Quantitative assessment of mammographic density and breast cancer risk for Japanese women

Kotsuma, Y; Tamaki, Yasuhiro; Nishimura, Toshihiro; Tsubai, Masayoshi; Ueda, Shinsuke; Shimazu, Kenzo; Kim, Seung Jin; Miyoshi, Yasuo; Tanji, Yoshio; Taguchi, Tetsuya; Noguchi, Shinzaburo

doi:10.1016/j.breast.2007.06.002

Cited by 33 publications

(26 citation statements)

References 35 publications

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“…Previous studies from Western countries have shown that women with extremely dense breasts (75 % or more dense tissue in breasts) have four to six times greater risk of developing breast cancer than women with fatty breasts (25 % or less dense tissue in breasts) [22][23][24][25][26][27][28][29][30]. Reports from Asian countries, mainly from Japan, have also identified dense breast tissue as a risk factor for breast cancer [31][32][33].…”

Section: Breast Density As a Risk Factor For Breast Cancermentioning

confidence: 93%

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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Section: Breast Density As a Risk Factor For Breast Cancermentioning

confidence: 93%

Breast density: the trend in breast cancer screening

Machida¹,

Tozaki

Shimauchi

et al. 2015

Breast Cancer

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“…With this program, MBD was examined for 223 healthy postmenopausal women and 205 postmenopausal BC patients. The mean MBD was higher for cases than controls aged between 50 and 90 years, with their last menopause less than 9 years previously, and a BMI of \22.3 kg/m 2 , without a history of childbirth or of a family history of BC among their first-and second-degree relatives (Table 3) [23]. For the case control study, the controls were divided into five groups according to MBD with almost equal numbers in each group, and the cases were also divided into five groups with MBDs corresponding to those of the five control groups.…”

Section: Mammographic Breast Densitymentioning

confidence: 92%

“…For the case control study, the controls were divided into five groups according to MBD with almost equal numbers in each group, and the cases were also divided into five groups with MBDs corresponding to those of the five control groups. Women in the quintile with the highest MBD were found to have a significantly higher risk of BC than those in the quintile with the lowest MBD after adjustment for current age, period after menopause, family history, age of menarche, parity status and BMI (OR = 3.02, 95% CI = 1.58-5.77) (Table 3A) [23]. Comparison of the women in the highest quintile (High) and those in other quintiles (Low) showed an odds ratio of 2.81 (95% CI = 1.72-4.59) (Table 3B) [23].…”

Section: Mammographic Breast Densitymentioning

confidence: 94%

“…Women in the quintile with the highest MBD were found to have a significantly higher risk of BC than those in the quintile with the lowest MBD after adjustment for current age, period after menopause, family history, age of menarche, parity status and BMI (OR = 3.02, 95% CI = 1.58-5.77) (Table 3A) [23]. Comparison of the women in the highest quintile (High) and those in other quintiles (Low) showed an odds ratio of 2.81 (95% CI = 1.72-4.59) (Table 3B) [23]. Our results indicated that MBD can function as a reliable risk factor of BC for postmenopausal Japanese women.…”

Section: Mammographic Breast Densitymentioning

confidence: 94%

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Breast cancer risk assessment for possible tailored screening for Japanese women

et al. 2009

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Accurate risk assessment for individual women is essential for effective screening of breast cancer (BC) in Japan, because the incidence of BC is still lower than in Western countries. We investigated various new risk factors of BC by means of case control studies and found that serum estrone and adiponectine levels as well as mammographic breast density were significantly correlated to BC risk. Combining these new factors and conventional risk factors of BC may result in a new and useful risk assessment tool, may improve the cost-effectiveness of screening, and may enable us to reduce the BC mortality of Japanese women.

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“…Furthermore, federal legislation has been introduced that would require national reporting of whether or not the patient has dense tissue. Such efforts have also stirred up interest in other countries, including Japan [41][42][43][44]. Despite existing work reporting on mammographic breast density worldwide however, it does not appear that an automatic method of measuring quantitative volumetric breast density (VBD) on full-field digital mammography (FFDM) has yet been accepted into routine practice.…”

Section: Introductionmentioning

confidence: 99%

Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer

et al. 2016

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Breast cancer is the most common invasive cancer among women and its incidence is increasing. Risk assessment is valuable and recent methods are incorporating novel biomarkers such as mammographic density. Artificial neural networks (ANN) are adaptive algorithms capable of performing pattern-to-pattern learning and are well suited for medical applications. They are potentially useful for calibrating full-field digital mammography (FFDM) for quantitative analysis. This study uses ANN modeling to estimate volumetric breast density (VBD) from FFDM on Japanese women with and without breast cancer. ANN calibration of VBD was performed using phantom data for one FFDM system. Mammograms of 46 Japanese women diagnosed with invasive carcinoma and 53 with negative findings were analyzed using ANN models learned. ANN-estimated VBD was validated against phantom data, compared intra-patient, with qualitative composition scoring, with MRI VBD, and interpatient with classical risk factors of breast cancer as well as cancer status. Phantom validations reached an R 2 of 0.993. Intra-patient validations ranged from R 2 of 0.789 with VBD to 0.908 with breast volume. ANN VBD agreed well with BI-RADS scoring and MRI VBD with R 2 ranging from 0.665 with VBD to 0.852 with breast volume. VBD was significantly higher in women with cancer. Associations with age, BMI, menopause, and cancer status previously reported were also confirmed. ANN modeling appears to produce reasonable measures of mammographic density validated with phantoms, with existing measures of breast density, and with classical biomarkers of breast cancer. FFDM VBD is significantly higher in Japanese women with cancer.

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Quantitative assessment of mammographic density and breast cancer risk for Japanese women

Cited by 33 publications

References 35 publications

Breast density: the trend in breast cancer screening

Breast density: the trend in breast cancer screening

Breast cancer risk assessment for possible tailored screening for Japanese women

Automatic Estimation of Volumetric Breast Density Using Artificial Neural Network-Based Calibration of Full-Field Digital Mammography: Feasibility on Japanese Women With and Without Breast Cancer

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