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Tran TXM, Chang Y, Choi HR, Kwon R, Lim GY, Kim EY, Ryu S, Park B. Adiposity, Body Composition Measures, and Breast Cancer Risk in Korean Premenopausal Women. JAMA Netw Open 2024; 7:e245423. [PMID: 38578637 PMCID: PMC10998159 DOI: 10.1001/jamanetworkopen.2024.5423] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/04/2023] [Accepted: 02/09/2024] [Indexed: 04/06/2024] Open
Abstract
Objective To investigate the association between body composition parameters and breast cancer (BC) risk in premenopausal women. Design, Setting, and Participants Prospective cohort study using data from the Kangbuk Samsung Cohort Study. Participants were women aged 20 to 54 years who were enrolled from 2011 to 2019 and followed up for BC development until December 31, 2020. Data were analyzed from June to August 2023. Exposures Trained nurses conducted anthropometric measurements and assessed body composition using segmental bioelectric impedance analysis. The analysis encompassed adiposity measures such as body mass index (BMI), waist circumference, and body composition parameters, including muscle mass, fat mass, ratio of muscle mass to weight, ratio of fat mass to weight, and fat mass index. Main outcomes and measures Adjusted hazard ratios (aHR) for BC during the follow-up period. Results Among 125 188 premenopausal women, the mean (SD) age was 34.9 (6.3) years. During a mean (range) follow-up of 6.7 (0.5-9.9) years, 1110 incident BC cases were identified. The mean (SD) BMI and waist circumference were 21.6 (3.1) and 75.3 (8.2) cm, respectively. Higher BMI and waist circumference were associated with decreased risk, with an aHR of 0.89 (95% CI, 0.84-0.95) per SD increase in BMI and 0.92 (95% CI, 0.86-0.98) per SD increase in waist circumference. A higher ratio of fat mass to weight was associated with decreased BC risk (aHR, 0.92; 95% CI, 0.86-0.99 per SD increase), whereas the opposite trend was observed for the ratio of muscle mass to weight, with an aHR of 1.08 (95% CI, 1.02-1.15) per SD increase. The results remained consistent even after additional adjustments for height in the model. The fat mass index was also inversely associated with BC risk, with an HR of 0.90 (95% CI, 0.85-0.97) per SD increase. Conclusions and Relevance In this cohort study of premenopausal women, a higher level of adiposity, represented by increased BMI, waist circumference, and fat mass, was consistently associated with decreased breast cancer risk. Conversely, muscle mass and its ratio to weight displayed opposite or inconsistent patterns. These findings suggest an inverse association between excess adiposity and the risk of BC in premenopausal women, confirming earlier findings that BMI is an indirect measure of adiposity.
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Affiliation(s)
- Thi Xuan Mai Tran
- Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
| | - Yoosoo Chang
- Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Hye Rin Choi
- Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Institute of Medical Research, Sungkyunkwan University, School of Medicine, Suwon, Republic of Korea
| | - Ria Kwon
- Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Institute of Medical Research, Sungkyunkwan University, School of Medicine, Suwon, Republic of Korea
| | - Ga-Young Lim
- Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Institute of Medical Research, Sungkyunkwan University, School of Medicine, Suwon, Republic of Korea
| | - Eun Young Kim
- Department of Surgery, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
| | - Seungho Ryu
- Center for Cohort Studies, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Occupational and Environmental Medicine, Kangbuk Samsung Hospital, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea
- Department of Clinical Research Design and Evaluation, Samsung Advanced Institute for Health Sciences and Technology, Sungkyunkwan University, Seoul, Republic of Korea
| | - Boyoung Park
- Department of Preventive Medicine, Hanyang University College of Medicine, Seoul, Republic of Korea
- Hanyang Institute of Bioscience and Biotechnology, Hanyang University, Seoul, Republic of Korea
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Kai C, Otsuka T, Nara M, Kondo S, Futamura H, Kodama N, Kasai S. Identifying factors that indicate the possibility of non-visible cases on mammograms using mammary gland content ratio estimated by artificial intelligence. Front Oncol 2024; 14:1255109. [PMID: 38505584 PMCID: PMC10949406 DOI: 10.3389/fonc.2024.1255109] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/08/2023] [Accepted: 02/12/2024] [Indexed: 03/21/2024] Open
Abstract
