Zurich, Switzerland
| | - Hanna Sartor
- Lund University and Skåne University Hospital, Department of Translational Medicine, Malmö, Sweden
| | - Sophia Zackrisson
- Lund University and Skåne University Hospital, Department of Translational Medicine, Malmö, Sweden
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Alqudah AM, Algharib HMS, Algharib AMS, Algharib HMS. COMPUTER AIDED DIAGNOSIS SYSTEM FOR AUTOMATIC TWO STAGES CLASSIFICATION OF BREAST MASS IN DIGITAL MAMMOGRAM IMAGES. BIOMEDICAL ENGINEERING-APPLICATIONS BASIS COMMUNICATIONS 2019. [DOI: 10.4015/s1016237219500078] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/07/2022]
Abstract
Breast cancer is the most frequent cancer type that is diagnosed in women. The exact causes of such cancer are still unknown. Early and precise detection of breast cancer using mammogram images or biopsy to provide the required medications can increase the healing percentage. There are much current research efforts to developed a computer aided diagnosis (CAD) system based on mammogram images for detecting and classification of breast masses. In this research, a CAD system is developed for automated segmentation and two-stages classification of breast masses. The first stage includes the classification of the masses into seven classes (normal, calcification, circumscribed, spiculated, ill-defined, architectural distortion, asymmetry), which is done using probabilistic neural network (PNN). The second classification stage is to define the severity of abnormality into two classes (Benign and Malignant) which were done using support vector machine (SVM). The results of applying the proposed method on two mammogram image show that the accuracy of detection and segmentation of the breast mass was 99.8% for mammographic image analysis society database (MIAS-DB) with 322 images and 97.5% for breast cancer digital repository (BCDR), BCDR-F03 and BCDR-DN01 with 936 images, while for the first classification stage has accuracy of 97.08%, sensitivity of 98.30% and specificity of 89.8%, and the second classification stage has an accuracy of 99.18%, sensitivity of 98.42% and specificity of 94.90%.
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Affiliation(s)
- Ali Mohammad Alqudah
- Department of Biomedical Systems and Informatics Engineering, Yarmouk University, Irbid, Jordan
| | | | - Amal M. S. Algharib
- Department of Biomedical Engineering, Middle East Technical University, Ankara, Turkey
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Strand F, Azavedo E, Hellgren R, Humphreys K, Eriksson M, Shepherd J, Hall P, Czene K. Localized mammographic density is associated with interval cancer and large breast cancer: a nested case-control study. Breast Cancer Res 2019; 21:8. [PMID: 30670066 PMCID: PMC6341532 DOI: 10.1186/s13058-019-1099-y] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/11/2018] [Accepted: 01/10/2019] [Indexed: 01/13/2023] Open
Abstract
Background High mammographic density is associated with breast cancer and with delayed detection. We have examined whether localized density, at the site of the subsequent cancer, is independently associated with being diagnosed with a large-sized or interval breast cancer. Methods Within a prospective cohort of 63,130 women, we examined 891 women who were diagnosed with incident breast cancer. For 386 women, retrospective localized density assessment was possible. The main outcomes were interval cancer vs. screen-detected cancer and large (> 2 cm) vs. small cancer. In negative screening mammograms, overall and localized density were classified reflecting the BI-RADS standard. Density concordance probabilities were estimated through multinomial regression. The associations between localized density and the two outcomes were modeled through logistic regression, adjusted for overall density, age, body mass index, and other characteristics. Results The probabilities of concordant localized density were 0.35, 0.60, 0.38, and 0.32 for overall categories “A,” “B,” “C,” and “D.” Overall density was associated with large cancer, comparing density category D to A with OR 4.6 (95%CI 1.8–11.6) and with interval cancer OR 31.5 (95%CI 10.9–92) among all women. Localized density was associated with large cancer at diagnosis with OR 11.8 (95%CI 2.7–51.8) among all women and associated with first-year interval cancer with OR 6.4 (0.7 to 58.7) with a significant linear trend p = 0.027. Conclusions Overall density often misrepresents localized density at the site where cancer subsequently arises. High localized density is associated with interval cancer and with large cancer. Our findings support the continued effort to develop and examine computer-based measures of localized density for use in personalized breast cancer screening. Electronic supplementary material The online version of this article (10.1186/s13058-019-1099-y) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Fredrik Strand
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden. .,Breast Radiology, Karolinska University Hospital, Stockholm, Sweden.
| | - Edward Azavedo
- Department of Molecular Medicine and Surgery, Karolinska Institutet, Stockholm, Sweden
| | - Roxanna Hellgren
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden.,Department of Radiology, Southern General Hospital, Stockholm, Sweden
| | - Keith Humphreys
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | - Mikael Eriksson
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
| | | | - Per Hall
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden.,Department of Oncology, South General Hospital, Stockholm, Sweden
| | - Kamila Czene
- Department of Medical Epidemiology and Biostatistics, Karolinska Institutet, Nobels Väg 12A, 171 77, Stockholm, Sweden
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Wengert GJ, Helbich TH, Leithner D, Morris EA, Baltzer PAT, Pinker K. Multimodality Imaging of Breast Parenchymal Density and Correlation with Risk Assessment. CURRENT BREAST CANCER REPORTS 2019; 11:23-33. [PMID: 35496471 PMCID: PMC9044508 DOI: 10.1007/s12609-019-0302-6] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
Abstract
Purpose of Review Breast density, or the amount of fibroglandular tissue in the breast, has become a recognized and independent marker for breast cancer risk. Public awareness of breast density as a possible risk factor for breast cancer has resulted in legislation for risk stratification purposes in many US states. This review will provide a comprehensive overview of the currently available imaging modalities for qualitative and quantitative breast density assessment and the current evidence on breast density and breast cancer risk assessment. Recent Findings To date, breast density assessment is mainly performed with mammography and to some extent with magnetic resonance imaging. Data indicate that computerized, quantitative techniques in comparison with subjective visual estimations are characterized by higher reproducibility and robustness. Summary Breast density reduces the sensitivity of mammography due to a masking effect and is also a recognized independent risk factor for breast cancer. Standardized breast density assessment using automated volumetric quantitative methods has the potential to be used for risk prediction and stratification and in determining the best screening plan for each woman.
