Mammographic density and estimation of breast cancer risk in intermediate risk population

Associations of Oral Contraceptives with Mammographic Breast Density in Premenopausal Women

BACKGROUND

We investigated the associations of oral contraceptives (OC) with percent breast density (PD), absolute dense area (DA), nondense area (NDA), and a novel image intensity variation (V) measure in premenopausal women.

METHODS

This study included 1,233 controls from a nested case-control study within Nurses' Health Study II cohort. Information on OCs was collected in 1989 and updated biennially. OC use was defined from the questionnaire closest to the mammogram date. PD, DA, and NDA were measured from digitized film mammograms using a computer-assisted thresholding technique; the V measure was obtained with a previously developed algorithm measuring the SD of pixel values in the eroded breast region. Generalized linear regression was used to assess associations between OCs and density measures (square root-transformed PD, DA, and NDA, and -untransformed V).

RESULTS

OC use was not associated with PD [current vs. never: β = -0.06; 95% confidence interval (CI), -0.37-0.24; past vs. never: β = 0.10; 95% CI, -0.09-0.29], DA (current vs. never: β = -0.20; 95% CI -0.59-0.18; past vs. never: β = 0.13; 95% CI, -0.12-0.39), and NDA (current vs. never: β = -0.19; 95% CI, -0.56-0.18; past vs. never: β = -0.01; 95% CI, -0.28-0.25). Women with younger age at initiation had significantly greater V-measure (<20 years vs. never: β = 26.88; 95% CI, 3.18-50.58; 20-24 years vs. never: β = 20.23; 95% CI, -4.24-44.71; 25-29 years vs. never: β = 2.61; 95% CI -29.00-34.23; ≥30 years vs. never: β = 0.28; 95% CI, -34.16-34.72, P _trend = 0.03).

CONCLUSIONS

Our findings suggest that an earlier age at first OC use was associated with significantly greater V.

IMPACT

These findings could guide decisions about the age for OC initiation.

Comparison of breast density assessment between human eye and automated software on digital and synthetic mammography: Impact on breast cancer risk

PURPOSE

To evaluate the agreement between automatic assessment software of breast density based on artificial intelligence (AI) and visual assessment by a senior and a junior radiologist, as well as the impact on the assessment of breast cancer risk (BCR) at 5 years.

MATERIALS AND METHODS

We retrospectively included 311 consecutive women (mean age, 55.6±8.5 [SD]; range: 40-74 years) without a personal history of breast cancer who underwent routine mammography between January 1, 2019 and February 28, 2019. Mammographic breast density (MBD) was independently evaluated by a junior and a senior reader on digital mammography (DM) and synthetic mammography (SM) using BI-RADS (5th edition) and by an AI software. For each MBD, BCR at 5 years was estimated per woman by the AI software. Interobserver agreement for MBD between the two readers and the AI software were evaluated by quadratic κ coefficients. Reproducibility of BCR was assessed by intraclass correlation coefficient (ICC).

RESULTS

Agreement for MBD assessment on DM and SM was almost perfect between senior and junior radiologists (κ=0.88 [95% CI: 0.84-0.92] and κ=0.86 [95% CI: 0.82-0.90], respectively) and substantial between the senior radiologist and AI (κ=0.79; 95% CI: 0.73-0.84). There was substantial agreement between DM and SM for the senior radiologist (κ=0.79; 95% CI: 0.74-0.84). BCR evaluation at 5 years was highly reproducible between the two radiologists on DM and SM (ICC=0.98 [95% CI: 0.97-0.98] for both), between BCR evaluation based on DM and SM evaluated by the senior (ICC=0.96; 95% CI: 0.95-0.97) or junior radiologist (ICC=0.97; 95% CI: 0.96-0.98) and between the senior radiologist and AI (ICC=0.96; 95% CI: 0.95-0.97).

CONCLUSION

This preliminary study demonstrates a very good agreement for BCR evaluation based on the evaluation of MBD by a senior radiologist, junior radiologist and AI software.