Background Mammography is the modality of choice for breast cancer screening. However, some cases of breast cancer have been diagnosed through ultrasonography alone with no or benign findings on mammography (hereby referred to as non-visibles). Therefore, this study aimed to identify factors that indicate the possibility of non-visibles based on the mammary gland content ratio estimated using artificial intelligence (AI) by patient age and compressed breast thickness (CBT). Methods We used AI previously developed by us to estimate the mammary gland content ratio and quantitatively analyze 26,232 controls and 150 non-visibles. First, we evaluated divergence trends between controls and non-visibles based on the average estimated mammary gland content ratio to ensure the importance of analysis by age and CBT. Next, we evaluated the possibility that mammary gland content ratio ≥50% groups affect the divergence between controls and non-visibles to specifically identify factors that indicate the possibility of non-visibles. The images were classified into two groups for the estimated mammary gland content ratios with a threshold of 50%, and logistic regression analysis was performed between controls and non-visibles. Results The average estimated mammary gland content ratio was significantly higher in non-visibles than in controls when the overall sample, the patient age was ≥40 years and the CBT was ≥40 mm (p < 0.05). The differences in the average estimated mammary gland content ratios in the controls and non-visibles for the overall sample was 7.54%, the differences in patients aged 40-49, 50-59, and ≥60 years were 6.20%, 7.48%, and 4.78%, respectively, and the differences in those with a CBT of 40-49, 50-59, and ≥60 mm were 6.67%, 9.71%, and 16.13%, respectively. In evaluating mammary gland content ratio ≥50% groups, we also found positive correlations for non-visibles when controls were used as the baseline for the overall sample, in patients aged 40-59 years, and in those with a CBT ≥40 mm (p < 0.05). The corresponding odds ratios were ≥2.20, with a maximum value of 4.36. Conclusion The study findings highlight an estimated mammary gland content ratio of ≥50% in patients aged 40-59 years or in those with ≥40 mm CBT could be indicative factors for non-visibles.
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Affiliation(s)
- Chiharu Kai
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan
- Major in Health and Welfare, Graduate School of Niigata University of Health and Welfare, Niigata, Niigata, Japan
| | | | - Miyako Nara
- Department of Breast Surgery, Tokyo Metropolitan Cancer and Infectious Disease Center, Komagome Hospital, Tokyo, Japan
| | - Satoshi Kondo
- Graduate School of Engineering, Muroran Institute of Technology, Muroran, Hokkaido, Japan
| | - Hitoshi Futamura
- Healthcare Business Headquarters, Konica Minolta, Inc., Tokyo, Japan
| | - Naoki Kodama
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan
| | - Satoshi Kasai
- Department of Radiological Technology, Faculty of Medical Technology, Niigata University of Health and Welfare, Niigata, Niigata, Japan
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Magni V, Capra D, Cozzi A, Monti CB, Mobini N, Colarieti A, Sardanelli F. Mammography biomarkers of cardiovascular and musculoskeletal health: A review. Maturitas 2023; 167:75-81. [PMID: 36308974 DOI: 10.1016/j.maturitas.2022.10.001] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2022] [Revised: 10/09/2022] [Accepted: 10/10/2022] [Indexed: 11/07/2022]
Abstract
Breast density (BD) and breast arterial calcifications (BAC) can expand the role of mammography. In premenopause, BD is related to body fat composition: breast adipose tissue and total volume are potential indicators of fat storage in visceral depots, associated with higher risk of cardiovascular disease (CVD). Women with fatty breast have an increased likelihood of hypercholesterolemia. Women without cardiometabolic diseases with higher BD have a lower risk of diabetes mellitus, hypertension, chest pain, and peripheral vascular disease, while those with lower BD are at increased risk of cardiometabolic diseases. BAC, the expression of Monckeberg sclerosis, are associated with CVD risk. Their prevalence, 13 % overall, rises after menopause and is reduced in women aged over 65 receiving hormonal replacement therapy. Due to their distinct pathogenesis, BAC are associated with hypertension but not with other cardiovascular risk factors. Women with BAC have an increased risk of acute myocardial infarction, ischemic stroke, and CVD death; furthermore, moderate to severe BAC load is associated with coronary artery disease. The clinical use of BAC assessment is limited by their time-consuming manual/visual quantification, an issue possibly solved by artificial intelligence-based approaches addressing BAC complex topology as well as their large spectrum of extent and x-ray attenuations. A link between BD, BAC, and osteoporosis has been reported, but data are still inconclusive. Systematic, standardised reporting of BD and BAC should be encouraged.