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Wengert GJ, Helbich TH, Kapetas P, Baltzer PA, Pinker K. Density and tailored breast cancer screening: practice and prediction - an overview. Acta Radiol Open 2018; 7:2058460118791212. [PMID: 30245850 PMCID: PMC6144518 DOI: 10.1177/2058460118791212] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2018] [Accepted: 06/27/2018] [Indexed: 01/13/2023] Open
Abstract
Mammography, as the primary screening modality, has facilitated a substantial
decrease in breast cancer-related mortality in the general population. However,
the sensitivity of mammography for breast cancer detection is decreased in women
with higher breast densities, which is an independent risk factor for breast
cancer. With increasing public awareness of the implications of a high breast
density, there is an increasing demand for supplemental screening in these
patients. Yet, improvements in breast cancer detection with supplemental
screening methods come at the expense of increased false-positives, recall
rates, patient anxiety, and costs. Therefore, breast cancer screening practice
must change from a general one-size-fits-all approach to a more personalized,
risk-based one that is tailored to the individual woman’s risk, personal
beliefs, and preferences, while accounting for cost, potential harm, and
benefits. This overview will provide an overview of the available breast density assessment
modalities, the current breast density screening recommendations for women at
average risk of breast cancer, and supplemental methods for breast cancer
screening. In addition, we will provide a look at the possibilities for a
risk-adapted breast cancer screening.
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Affiliation(s)
- Georg J Wengert
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
| | - Thomas H Helbich
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
| | - Panagiotis Kapetas
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
| | - Pascal At Baltzer
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria
| | - Katja Pinker
- Department of Biomedical Imaging and Image-guided Therapy, Division of Molecular and Gender Imaging, Medical University of Vienna, Vienna, Austria.,Department of Radiology, Breast Imaging Service, Memorial Sloan-Kettering Cancer Center, New York, NY, USA
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Gennaro G, Bernardi D, Houssami N. Radiation dose with digital breast tomosynthesis compared to digital mammography: per-view analysis. Eur Radiol 2017; 28:573-581. [DOI: 10.1007/s00330-017-5024-4] [Citation(s) in RCA: 64] [Impact Index Per Article: 9.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/09/2017] [Revised: 07/22/2017] [Accepted: 08/04/2017] [Indexed: 11/27/2022]
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Cho HM, Ding H, Kumar N, Sennung D, Molloi S. Calibration phantoms for accurate water and lipid density quantification using dual energy mammography. Phys Med Biol 2017; 62:4589-4603. [DOI: 10.1088/1361-6560/aa6f31] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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McCarthy AM, Keller BM, Pantalone LM, Hsieh MK, Synnestvedt M, Conant EF, Armstrong K, Kontos D. Racial Differences in Quantitative Measures of Area and Volumetric Breast Density. J Natl Cancer Inst 2016; 108:djw104. [PMID: 27130893 PMCID: PMC5939658 DOI: 10.1093/jnci/djw104] [Citation(s) in RCA: 61] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2015] [Revised: 01/29/2016] [Accepted: 03/09/2016] [Indexed: 12/12/2022] Open
Abstract
BACKGROUND Increased breast density is a strong risk factor for breast cancer and also decreases the sensitivity of mammographic screening. The purpose of our study was to compare breast density for black and white women using quantitative measures. METHODS Breast density was assessed among 5282 black and 4216 white women screened using digital mammography. Breast Imaging-Reporting and Data System (BI-RADS) density was obtained from radiologists' reports. Quantitative measures for dense area, area percent density (PD), dense volume, and volume percent density were estimated using validated, automated software. Breast density was categorized as dense or nondense based on BI-RADS categories or based on values above and below the median for quantitative measures. Logistic regression was used to estimate the odds of having dense breasts by race, adjusted for age, body mass index (BMI), age at menarche, menopause status, family history of breast or ovarian cancer, parity and age at first birth, and current hormone replacement therapy (HRT) use. All statistical tests were two-sided. RESULTS There was a statistically significant interaction of race and BMI on breast density. After accounting for age, BMI, and breast cancer risk factors, black women had statistically significantly greater odds of high breast density across all quantitative measures (eg, PD nonobese odds ratio [OR] = 1.18, 95% confidence interval [CI] = 1.02 to 1.37, P = .03, PD obese OR = 1.26, 95% CI = 1.04 to 1.53, P = .02). There was no statistically significant difference in BI-RADS density by race. CONCLUSIONS After accounting for age, BMI, and other risk factors, black women had higher breast density than white women across all quantitative measures previously associated with breast cancer risk. These results may have implications for risk assessment and screening.