Exploring Association of Breast Pain, Pregnancy, and Body Mass Index with Breast Tissue Elasticity in Healthy Women: Glandular and Fat Differences

Breast sonoelastography is a relatively novel ultrasound (US) method that enables estimation of tissue stiffness to estimate the elasticity of normal breast tissue and seek to correlate it with well-known breast cancer risk factors. Two hundred women of different age were included in the study and completed a questionnaire about personal, familiar, and reproductive history. Glandular and fatty tissue elasticity in all breast quadrants was measured by shear wave elastography (SWE). Mean elastographic values of breast tissue were calculated and compared to personal history risk factors. Elasticity of normal glandular tissue (66.4 kilopascals (kPa)) was higher than fatty tissue (26.1 kPa) in all breast quadrants and in both breasts. Lower outer quadrant (LOQ) had the lowest elasticity values of both parenchyma and fat. Higher elasticity values of breast tissue were confirmed in the left breast than in the right breast. Glandular and fat tissue elasticity negatively correlated with body mass index (BMI). Women with mastodynia had higher glandular elastographic values compared to subjects without breast pain. Nuliparity was also associated with higher elasticity of glandular breast tissue. The results of this study are promising and could, over time, contribute to a better understanding of glandular breast tissue elasticity as a potential risk factor for breast cancer.

Density of breast: An independent risk factor for developing breast cancer, a prospective study at two premium breast centers

Background

Breast cancer is the leading cause of death among women worldwide. Studies have identified breast density as a controversial risk factor of breast cancer. Moreover, studies found that breast density reduction through Tamoxifen could reduce risk of breast cancer significantly. To date, no study on the association between breast density and breast cancer has been carried out in Malaysia. If breast density is proven to be a risk factor of breast cancer, intervention could be carried out to reduce breast cancer risk through breast density reduction.

Purpose

To determine if density of breast is an independent risk factor which will contribute to development of breast cancer.

Materials and Methods

A prospective cohort study is carried out in two hospitals targeting adult female patients who presented to the Breast Clinic with symptoms suspicious of breast cancer. Participants recruited were investigated for breast cancer based on their symptoms. Breast density assessed from mammogram was correlated with tissue biopsy results and final diagnosis of benign or malignant breast disease.

Results

Participants with dense breasts showed 29% increased risk of breast cancer when compared to those with almost entirely fatty breasts (odds ratio [OR] 1.29, 95% CI 0.38‐4.44, P = .683). Among the postmenopausal women, those with dense breasts were 3.1 times more likely to develop breast cancer compared with those with fatty breasts (OR 3.125, 95% CI 0.72‐13.64, P = .13). Moreover, the chance of developing breast cancer increases with age (OR 1.046, 95% CI 1.003‐1.090, P < .05). In contrast, the density of breast decreases with increasing age (P < .05) and body mass index (P = .051). The proportion of high breast density whether in the whole sample size, premenopausal, or postmenopausal group was consistently high.

Conclusion

Although results were not statistically significant, important association between breast density and risk of breast cancer cannot be ruled out. The study is limited by a small sample size and subjective assessment of breast density. More studies are required to reconcile the differences between studies of contrasting evidence.

Mammographic Density Distribution in Ras Al Khaimah (RAK): Relationships with Demographic and Reproductive Factors

Objective:

Mammographic density is an important risk factor for breast cancer and determines to a large extent mammographic screening efficacy. This study aims to provide baseline data for mammographic density profiling of women living in Ras Al Khaimah (RAK) and to identify risk factors associated with high mammographic density.

Methods:

A cross-sectional design was used to examine a series of 366 mammography cases. The Breast Imaging Reporting and Data System (BI-RADS, 5th edition) was used to evaluate mammographic density. Pearson’s chi-squared, Mann-Whitney U test and multivariate logistic regression were used for statistical analysis.

