Alternative methods to measure breast density in younger women

Lloyd, Rachel; Pirikahu, Sarah; Walter, Jane; Cadby, Gemma; Darcey, Ellie; Perera, Dilukshi; Hickey, Martha; Saunders, Christobel; Karnowski, Karol; Sampson, David D.; Shepherd, John; Lilge, Lothar; Stone, Jennifer

doi:10.1038/s41416-023-02201-5

Cited by 5 publications

(6 citation statements)

References 33 publications

(40 reference statements)

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“…Instead, menarche mainly explained AFGV variability (39%), but BMI z-score only explained 2%. The Dietary Intervention Study in Children (DISC) performed magnetic resonance imaging in 174 women aged between 25 and 29 years, and they observed an inverse association between body fatness and %FGV and AFGV [ 26 ], while we observed an inverse association with %FGV and positive with AFGV, similar to a recent study published by Lloyd 2023 in 169 women aged between 18 and 40 year [ 27 ] and our previous findings in premenopausal women [ 12 ]. Most of the studies carried out in pre or post-menopausal women agree with the inverse association between body fatness and %FGV, but the evidence with AFGV remains controversial [ 12 , 28 – 30 ].…”

Section: Discussionsupporting

confidence: 90%

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

Pereira,

Garmendia,

Leiva

et al. 2024

Breast Cancer Res

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Background Breast density (BD) is a strong risk factor for breast cancer. Little is known about how BD develops during puberty. Understanding BD trajectories during puberty and its determinants could be crucial for promoting preventive actions against breast cancer (BC) at early ages. The objective of this research is to characterize % fibroglandular volume (%FGV), absolute fibroglandular volume (AFGV), and breast volume (BV) at different breast Tanner stages until 4-year post menarche in a Latino cohort and to assess determinants of high %FGV and AFGV during puberty and in a fully mature breast. Methods This is a longitudinal follow-up of 509 girls from low-middle socioeconomic status of the Southeast area of Santiago, recruited at a mean age of 3.5 years. The inclusion criteria were singleton birth born, birthweight between 2500 and 4500 g with no medical or mental disorder. A trained dietitian measured weight and height since 3.5 years old and sexual maturation from 8 years old (breast Tanner stages and age at menarche onset). Using standardized methods, BD was measured using dual-energy X-ray absorptiometry (DXA) in various developmental periods (breast Tanner stage B1 until 4 years after menarche onset). Results In the 509 girls, we collected 1,442 breast DXA scans; the mean age at Tanner B4 was 11.3 years. %FGV increased across breast Tanner stages and peaked 250 days after menarche. AFGV and BV peaked 2 years after menarche onset. Girls in the highest quartiles of %FGV, AFGV, and BV at Tanner B4 and B5 before menarche onset had the highest values thereafter until 4 years after menarche onset. The most important determinants of %FGV and AFGV variability were BMI z-score (R2 = 44%) and time since menarche (R2 = 42%), respectively. Conclusion We characterize the breast development during puberty, a critical window of susceptibility. Although the onset of menarche is a key milestone for breast development, we observed that girls in the highest quartiles of %FGV and AFGV tracked in that group afterwards. Following these participants in adulthood would be of interest to understand the changes in breast composition during this period and its potential link with BC risk.

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Section: Discussionsupporting

confidence: 90%

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

Pereira,

Garmendia,

Leiva

et al. 2024

Breast Cancer Res

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“…As described previously [ 22 , 23 , 26 , 27 ], the resulting OBS output is processed to produce four main chromophore concentrations representing breast tissue volume composition: water, collagen, haemoglobin, and lipids. Herein, the light attenuation percentage of the water (%water) refers to breast density.…”

Section: Methodsmentioning

confidence: 99%

“…All DXA breast density measurements were completed by a trained research assistant following the standard operating procedures described previously [ 17 – 19 , 26 ] and briefly summarized here. Women were required to remove all jewellery and their clothing from the waist up and change into a front-opening hospital gown.…”

