Effect of preventive hormonal therapy on breast density: a systematic qualitative review

Development of patient-specific 3D-printed breast phantom using silicone and peanut oils for magnetic resonance imaging

Background

Despite increasing reports of 3D printing in medical applications, the use of 3D printing in breast imaging is limited, thus, personalized 3D-printed breast model could be a novel approach to overcome current limitations in utilizing breast magnetic resonance imaging (MRI) for quantitative assessment of breast density. The aim of this study is to develop a patient-specific 3D-printed breast phantom and to identify the most appropriate materials for simulating the MR imaging characteristics of fibroglandular and adipose tissues.

Methods

A patient-specific 3D-printed breast model was generated using 3D-printing techniques for the construction of the hollow skin and fibroglandular region shells. Then, the T1 relaxation times of the five selected materials (agarose gel, silicone rubber with/without fish oil, silicone oil, and peanut oil) were measured on a 3T MRI system to determine the appropriate ones to represent the MR imaging characteristics of fibroglandular and adipose tissues. Results were then compared to the reference values of T1 relaxation times of the corresponding tissues: 1,324.42±167.63 and 449.27±26.09 ms, respectively. Finally, the materials that matched the T1 relaxation times of the respective tissues were used to fill the 3D-printed hollow breast shells.

Results

The silicone and peanut oils were found to closely resemble the T1 relaxation times and imaging characteristics of these two tissues, which are 1,515.8±105.5 and 405.4±15.1 ms, respectively. The agarose gel with different concentrations, ranging from 0.5 to 2.5 wt%, was found to have the longest T1 relaxation times.

Conclusions

A patient-specific 3D-printed breast phantom was successfully designed and constructed using silicone and peanut oils to simulate the MR imaging characteristics of fibroglandular and adipose tissues. The phantom can be used to investigate different MR breast imaging protocols for the quantitative assessment of breast density.

Associations of aspirin and other anti-inflammatory medications with mammographic breast density and breast cancer risk

PURPOSE

We investigated the associations of aspirin and other non-steroid anti-inflammatory drugs with mammographic breast density (MBD) and their interactions in relation to breast cancer risk.

METHODS

This study included 3,675 cancer-free women within the Nurses' Health Study (NHS) and Nurses' Health Study II (NHSII) cohorts. Percent breast density (PD), absolute dense area (DA), and non-dense area (NDA) were measured from digitized film mammograms using a computer-assisted thresholding technique; all measures were square root-transformed. Information on medication use was collected in 1980 (NHS) and 1989 (NHSII) and updated biennially. Medication use was defined as none, past or current; average cumulative dose and frequency were calculated for all past or current users from all bi-annual questionnaires preceding the mammogram date. We used generalized linear regression to quantify associations of medications with MBD. Two-way interactions were examined in logistic regression models.

RESULTS

In multivariate analysis, none of the anti-inflammatory medications were associated with PD, DA, and NDA. We found no interactions of any of the medications with PD with respect to breast cancer risk (all p-interactions > 0.05). However, some of the aspirin variables appeared to have positive associations with breast cancer risk limited only to women with PD 10-24% (past aspirin OR 1.56, 95% CI 1.03-2.35; current aspirin with < 5 years of use OR 1.82, 95% CI 1.01-3.28; current aspirin with ≥ 5 years of use OR 1.89, 95% CI 1.26-2.82).

CONCLUSIONS

Aspirin and NSAIDs are not associated with breast density measures. We found no interactions of aspirin with MBD in relation to breast cancer risk.

Quantitative Measurements of Breast Density Using Magnetic Resonance Imaging: A Systematic Review and Meta-Analysis

Breast density, a measure of dense fibroglandular tissue relative to non-dense fatty tissue, is confirmed as an independent risk factor of breast cancer. Although there has been an increasing interest in the quantitative assessment of breast density, no research has investigated the optimal technical approach of breast MRI in this aspect. Therefore, we performed a systematic review and meta-analysis to analyze the current studies on quantitative assessment of breast density using MRI and to determine the most appropriate technical/operational protocol. Databases (PubMed, EMBASE, ScienceDirect, and Web of Science) were searched systematically for eligible studies. Single arm meta-analysis was conducted to determine quantitative values of MRI in breast density assessments. Combined means with their 95% confidence interval (CI) were calculated using a fixed-effect model. In addition, subgroup meta-analyses were performed with stratification by breast density segmentation/measurement method. Furthermore, alternative groupings based on statistical similarities were identified via a cluster analysis employing study means and standard deviations in a Nearest Neighbor/Single Linkage. A total of 38 studies matched the inclusion criteria for this systematic review. Twenty-one of these studies were judged to be eligible for meta-analysis. The results indicated, generally, high levels of heterogeneity between study means within groups and high levels of heterogeneity between study variances within groups. The studies in two main clusters identified by the cluster analysis were also subjected to meta-analyses. The review confirmed high levels of heterogeneity within the breast density studies, considered to be due mainly to the applications of MR breast-imaging protocols and the use of breast density segmentation/measurement methods. Further research should be performed to determine the most appropriate protocol and method for quantifying breast density using MRI.

The association of mammographic density with risk of contralateral breast cancer and change in density with treatment in the WECARE study

Background

Mammographic density (MD) is an established predictor of risk of a first breast cancer, but the relationship of MD to contralateral breast cancer (CBC) risk is not clear, including the roles of age, mammogram timing, and change with treatment. Multivariable prediction models for CBC risk are needed and MD could contribute to these.