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Affiliation(s)
- Anne Marie McCarthy
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Brad M Keller
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Lauren M Pantalone
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Meng-Kang Hsieh
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Marie Synnestvedt
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Emily F Conant
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Katrina Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
| | - Despina Kontos
- Department of Medicine, Massachusetts General Hospital, Boston, MA (AMM, KA); Department of Radiology, University of Pennsylvania, Philadelphia, PA (BMK, LMP, MKH, MS, EFC, DK)
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Molloi S, Ducote JL, Ding H, Feig SA. Postmortem validation of breast density using dual-energy mammography. Med Phys 2015; 41:081917. [PMID: 25086548 DOI: 10.1118/1.4890295] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/27/2022] Open
Abstract
PURPOSE Mammographic density has been shown to be an indicator of breast cancer risk and also reduces the sensitivity of screening mammography. Currently, there is no accepted standard for measuring breast density. Dual energy mammography has been proposed as a technique for accurate measurement of breast density. The purpose of this study is to validate its accuracy in postmortem breasts and compare it with other existing techniques. METHODS Forty postmortem breasts were imaged using a dual energy mammography system. Glandular and adipose equivalent phantoms of uniform thickness were used to calibrate a dual energy basis decomposition algorithm. Dual energy decomposition was applied after scatter correction to calculate breast density. Breast density was also estimated using radiologist reader assessment, standard histogram thresholding and a fuzzy C-mean algorithm. Chemical analysis was used as the reference standard to assess the accuracy of different techniques to measure breast composition. RESULTS Breast density measurements using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual energy were in good agreement with the measured fibroglandular volume fraction using chemical analysis. The standard error estimates using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean, and dual energy were 9.9%, 8.6%, 7.2%, and 4.7%, respectively. CONCLUSIONS The results indicate that dual energy mammography can be used to accurately measure breast density. The variability in breast density estimation using dual energy mammography was lower than reader assessment rankings, standard histogram thresholding, and fuzzy C-mean algorithm. Improved quantification of breast density is expected to further enhance its utility as a risk factor for breast cancer.
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Affiliation(s)
- Sabee Molloi
- Department of Radiological Sciences, University of California, Irvine, California 92697
| | - Justin L Ducote
- Department of Radiological Sciences, University of California, Irvine, California 92697
| | - Huanjun Ding
- Department of Radiological Sciences, University of California, Irvine, California 92697
| | - Stephen A Feig
- Department of Radiological Sciences, University of California, Irvine, California 92697
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Keller BM, Chen J, Daye D, Conant EF, Kontos D. Preliminary evaluation of the publicly available Laboratory for Breast Radiodensity Assessment (LIBRA) software tool: comparison of fully automated area and volumetric density measures in a case-control study with digital mammography. Breast Cancer Res 2015; 17:117. [PMID: 26303303 PMCID: PMC4549121 DOI: 10.1186/s13058-015-0626-8] [Citation(s) in RCA: 60] [Impact Index Per Article: 6.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2015] [Accepted: 08/04/2015] [Indexed: 12/30/2022] Open
Abstract
INTRODUCTION Breast density, commonly quantified as the percentage of mammographically dense tissue area, is a strong breast cancer risk factor. We investigated associations between breast cancer and fully automated measures of breast density made by a new publicly available software tool, the Laboratory for Individualized Breast Radiodensity Assessment (LIBRA). METHODS Digital mammograms from 106 invasive breast cancer cases and 318 age-matched controls were retrospectively analyzed. Density estimates acquired by LIBRA were compared with commercially available software and standard Breast Imaging-Reporting and Data System (BI-RADS) density estimates. Associations between the different density measures and breast cancer were evaluated by using logistic regression after adjustment for Gail risk factors and body mass index (BMI). Area under the curve (AUC) of the receiver operating characteristic (ROC) was used to assess discriminatory capacity, and odds ratios (ORs) for each density measure are provided. RESULTS All automated density measures had a significant association with breast cancer (OR = 1.47-2.23, AUC = 0.59-0.71, P < 0.01) which was strengthened after adjustment for Gail risk factors and BMI (OR = 1.96-2.64, AUC = 0.82-0.85, P < 0.001). In multivariable analysis, absolute dense area (OR = 1.84, P < 0.001) and absolute dense volume (OR = 1.67, P = 0.003) were jointly associated with breast cancer (AUC = 0.77, P < 0.01), having a larger discriminatory capacity than models considering the Gail risk factors alone (AUC = 0.64, P < 0.001) or the Gail risk factors plus standard area percent density (AUC = 0.68, P = 0.01). After BMI was further adjusted for, absolute dense area retained significance (OR = 2.18, P < 0.001) and volume percent density approached significance (OR = 1.47, P = 0.06). This combined area-volume density model also had a significantly (P < 0.001) improved discriminatory capacity (AUC = 0.86) relative to a model considering the Gail risk factors plus BMI (AUC = 0.80). CONCLUSIONS Our study suggests that new automated density measures may ultimately augment the current standard breast cancer risk factors. In addition, the ability to fully automate density estimation with digital mammography, particularly through the use of publically available breast density estimation software, could accelerate the translation of density reporting in routine breast cancer screening and surveillance protocols and facilitate broader research into the use of breast density as a risk factor for breast cancer.