Section: Methodsmentioning

confidence: 99%

“…There are several alternative methods of measuring breast density that are safe for women of all ages and also correlate closely with mammographic measures, including magnetic resonance imaging (MRI) [ 15 , 16 ], dual X-ray absorptiometry (DXA) [ 17 – 21 ] and optical breast spectroscopy (OBS) [ 22 – 26 ]. MRI measures breast tissue water content to estimate breast density but unfortunately is not an efficient modality for routine breast density assessment due to accessibility issues, cost and invasiveness.…”

Section: Introductionmentioning

confidence: 99%

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The distribution of breast density in women aged 18 years and older

Perera,

Pirikahu,

Walter

et al. 2024

Breast Cancer Res Treat

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Purpose Age and body mass index (BMI) are critical considerations when assessing individual breast cancer risk, particularly for women with dense breasts. However, age- and BMI-standardized estimates of breast density are not available for screen-aged women, and little is known about the distribution of breast density in women aged < 40. This cross-sectional study uses three different modalities: optical breast spectroscopy (OBS), dual-energy X-ray absorptiometry (DXA), and mammography, to describe the distributions of breast density across categories of age and BMI. Methods Breast density measures were estimated for 1,961 Australian women aged 18–97 years using OBS (%water and %water + %collagen). Of these, 935 women had DXA measures (percent and absolute fibroglandular dense volume, %FGV and FGV, respectively) and 354 had conventional mammographic measures (percent and absolute dense area). The distributions for each breast density measure were described across categories of age and BMI. Results The mean age was 38 years (standard deviation = 15). Median breast density measures decreased with age and BMI for all three modalities, except for DXA-FGV, which increased with BMI and decreased after age 30. The variation in breast density measures was largest for younger women and decreased with increasing age and BMI. Conclusion This unique study describes the distribution of breast density measures for women aged 18–97 using alternative and conventional modalities of measurement. While this study is the largest of its kind, larger sample sizes are needed to provide clinically useful age-standardized measures to identify women with high breast density for their age or BMI.

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“…This information can be used to distinguish bro-glandular stroma from adipose tissue, or healthy tissue from cancerous lesions. Thus, diffuse optical methods can offer a non-invasive, compact, and cost-effective contribution to the detection and classi cation of breast lesions [7][8][9][10][11][12][13][14] , to therapy monitoring 12,[15][16][17][18][19] and to the estimation of breast density 20,21 . In the last decades, the application of DO to these aims has been extensively investigated by several research groups around the world, using different kinds of instrumentations, measurement protocols and data analysis methods 22,23 .…”

Section: Introductionmentioning

confidence: 99%

In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density.

Serra,

Cubeddu,

Maffeis

et al. 2024

Preprint

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In this study, time domain diffuse optical spectroscopy is performed in the range 600–1100 nm on 11 healthy volunteers with a portable system for the quantitative characterization of breast tissue in terms of optical properties and optically-derived blood parameters, tissue constituent concentrations, and scattering parameters. A measurement protocol involving different geometries (reflectance and transmittance), subject’s positions (sitting and lying down), probing locations (outer, lower, and inner breast quadrants), and source-detector distances (2 and 3 cm) allowed us to investigate the effect of tissue heterogeneity and different measurement configurations on the results with the aim of identifying the best experimental conditions for the estimate of breast density (i.e., amount of fibro-glandular tissue in the breast) as a strong independent risk factor for breast cancer. The higher source-detector distance, which probes deeper tissue, retrieves optical outcomes in agreement with higher average density tissue. Similarly, results on the outer quadrants indicate higher density than internal quadrants. These findings are coherent with breast anatomy since the concentration of dense fibro-glandular stroma is higher in deep tissue and towards the external portion of the breast, where the mammary gland is located. The dataset generated with this laboratory campaign is used to device an optimal measurement protocol for a future clinical trial, where optical results will be correlated with conventional mammographic density, allowing us to identify a subset of wavelengths and measurement configurations for an effective estimate of breast density. The final objective is the design of a simplified, compact and cost-effective optical device for a non-invasive, routine assessment of density-associated breast cancer risk.

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Alternative methods to measure breast density in younger women

Cited by 5 publications

References 33 publications

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

Breast composition during and after puberty: the Chilean Growth and Obesity Cohort Study

The distribution of breast density in women aged 18 years and older

In vivo optimization of the experimental conditions for the non-invasive optical assessment of breast density.

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