Methods

We conducted a case-control study of MD and CBC risk in phase II of the WECARE study where cases had a CBC diagnosed ≥ 2 years after first diagnosis at age <55 years and controls had unilateral breast cancer (UBC) with similar follow-up time. We retrieved film mammograms of the unaffected breast from two time points, prior to/at the time of the first diagnosis (253 CBC cases, 269 UBC controls) and ≥ 6 months up to 48 months following the first diagnosis (333 CBC cases, 377 UBC controls). Mammograms were digitized and percent MD (%MD) was measured using the thresholding program Cumulus. Odds ratios (OR) and 95% confidence intervals (CI) for association between %MD and CBC, adjusted for age, treatment, and other factors related to CBC, were estimated using logistic regression. Linear regression was used to estimate the association between treatment modality and change in %MD in 467 women with mammograms at both time points.

Results

For %MD assessed following diagnosis, there was a statistically significant trend of increasing CBC with increasing %MD (p = 0.03). Lower density (<25%) was associated with reduced risk of CBC compared to 25 to < 50% density (OR 0.69, 95% CI 0.49, 0.98). Similar, but weaker, associations were noted for %MD measurements prior to/at diagnosis. The relationship appeared strongest in women aged < 45 years and non-existent in women aged 50 to 54 years. A decrease of ≥ 10% in %MD between first and second mammogram was associated marginally with reduced risk of CBC (OR 0.63, 95% CI 0.40, 1.01) compared to change of <10%. Both tamoxifen and chemotherapy were associated with statistically significant 3% decreases in %MD (p < 0.01).

Conclusions

Post-diagnosis measures of %MD may be useful to include in CBC risk prediction models with consideration of age at diagnosis. Chemotherapy is associated with reductions in %MD, similar to tamoxifen.

Electronic supplementary material

The online version of this article (10.1186/s13058-018-0948-4) contains supplementary material, which is available to authorized users.

Raised mammographic density: causative mechanisms and biological consequences

High mammographic density is the most important risk factor for breast cancer, after ageing. However, the composition, architecture, and mechanical properties of high X-ray density soft tissues, and the causative mechanisms resulting in different mammographic densities, are not well described. Moreover, it is not known how high breast density leads to increased susceptibility for cancer, or the extent to which it causes the genomic changes that characterise the disease. An understanding of these principals may lead to new diagnostic tools and therapeutic interventions.

Double-Blind Randomized 12-Month Soy Intervention Had No Effects on Breast MRI Fibroglandular Tissue Density or Mammographic Density

Soy supplementation by patients with breast cancer remains controversial. No controlled intervention studies have investigated the effects of soy supplementation on mammographic density in patients with breast cancer. We conducted a double-blind, randomized, placebo-controlled intervention study in previously treated patients with breast cancer (n = 66) and high-risk women (n = 29). We obtained digital mammograms and breast MRI scans at baseline and after 12 months of daily soy (50 mg isoflavones per day; n = 46) or placebo (n = 49) tablet supplementation. The total breast area (MA) and the area of mammographic density (MD) on the mammogram were measured using a validated computer-assisted method, and mammographic density percent (MD% = 100 × MD/MA) was determined. A well-tested computer algorithm was used to quantitatively measure the total breast volume (TBV) and fibroglandular tissue volume (FGV) on the breast MRI, and the FGV percent (FGV% = 100 × FGV/TBV) was calculated. On the basis of plasma soy isoflavone levels, compliance was excellent. Small decreases in MD% measured by the ratios of month 12 to baseline levels were seen in the soy (0.95) and the placebo (0.87) groups; these changes did not differ between the treatments (P = 0.38). Small decreases in FGV% were also found in both the soy (0.90) and the placebo (0.92) groups; these changes also did not differ between the treatments (P = 0.48). Results were comparable in patients with breast cancer and high-risk women. We found no evidence that soy supplementation would decrease mammographic density and that MRI might be more sensitive to changes in density than mammography.

Minimal impact of adjuvant exemestane or tamoxifen treatment on mammographic breast density in postmenopausal breast cancer patients: a Dutch TEAM trial analysis

BACKGROUND

Mammographic breast density is one of the strongest independent risk factors for developing breast cancer. We examined the effect of exemestane and tamoxifen on breast density in Dutch postmenopausal early breast cancer patients participating in the Tamoxifen Exemestane Adjuvant Multinational (TEAM) trial.

MATERIAL AND METHODS

Analogue mammograms of selected TEAM participants before start, and after one and two (and if available after three) years of adjuvant endocrine therapy were collected centrally and reviewed. Study endpoints were change in breast density over time, and correlations between breast density and locoregional recurrence (LRR), distance recurrence (DR), and contralateral breast cancer (CBC).

RESULTS

Mammograms of 378 patients (181 tamoxifen, 197 exemestane) were included in the current per protocol analyses. Baseline breast density was low (breast density score<50% in 75% of patients) and not different between patients randomised to exemestane or tamoxifen (coefficient 0.16, standard error 0.17). Breast density did not change during treatment in exemestane (p=0.25) or tamoxifen users (p=0.59). No relation was observed between breast density and the occurrence of a LRR [hazards ratio (HR) 0.87, 95% CI 0.45-1.68, p=0.67], a DR (HR 1.02, 95% CI 0.77-1.35, p=0.90), or CBC (HR 1.31, 95% CI 0.63-2.72, p=0.48).

CONCLUSION

The in general low breast density score in early postmenopausal breast cancer patients did not substantially change over time, and this pattern was not different between tamoxifen and exemestane users. Breast density was not a predictive marker for efficacy of adjuvant endocrine therapy.