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Affiliation(s)
- Brad M Keller
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Silverstein Building, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, Perelman School of Medicine, University of Pennsylvania, 203 Blockley Hall, 423 Guardian Drive, Philadelphia, PA, USA.
| | - Dania Daye
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Silverstein Building, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Emily F Conant
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Silverstein Building, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
| | - Despina Kontos
- Department of Radiology, Perelman School of Medicine, University of Pennsylvania, 1 Silverstein Building, 3400 Spruce Street, Philadelphia, PA, 19104, USA.
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Molloi S, Ding H, Feig S. Breast density evaluation using spectral mammography, radiologist reader assessment, and segmentation techniques: a retrospective study based on left and right breast comparison. Acad Radiol 2015; 22:1052-9. [PMID: 26031229 DOI: 10.1016/j.acra.2015.03.017] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2015] [Revised: 03/17/2015] [Accepted: 03/18/2015] [Indexed: 11/18/2022]
Abstract
RATIONALE AND OBJECTIVES The purpose of this study was to compare the precision of mammographic breast density measurement using radiologist reader assessment, histogram threshold segmentation, fuzzy C-mean segmentation, and spectral material decomposition. MATERIALS AND METHODS Spectral mammography images from a total of 92 consecutive asymptomatic women (aged 50-69 years) who presented for annual screening mammography were retrospectively analyzed for this study. Breast density was estimated using 10 radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and spectral material decomposition. The breast density correlation between left and right breasts was used to assess the precision of these techniques to measure breast composition relative to dual-energy material decomposition. RESULTS In comparison to the other techniques, the results of breast density measurements using dual-energy material decomposition showed the highest correlation. The relative standard error of estimate for breast density measurements from left and right breasts using radiologist reader assessment, standard histogram thresholding, fuzzy C-mean algorithm, and dual-energy material decomposition was calculated to be 1.95, 2.87, 2.07, and 1.00, respectively. CONCLUSIONS The results indicate that the precision of dual-energy material decomposition was approximately factor of two higher than the other techniques with regard to better correlation of breast density measurements from right and left breasts.
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Affiliation(s)
- Sabee Molloi
- Department of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA 92697.
| | - Huanjun Ding
- Department of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA 92697
| | - Stephen Feig
- Department of Radiological Sciences, University of California, Medical Sciences I, B-140, Irvine, CA 92697
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He W, Juette A, Denton ERE, Oliver A, Martí R, Zwiggelaar R. A Review on Automatic Mammographic Density and Parenchymal Segmentation. Int J Breast Cancer 2015; 2015:276217. [PMID: 26171249 PMCID: PMC4481086 DOI: 10.1155/2015/276217] [Citation(s) in RCA: 33] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2015] [Revised: 04/21/2015] [Accepted: 05/17/2015] [Indexed: 01/03/2023] Open
Abstract
Breast cancer is the most frequently diagnosed cancer in women. However, the exact cause(s) of breast cancer still remains unknown. Early detection, precise identification of women at risk, and application of appropriate disease prevention measures are by far the most effective way to tackle breast cancer. There are more than 70 common genetic susceptibility factors included in the current non-image-based risk prediction models (e.g., the Gail and the Tyrer-Cuzick models). Image-based risk factors, such as mammographic densities and parenchymal patterns, have been established as biomarkers but have not been fully incorporated in the risk prediction models used for risk stratification in screening and/or measuring responsiveness to preventive approaches. Within computer aided mammography, automatic mammographic tissue segmentation methods have been developed for estimation of breast tissue composition to facilitate mammographic risk assessment. This paper presents a comprehensive review of automatic mammographic tissue segmentation methodologies developed over the past two decades and the evidence for risk assessment/density classification using segmentation. The aim of this review is to analyse how engineering advances have progressed and the impact automatic mammographic tissue segmentation has in a clinical environment, as well as to understand the current research gaps with respect to the incorporation of image-based risk factors in non-image-based risk prediction models.
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Affiliation(s)
- Wenda He
- Department of Computer Science, Aberystwyth University, Aberystwyth SY23 3DB, UK
| | - Arne Juette
- Department of Radiology, Norfolk & Norwich University Hospital, Norwich NR4 7UY, UK
| | - Erika R. E. Denton
- Department of Radiology, Norfolk & Norwich University Hospital, Norwich NR4 7UY, UK
| | - Arnau Oliver
- Department of Architecture and Computer Technology, University of Girona, 17071 Girona, Spain
| | - Robert Martí
- Department of Architecture and Computer Technology, University of Girona, 17071 Girona, Spain
| | - Reyer Zwiggelaar
- Department of Computer Science, Aberystwyth University, Aberystwyth SY23 3DB, UK
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17
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Keller BM, McCarthy AM, Chen J, Armstrong K, Conant EF, Domchek SM, Kontos D. Associations between breast density and a panel of single nucleotide polymorphisms linked to breast cancer risk: a cohort study with digital mammography. BMC Cancer 2015; 15:143. [PMID: 25881232 PMCID: PMC4365961 DOI: 10.1186/s12885-015-1159-3] [Citation(s) in RCA: 14] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/13/2014] [Accepted: 03/04/2015] [Indexed: 12/16/2022] Open
Abstract
Background Breast density and single-nucleotide polymorphisms (SNPs) have both been associated with breast cancer risk. To determine the extent to which these two breast cancer risk factors are associated, we investigate the association between a panel of validated SNPs related to breast cancer and quantitative measures of mammographic density in a cohort of Caucasian and African-American women. Methods In this IRB-approved, HIPAA-compliant study, we analyzed a screening population of 639 women (250 African American and 389 Caucasian) who were tested with a validated panel assay of 12 SNPs previously associated to breast cancer risk. Each woman underwent digital mammography as part of routine screening and all were interpreted as negative. Both absolute and percent estimates of area and volumetric density were quantified on a per-woman basis using validated software. Associations between the number of risk alleles in each SNP and the density measures were assessed through a race-stratified linear regression analysis, adjusted for age, BMI, and Gail lifetime risk. Results The majority of SNPs were not found to be associated with any measure of breast density. SNP rs3817198 (in LSP1) was significantly associated with both absolute area (p = 0.004) and volumetric (p = 0.019) breast density in Caucasian women. In African-American women, SNPs rs3803662 (in TNRC9/TOX3) and rs4973768 (in NEK10) were significantly associated with absolute (p = 0.042) and percent (p = 0.028) volume density respectively. Conclusions The majority of SNPs investigated in our study were not found to be significantly associated with breast density, even when accounting for age, BMI, and Gail risk, suggesting that these two different risk factors contain potentially independent information regarding a woman’s risk to develop breast cancer. Additionally, the few statistically significant associations between breast density and SNPs were different for Caucasian versus African American women. Larger prospective studies are warranted to validate our findings and determine potential implications for breast cancer risk assessment. Electronic supplementary material The online version of this article (doi:10.1186/s12885-015-1159-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Brad M Keller
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Anne Marie McCarthy
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Jinbo Chen
- Department of Biostatistics and Epidemiology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Katrina Armstrong
- Department of Medicine, Massachusetts General Hospital, Boston, MA, 02114, USA.