Results:

Most participants (67%) fell into BI-RADS b and c mammographic density categories. Of the total sample, women who were aged ≤ 45 years (p=0.004, OR=1.9), weighed ≤ 71kg (p=<0.0001, OR=4.8), had a body mass index of ≤ 27 kg/m² (p=<0.0001, OR=5.1) and were of non-Arab descent (p=0.007, OR=1.8) were significantly more likely to have denser breast tissue. Adjusted ethnicity regression analysis showed that Emirati women were significantly less likely to have dense breast tissue compared with Western women (p=0.04, OR=0.4). Among the sample of survey participants, increased odds of having mammographic density were among women who were full-time workers (p=0.02, OR=2.8), of Christian faith (p=0.007, OR=4.4), nulliparous (p=0.003, OR=10.8), had three or fewer children (p=0.03, OR=3.8), and had used oral contraceptives for three years or more (p=0.01, OR=6.1).

Conclusion:

This study indicated that because Emirati women have a low mammographic density profile, screening mammography can be considered as an effective early detection imaging modality.

Comparison of inter- and intra-observer variability of breast density assessments using the fourth and fifth editions of Breast Imaging Reporting and Data System

Background

Breast density is a well-known independent risk factor for breast cancer and can significantly affect the sensitivity of screening mammograms.

Objective

We aimed to evaluate the intra- and inter-observer consistencies of breast density assessments using methods outlined in the fourth and fifth editions of the American College of Radiology (ACR) Breast Imaging Reporting and Data System (BI-RADS) guidelines to determine which method is more reliable.

Materials and methods

Three radiologists with subspecialties in breast imaging defined breast density in 72 mammograms four times each: twice using the fourth edition of the ACR BI-RADS guidelines and twice using the fifth edition. The intra- and inter-observer agreements were calculated and compared for each method.

Results

The weighted kappa values for the overall intra-observer agreement were 0.955 (95% confidence interval [CI]: 0.931–0.980) and 0.938 (95% CI: 0.907–0.968) when breast densities were assessed according to criteria outlined in the fourth and fifth ACR BI-RADS editions, respectively. The difference between these values was not statistically significant (p = .4). The overall Fleiss-Cohen (quadratic) weighted kappa for inter-observer agreement were 0.623 (95% CI: 0.517–0.729) and 0.702 (95% CI: 0.589–0.815) when breast densities were assessed according to criteria outlined in the fourth and fifth ACR BI-RADS editions, respectively. The difference between these values was not statistically significant (p = .32). Similarly, there were no significant differences in the evaluation of breast density (overall) when comparing breast density assignment using criteria outlined in the fourth and fifth ACR BI-RADS edition (p = .582).

Conclusion

The ACR BI-RADS guideline is an acceptable method to classify breast density, resulting in substantial inter-observer agreements using criteria outlined in both the fourth and fifth editions. The intra-observer agreement was nearly perfect for radiologists using criteria outlined in both sets of guidelines. Moreover, although the percentage of women who were classified as having dense breasts was higher when radiologists used the fifth edition of ACR BI-RADS guidelines than when they used the fourth edition, this difference was not statistically significant.

Breast cancer in South-Eastern European countries since 2000: Rising incidence and decreasing mortality at young and middle ages

BACKGROUND

Marked variations exist in the incidence and mortality trends of major cancers in South-Eastern European (SEE) countries which have now been detailed by age for breast cancer (BC) to seek clues for improvement.

METHODS

We brought together and analysed data from 14 cancer registries (CRs), situated in SEE countries or directly adjacent. Age-standardised rate at world standard (ASRw) and truncated incidence and mortality rates during 2000-2010 by year, and for four age groups, were calculated. Average annual percentage change of rates was estimated using Joinpoint regression.

RESULTS

Annual incidence rates increased significantly in countries and age groups, by 2-4% (15-39 years), 2-5% (40-49), 1-4% (50-69) and 1-6% (at 70+). Mortality rates decreased significantly in all age-groups in most countries, but increased up to 5% annually above age 55 in Ukraine, Serbia, Moldova and Cyprus. The BC data quality was evaluated by internationally agreed indicators which appeared suboptimal for Moldova, Bosnia and Herzegovina and Romania.

CONCLUSION

The observed variations of incidence trends reflect the influence of risk factors, as well as levels of early detection activities (screening). While mortality rates were mostly decreasing, probably due to improved cancer care and introduction of more effective systemic treatment regimens, the worrying increasing mortality trends in the 55-plus age groups in some countries have to be addressed by health professionals and policymakers. In order to assess and monitor the effects of cancer control activities in the region, the CRs need substantial investments.