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Affiliation(s)
- Veronica Magni
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Davide Capra
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Andrea Cozzi
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.
| | - Caterina B Monti
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Nazanin Mobini
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy.
| | - Anna Colarieti
- Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy
| | - Francesco Sardanelli
- Department of Biomedical Sciences for Health, Università degli Studi di Milano, Via Mangiagalli 31, 20133 Milano, Italy; Unit of Radiology, IRCCS Policlinico San Donato, Via Morandi 30, 20097 San Donato Milanese, Italy.
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Association of body composition fat parameters and breast density in mammography by menopausal status. Sci Rep 2022; 12:22224. [PMID: 36564447 PMCID: PMC9789058 DOI: 10.1038/s41598-022-26839-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/26/2022] [Accepted: 12/21/2022] [Indexed: 12/24/2022] Open
Abstract
We investigated the relationship between body fat-driven obesity and breast fat density in mammography according to menopausal status. We retrospectively analyzed 8537 women (premenopausal, n = 4351; postmenopausal, n = 4186). Body fat parameters included BMI (body mass index), waist circumference (WC), waist-hip ratio (WHR), fat mass index (FMI), Percentage of body fat (PBF), and visceral fat area (VFA). Body fat-driven obesity was defined as follows: overall obesity, BMI ≥ 25 kg/m2; central obesity, WC > 85 cm; abdominal obesity, WHR > 0.85; excessive FMI, the highest quartile (Q4) of FMI; excessive PBF, the highest quartile (Q4) of VFA; visceral obesity, and the highest quartile (Q4) of VFA). Breast density was classified according to BI-RADS (grade a, b, c, and d), which defined as an ordinal scale (grade a = 1, grade b = 2, grade c = 3, and grade d = 4). All body fat-driven obesity parameters were negatively associated with the grade of breast density in both groups of women (p < 0.001): The more fatty parameters are, the less dense breast is. In multivariable binary logistic regression, all body fat-driven obesity parameters also showed a negative association with grade d density (vs. grade a, b, or c). In premenopausal women, BMI was a more associated parameter with grade d density than those of the other fat-driven parameters (OR 0.265, CI 0.204-0.344). In postmenopausal women, WC was more associated with grade d density than the others (OR 0.315, CI 0.239-0.416). We found that BMI, WC, WHR, FMI, PBF and VFA were negatively correlated with dense breast, and the association degree pattern between body fat-driven obesity and dense breast differs according to menopausal status.
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Chalfant JS, Hoyt AC. Breast Density: Current Knowledge, Assessment Methods, and Clinical Implications. JOURNAL OF BREAST IMAGING 2022; 4:357-370. [PMID: 38416979 DOI: 10.1093/jbi/wbac028] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2022] [Indexed: 03/01/2024]
Abstract
Breast density is an accepted independent risk factor for the future development of breast cancer, and greater breast density has the potential to mask malignancies on mammography, thus lowering the sensitivity of screening mammography. The risk associated with dense breast tissue has been shown to be modifiable with changes in breast density. Numerous studies have sought to identify factors that influence breast density, including age, genetic, racial/ethnic, prepubertal, adolescent, lifestyle, environmental, hormonal, and reproductive history factors. Qualitative, semiquantitative, and quantitative methods of breast density assessment have been developed, but to date there is no consensus assessment method or reference standard for breast density. Breast density has been incorporated into breast cancer risk models, and there is growing consciousness of the clinical implications of dense breast tissue in both the medical community and public arena. Efforts to improve breast cancer screening sensitivity for women with dense breasts have led to increased attention to supplemental screening methods in recent years, prompting the American College of Radiology to publish Appropriateness Criteria for supplemental screening based on breast density.
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Affiliation(s)
- James S Chalfant
- David Geffen School of Medicine at University of California, Los Angeles, Department of Radiological Sciences, Santa Monica, CA, USA
| | - Anne C Hoyt
- David Geffen School of Medicine at University of California, Los Angeles, Department of Radiological Sciences, Santa Monica, CA, USA
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