| | - Emily F Conant
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
| | - Susan M Domchek
- Abramson Cancer Center, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA, 19104, USA.
| | - Despina Kontos
- Department of Radiology, University of Pennsylvania Perelman School of Medicine, 3600 Market St. Ste 360, Philadelphia, PA, 19104, USA.
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Ekpo EU, McEntee MF. Measurement of breast density with digital breast tomosynthesis--a systematic review. Br J Radiol 2014; 87:20140460. [PMID: 25146640 DOI: 10.1259/bjr.20140460] [Citation(s) in RCA: 38] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/19/2023] Open
Abstract
Digital breast tomosynthesis (DBT) has gained acceptance as an adjunct to digital mammography in screening. Now that breast density reporting is mandated in several states in the USA, it is increasingly important that the methods of breast density measurement be robust, reliable and consistent. Breast density assessment with DBT needs some consideration since quantitative methods are modelled for two-dimensional (2D) mammography. A review of methods used for breast density assessment with DBT was performed. Existing evidence shows Cumulus has better reproducibility than that of the breast imaging reporting and data system (BI-RADS®) but still suffers from subjective variability; MedDensity is limited by image noise, whilst Volpara and Quantra are robust and consistent. The reported BI-RADs inter-reader breast density agreement (k) ranged from 0.65 to 0.91, with inter-reader correlation (r) ranging from 0.70 to 0.93. The correlation (r) between BI-RADS and Cumulus ranged from 0.54-0.94, whilst that of BI-RADs and MedDensity ranged from 0.48-0.78. The reported agreement (k) between BI-RADs and Volpara is 0.953. Breast density correlation between DBT and 2D mammography ranged from 0.73 to 0.97, with agreement (k) ranging from 0.56 to 0.96. To avoid variability and provide more reliable breast density information for clinicians, automated volumetric methods are preferred.
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Affiliation(s)
- E U Ekpo
- 1 Discipline of Medical Radiation Science, Faculty of Health Science, University of Sydney, Sydney, NSW, Australia
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19
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Sohn G, Lee JW, Park SW, Park J, Woo J, Kim HJ, Shin HJ, Kim HH, Jung KH, Sung J, Lee SW, Son BH, Ahn SH. Reliability of the percent density in digital mammography with a semi-automated thresholding method. J Breast Cancer 2014; 17:174-9. [PMID: 25013440 PMCID: PMC4090321 DOI: 10.4048/jbc.2014.17.2.174] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2013] [Accepted: 03/17/2014] [Indexed: 11/30/2022] Open
Abstract
PURPOSE The reliability of the quantitative measurement of breast density with a semi-automated thresholding method (Cumulus™) has mainly been investigated with film mammograms. This study aimed to evaluate the intrarater reproducibility of percent density (PD) by Cumulus™ with digital mammograms. METHODS This study included 1,496 craniocaudal digital mammograms from the unaffected breast of breast cancer patients. One rater reviewed each mammogram and estimated the PD using the Cumulus™ method. All images were reassessed by the same rater 1 month later without reference to the previously assigned values. The repeatability of the PD was evaluated by an intraclass correlation coefficient (ICC). All patients were grouped based on their body mass index (BMI), age, family history of breast cancer, breastfeeding history and breast area (calculated with Cumulus™), and subgroup analysis for the ICC of each group was performed. All patients were categorized by their Breast Imaging Reporting and Data System (BI-RADS) density pattern, and the mean and standard deviation of the PD by each BI-RADS categories were compared. RESULTS The ICC for the PD was 0.94, indicating excellent repeatability. The discrepancy between the paired PD values ranged from 0 to 23.93, with an average of 3.90 (standard deviation=3.39). The subgroup ICCs for the PD ranged from 0.88 to 0.96, indicating excellent reliability in all subgroups regardless of patient variables. The ICCs of the PD for the high-risk (BI-RADS 3 and 4) and low-risk (BI-RADS 1 and 2) groups were 0.90 and 0.88, respectively. CONCLUSION This study suggests that PD calculated with digital mammograms has an acceptable reliability regardless of patient age, BMI, family history of breast cancer, breastfeeding history, breast size, and BI-RADS density pattern.