Breast Density and Breast Cancer Incidence in the Lebanese Population: Results from a Retrospective Multicenter Study

Purpose

To study the distribution of breast mammogram density in Lebanese women and correlate it with breast cancer (BC) incidence.

Methods

Data from 1,049 women who had screening or diagnostic mammography were retrospectively reviewed. Age, menopausal status, contraceptives or hormonal replacement therapy (HRT), parity, breastfeeding, history of BC, breast mammogram density, and final BI-RADS assessment were collected. Breast density was analyzed in each age category and compared according to factors that could influence breast density and BC incidence.

Results

120 (11.4%) patients had BC personal history with radiation and/or chemotherapy; 66 patients were postmenopausal under HRT. Mean age was 52.58 ± 11.90 years. 76.4% of the patients (30–39 years) had dense breasts. Parity, age, and menopausal status were correlated to breast density whereas breastfeeding and personal/family history of BC and HRT were not. In multivariate analysis, it was shown that the risk of breast cancer significantly increases 3.3% with age (P = 0.005), 2.5 times in case of menopause (P = 0.004), and 1.4 times when breast density increases (P = 0.014).

Conclusion

Breast density distribution in Lebanon is similar to the western society. Similarly to other studies, it was shown that high breast density was statistically related to breast cancer, especially in older and menopausal women.

Mammographic breast density in women with premature ovarian failure: a prospective analysis

OBJECTIVE

This study aims to compare breast density between two mammograms in women with premature ovarian failure (POF).

METHODS

A cohort study evaluated 56 women with POF. Two mammograms performed at least 2 years apart were analyzed. Mammogram films were digitalized, and images were assessed using a computer-assisted method; the percentage of breast image that is radiologically dense is referred to as the percentage of mammographic density (PMD). Age at menarche, age at onset of POF, length of POF, length of estrogen-progestin therapy (EPT), body mass index (BMI), pregnancy, and age at the time of each mammogram were evaluated.

RESULTS

The mean (SD) age at POF diagnosis was 32.35 (5.95) years. In the first mammogram, the mean (SD) age, BMI, and length of POF were 37.58 (3.72) years, 26.79 (4.86) kg/m, and 5.25 (4.61) years, respectively. EPT had been used for a mean (SD) of 2.71 (3.12) years. In the second mammogram, the mean (SD) age, BMI, and length of POF were 43.23 (4.98) years, 27.6 (5.39) kg/m, and 10.5 (5.11) years, respectively. EPT had been used for a mean (SD) of 7.25 (4.6) years. The mean (SD) interval between mammograms was 5.25 (3) years, and the mean (SD) PMD decreased from 27.78% (21.04%) to 17.53% (15.71%) (P = 0.007). Comparing PMD between women taking EPT and those not taking EPT, we observed no significant differences. In both instances, multiparous women had lower PMD than nulliparous women (P < 0.05). BMI, length of POF, and pregnancy were negatively correlated with PMD.

CONCLUSIONS

Breast density in young women with POF decreases across a period of 5 years, regardless of EPT use. Further studies may elucidate how this result will correlate with decision-making in clinical therapeutics and breast cancer risk in POF.

Breast cancer in European Union: an update of screening programmes as of March 2014 (review)

Breast cancer, a major cause of female morbidity and mortality, is a global health problem; 2008 data show an incidence of ~450,000 new cases and 140,000 deaths (mean incidence rate 70.7 and mortality rate 16.7, world age-standardized rate per 100,000 women) in European Union Member States. Incidence rates in Western Europe are among the highest in the world. We review the situation of BC screening programmes in European Union. Up to date information on active BC screening programmes was obtained by reviewing the literature and searching national health ministries and cancer service websites. Although BC screening programmes are in place in nearly all European Union countries there are still considerable differences in target population coverage and age and in the techniques deployed. Screening is a mainstay of early BC detection whose main weakness is the rate of participation of the target population. National policies and healthcare planning should aim at maximizing participation in controlled organized screening programmes by identifying and lowering any barriers to adhesion, also with a view to reducing healthcare costs.