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Affiliation(s)
- Guiyun Sohn
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jong Won Lee
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sung Won Park
- Department of Radiology, Health Promotion Center, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jihoon Park
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Jiyoung Woo
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hwa Jung Kim
- Department of Biostatistics and Clinical Epidemiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hee Jung Shin
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Hak Hee Kim
- Department of Radiology and Research Institute of Radiology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Kyung Hae Jung
- Department of Oncology, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Joohon Sung
- Department of Epidemiology, School of Public Health and Institution of Health and Environment, Seoul National University, Seoul, Korea
| | - Seung Wook Lee
- Graduate School of Public Health, Seoul National University, Seoul, Korea
| | - Byung Ho Son
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
| | - Sei-Hyun Ahn
- Department of Surgery, Asan Medical Center, University of Ulsan College of Medicine, Seoul, Korea
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Lam AR, Ding H, Molloi S. Quantification of breast density using dual-energy mammography with liquid phantom calibration. Phys Med Biol 2014; 59:3985-4000. [DOI: 10.1088/0031-9155/59/14/3985] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
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Breast density assessment using a 3T MRI system: comparison among different sequences. PLoS One 2014; 9:e99027. [PMID: 24892933 PMCID: PMC4044003 DOI: 10.1371/journal.pone.0099027] [Citation(s) in RCA: 26] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/15/2014] [Accepted: 05/09/2014] [Indexed: 11/23/2022] Open
Abstract
Purpose To compare MRI sequences for breast density measurements on a 3T MRI system using IDEAL (Iterative Decomposition of water and fat with Echo Asymmetry and Least squares estimation) as possible physiology-like reference. Materials and Methods MRI examination was performed in 48 consecutive patients (mean age 41, years; range, 35–67 years) on a 3.0T scanner and 46 were included. All (fertile) women, were examined between days 5 and 15 of their menstrual cycle. MRI protocol included: T1-turbo spin-echo (T1-tSE), T2-turbo spin-echo (T2-tSE), VIBRANT (Volume Imaging for Breast Assessment) before and after injection of contrast media and IDEAL. Breast density was calculated with semi-automated software. Statistical analysis was performed with non-parametric tests. Results Mean percentage of breast density calculated in each sequence was: T1-tSE = 56%; T2-tSE = 52%; IDEAL FatOnly = 55%; IDEAL WaterOnly = 53%, VIBRANT = 55%. Significant differences were observed between T2-tSE and both T1-tSE (p<0.001), VIBRANT sequences (p = 0.009), T1-tSE and both IDEAL WaterOnly (p = 0.007) and IDEAL FatOnly (p = 0.047). Breast density percentage showed a positive linear correlation among different sequences: r≥0.93. Conclusions Differences exist between MRI sequences used to assess breast density percentage. T1-weighted sequences values were similar to IDEAL sequences.
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Machida Y, Tozaki M, Yoshida T, Saita A, Yakabe M, Nii K. Feasibility study of a breast density measurement within a direct photon-counting mammography scanner system. Jpn J Radiol 2014; 32:561-7. [PMID: 24838833 DOI: 10.1007/s11604-014-0333-x] [Citation(s) in RCA: 8] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/18/2014] [Accepted: 05/09/2014] [Indexed: 01/12/2023]
Abstract
PURPOSE To evaluate the clinical feasibility of breast density measurements by a new application within a direct photon-counting mammography scanner system. MATERIALS AND METHODS A retrospective study of consecutive women who underwent mammography using a direct photon-counting mammography scanner system (MicroDose mammography SI; Philips Digital Mammography Sweden AB) was performed at the authors' institution between September and December 2013. Quantitative volumetric glandularity measurements were performed automatically for each acquired mammographic image using an application (Breast Density Measurement; Philips Digital Mammography Sweden AB). The quantitative volumetric glandularity of each breast was defined as the average values for the mediolateral oblique (MLO) and craniocaudal (CC) mammogram views. RESULTS Of the 44 women who underwent bilateral mammogram acquisitions, the breast density measurements were performed successfully in 40 patients (90.9%). A very good to excellent correlation in the quantitative breast density measurements acquired from the MLO and CC images was obtained in the 40 evaluable patients (R = 0.99). CONCLUSION The calculated volumetric glandularity using this new application should correspond well with the true volumetric density of each breast.
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Affiliation(s)
- Youichi Machida
- Diagnostic Imaging Center, Kameda Kyobashi Clinic, Tokyo Square Garden 4F, 3-1-1 Kyobashi, Chuo-ku, Tokyo, 104-0031, Japan,
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Vállez N, Bueno G, Déniz O, Dorado J, Seoane JA, Pazos A, Pastor C. Breast density classification to reduce false positives in CADe systems. COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE 2014; 113:569-584. [PMID: 24286729 DOI: 10.1016/j.cmpb.2013.10.004] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.9] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/30/2012] [Revised: 10/03/2013] [Accepted: 10/05/2013] [Indexed: 06/02/2023]
Abstract
This paper describes a novel weighted voting tree classification scheme for breast density classification. Breast parenchymal density is an important risk factor in breast cancer. Moreover, it is known that mammogram interpretation is more difficult when dense tissue is involved. Therefore, automated breast density classification may aid in breast lesion detection and analysis. Several classification methods have been compared and a novel hierarchical classification procedure of combined classifiers with linear discriminant analysis (LDA) is proposed as the best solution to classify the mammograms into the four BIRADS tissue classes. The classification scheme is based on 298 texture features. Statistical analysis to test the normality and homoscedasticity of the data was carried out for feature selection. Thus, only features that are influenced by the tissue type were considered. The novel classification techniques have been incorporated into a CADe system to drive the detection algorithms and tested with 1459 images. The results obtained on the 322 screen-film mammograms (SFM) of the mini-MIAS dataset show that 99.75% of samples were correctly classified. On the 1137 full-field digital mammograms (FFDM) dataset results show 91.58% agreement. The results of the lesion detection algorithms were obtained from modules integrated within the CADe system developed by the authors and show that using breast tissue classification prior to lesion detection leads to an improvement of the detection results. The tools enhance the detectability of lesions and they are able to distinguish their local attenuation without local tissue density constraints.
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Affiliation(s)
- Noelia Vállez
- VISILAB, Engineering School, Universidad de Castilla-La Mancha, Spain.
| | - Gloria Bueno
- VISILAB, Engineering School, Universidad de Castilla-La Mancha, Spain.
| | - Oscar Déniz
- VISILAB, Engineering School, Universidad de Castilla-La Mancha, Spain.
| | - Julián Dorado
- RNASA-IMEDIR Group, Computer School, Universidade da Coruña, Spain
| | | | - Alejandro Pazos
- RNASA-IMEDIR Group, Computer School, Universidade da Coruña, Spain
| | - Carlos Pastor
- Department of Radiology, Hospital General Universitario de Ciudad Real, Spain
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Tagliafico A, Tagliafico G, Houssami N. Differences in breast density assessment using mammography, tomosynthesis and MRI and their implications for practice. Br J Radiol 2013; 86:20130528. [PMID: 24167184 DOI: 10.1259/bjr.20130528] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Affiliation(s)
- A Tagliafico
- Department of Experimental Medicine, University of Genoa, Genoa, Italy
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Tagliafico AS, Tagliafico G, Cavagnetto F, Calabrese M, Houssami N. Estimation of percentage breast tissue density: comparison between digital mammography (2D full field digital mammography) and digital breast tomosynthesis according to different BI-RADS categories. Br J Radiol 2013; 86:20130255. [PMID: 24029631 DOI: 10.1259/bjr.20130255] [Citation(s) in RCA: 28] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/05/2022] Open
Abstract
OBJECTIVE To compare breast density estimated from two-dimensional full-field digital mammography (2D FFDM) and from digital breast tomosynthesis (DBT) according to different Breast Imaging-Reporting and Data System (BI-RADS) categories, using automated software. METHODS Institutional review board approval and written informed patient consent were obtained. DBT and 2D FFDM were performed in the same patients to allow within-patient comparison. A total of 160 consecutive patients (mean age: 50±14 years; mean body mass index: 22±3) were included to create paired data sets of 40 patients for each BI-RADS category. Automatic software (MedDensity(©), developed by Giulio Tagliafico) was used to compare the percentage breast density between DBT and 2D FFDM. The estimated breast percentage density obtained using DBT and 2D FFDM was examined for correlation with the radiologists' visual BI-RADS density classification. RESULTS The 2D FFDM differed from DBT by 16.0% in BI-RADS Category 1, by 11.9% in Category 2, by 3.5% in Category 3 and by 18.1% in Category 4. These differences were highly significant (p<0.0001). There was a good correlation between the BI-RADS categories and the density evaluated using 2D FFDM and DBT (r=0.56, p<0.01 and r=0.48, p<0.01, respectively). CONCLUSION Using DBT, breast density values were lower than those obtained using 2D FFDM, with a non-linear relationship across the BI-RADS categories. These data are relevant for clinical practice and research studies using density in determining the risk. ADVANCES IN KNOWLEDGE On DBT, breast density values were lower than with 2D FFDM, with a non-linear relationship across the classical BI-RADS categories.
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Affiliation(s)
- A S Tagliafico
- Department of Experimental Medicine, University of Genova, Genova, Italy
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Harvey JA, Gard CC, Miglioretti DL, Yankaskas BC, Kerlikowske K, Buist DSM, Geller BA, Onega TL. Reported mammographic density: film-screen versus digital acquisition. Radiology 2012; 266:752-8. [PMID: 23249570 DOI: 10.1148/radiol.12120221] [Citation(s) in RCA: 35] [Impact Index Per Article: 2.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/16/2023]
Abstract
PURPOSE To test the hypothesis that American College of Radiology Breast Imaging Reporting and Data System (BI-RADS) categories for breast density reported by radiologists are lower when digital mammography is used than those reported when film-screen (FS) mammography is used. MATERIALS AND METHODS This study was institutional review board approved and HIPAA compliant. Demographic data, risk factors, and BI-RADS breast density categories were collected from five mammography registries that were part of the Breast Cancer Surveillance Consortium. Active, passive, or waiver of consent was obtained for all participants. Women aged 40 years and older who underwent at least two screening mammographic examinations less than 36 months apart between January 1, 2000, and December 31, 2009, were included. Women with prior breast cancer, augmentation, or use of agents known to affect density were excluded. The main sample included 89 639 women with both FS and digital mammograms. The comparison group included 259 046 women with two FS mammograms and 87 066 women with two digital mammograms. BI-RADS density was cross-tabulated according to the order in which the two types of mammogram were acquired and by the first versus second interpretation. RESULTS Regardless of acquisition method, the percentage of women with a change in density from one reading to the next was similar. Breast density was lower in 19.8% of the women who underwent FS before digital mammography and 17.1% of those who underwent digital before FS mammography. Similarly, lower density classifications were reported on the basis of the second mammographic examination regardless of acquisition method (15.8%-19.8%). The percentage of agreement between density readings was similar regardless of mammographic types paired (67.3%-71.0%). CONCLUSION The study results showed no difference in reported BI-RADS breast density categories according to acquisition method. Reported BI-RADS density categories may be useful in the development of breast cancer risk models in which FS, digital, or both acquisition methods are used.
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Affiliation(s)
- Jennifer A Harvey
- Department of Radiology, University of Virginia, Box 800170, Charlottesville, VA 22908, USA.
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Ding H, Molloi S. Quantification of breast density with spectral mammography based on a scanned multi-slit photon-counting detector: a feasibility study. Phys Med Biol 2012; 57:4719-38. [PMID: 22771941 PMCID: PMC3478949 DOI: 10.1088/0031-9155/57/15/4719] [Citation(s) in RCA: 44] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/25/2023]
Abstract
A simple and accurate measurement of breast density is crucial for the understanding of its impact in breast cancer risk models. The feasibility to quantify volumetric breast density with a photon-counting spectral mammography system has been investigated using both computer simulations and physical phantom studies. A computer simulation model involved polyenergetic spectra from a tungsten anode x-ray tube and a Si-based photon-counting detector has been evaluated for breast density quantification. The figure-of-merit (FOM), which was defined as the signal-to-noise ratio of the dual energy image with respect to the square root of mean glandular dose, was chosen to optimize the imaging protocols, in terms of tube voltage and splitting energy. A scanning multi-slit photon-counting spectral mammography system has been employed in the experimental study to quantitatively measure breast density using dual energy decomposition with glandular and adipose equivalent phantoms of uniform thickness. Four different phantom studies were designed to evaluate the accuracy of the technique, each of which addressed one specific variable in the phantom configurations, including thickness, density, area and shape. In addition to the standard calibration fitting function used for dual energy decomposition, a modified fitting function has been proposed, which brought the tube voltages used in the imaging tasks as the third variable in dual energy decomposition. For an average sized 4.5 cm thick breast, the FOM was maximized with a tube voltage of 46 kVp and a splitting energy of 24 keV. To be consistent with the tube voltage used in current clinical screening exam (∼32 kVp), the optimal splitting energy was proposed to be 22 keV, which offered a FOM greater than 90% of the optimal value. In the experimental investigation, the root-mean-square (RMS) error in breast density quantification for all four phantom studies was estimated to be approximately 1.54% using standard calibration function. The results from the modified fitting function, which integrated the tube voltage as a variable in the calibration, indicated a RMS error of approximately 1.35% for all four studies. The results of the current study suggest that photon-counting spectral mammography systems may potentially be implemented for an accurate quantification of volumetric breast density, with an RMS error of less than 2%, using the proposed dual energy imaging technique.
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Affiliation(s)
- Huanjun Ding
- Department of Radiological Sciences University of California Irvine, CA 92697, USA
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Tagliafico A, Tagliafico G, Astengo D, Cavagnetto F, Rosasco R, Rescinito G, Monetti F, Calabrese M. Mammographic density estimation: one-to-one comparison of digital mammography and digital breast tomosynthesis using fully automated software. Eur Radiol 2012; 22:1265-70. [DOI: 10.1007/s00330-012-2380-y] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/13/2011] [Revised: 11/18/2011] [Accepted: 12/07/2011] [Indexed: 10/28/2022]
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Wessel C, Schnabel JA, Brady M. Towards a more realistic biomechanical modelling of breast malignant tumours. Phys Med Biol 2012; 57:631-48. [DOI: 10.1088/0031-9155/57/3/631] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
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Keller BM, Conant EF, Oh H, Kontos D. Breast Cancer Risk Prediction via Area and Volumetric Estimates of Breast Density. BREAST IMAGING 2012. [DOI: 10.1007/978-3-642-31271-7_31] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/27/2022]
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Wessel C, Schnabel JA, Brady M. A Biomechanical model of spiculated tumours under mammographic compressions. ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY. ANNUAL INTERNATIONAL CONFERENCE 2010; 2010:712-715. [PMID: 21095670 DOI: 10.1109/iembs.2010.5626107] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/30/2023]
Abstract
The aim of this paper is to introduce effects well known to clinicians -but neglected to date- in the biomechanical modelling of breast malignant tumours. We develop a model of an isolated stellate breast tumour under mammographic compression forces. We study a range of reported mechanical properties, both linear elastic and hyperelastic. We also introduce different volumes of increased density/stiffness around the tumour. We show that each of these issues has a non-negligible effect on stresses and strains/deformations.
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Affiliation(s)
- Carolina Wessel
- Department of Engineering Science, University of Oxford, Parks Road, OX1 3PJ, UK.
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Mammographic density estimation: Comparison among BI-RADS categories, a semi-automated software and a fully automated one. Breast 2009; 18:35-40. [DOI: 10.1016/j.breast.2008.09.005] [Citation(s) in RCA: 69] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/11/2008] [Revised: 09/25/2008] [Accepted: 09/26/2008] [Indexed: 01/11/2023] Open
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