Dense Volume Research Articles

Circulating sex hormones and volumetric breast density: A prospective study in women from the EPIC Florence cohort

AbstractMammographic breast density (MBD) is a known risk factor for breast cancer. This study aimed to evaluate prospectively how circulating levels of sex hormones and sex hormones binding globulin (SHBG) are associated with volumetric percent density (VPD, %) and absolute breast dense volume (DV, cm3) measured after an average 13.5 years of follow up. We included 422 post‐ and 445 pre‐menopausal women enrolled in the Florence section of the European Prospective Investigation into Cancer and Nutrition study. Blood levels of circulating sex hormones and SHBG were determined in serum samples collected at enrollment. The automated Volpara™ density software was used to obtain DV and VPD measures from the first available full‐field digital mammography performed after enrollment. We carried out adjusted linear regression models for post‐menopausal and pre‐menopausal women, separately. Higher baseline blood levels of SHBG were associated with higher VPD both in post‐menopausal (%Diff 17.2 III vs. I tertile, p‐value 0.02, p‐trend 0.02) and pre‐menopausal women (%Diff 21.1 III vs. I tertile, p‐value 0.004, p‐trend 0.004). Among pre‐menopausal women a modifying effect of parity emerged, with significant inverse associations of estradiol, free estradiol, estrone, and free testosterone with VPD in women with a lower number of births or higher age at every birth. DV was not associated with sex hormones or SHBG. A direct association between increasing serum level of SHBG and VPD was observed both in post‐ and pre‐menopausal women. This association need to be further investigated in order to better understand the underlying mechanisms.

Mammographic density in relation to breast cancer risk factors among Chinese women.

Background Increased mammographic density (MD) is a known breast cancer (BC) risk factor, but its influencing factors are unclear in Asian populations. This study examined the links between known BC risk factors and quantitatively measured MD in 7,351 Chinese women with non-malignant mammographic findings. Methods VolparaDensity software quantified volumetric MD measures: total breast (TBV), absolute dense (ADV), percent dense (PDV= ADV/TBV), and non-dense volumes (NDV= TBV-ADV). Multivariable linear regression models assessed associations between these MD metrics and BC risk factors. Results The mean age of the population was 50.1 (SD=8.3) years. The mean ADV, NDV, and PDV were 58.4 (SD=32.1), 382.8 (SD=202.0) cm³ and 14.8 (SD=7.1) %, respectively. PDV was inversely associated with age, weight, body mass index (BMI), parity, breastfeeding duration, and postmenopausal status, but positively linked to height and age at menopause. NDV showed opposite associations. ADV had similar associations to PDV, except for height, weight, and BMI, which differed for women with the lowest NDV. PDV associations with age at menarche, age at first birth, and breastfeeding duration varied by BMI and menopausal status. Conclusions MD may influence the relationship between reproductive factors and BC risk, depending on MD measure, menopausal status, and BMI. Impact This study examines how quantitative MD measures relate to known BC risk factors in an East Asian population, factoring in menopausal status and BMI. The results underscore the complex role of MD and confounding factors in BC risk, highlighting the need for tailored insights for future research and screening.

Volumetric Breast Density Estimation From Three-Dimensional Reconstructed Digital Breast Tomosynthesis Images Using Deep Learning.

Breast density is a widely established independent breast cancer risk factor. With the increasing utilization of digital breast tomosynthesis (DBT) in breast cancer screening, there is an opportunity to estimate volumetric breast density (VBD) routinely. However, current available methods extrapolate VBD from two-dimensional (2D) images acquired using DBT and/or depend on the existence of raw DBT data, which is rarely archived by clinical centers because of storage constraints. We retrospectively analyzed 1,080 nonactionable three-dimensional (3D) reconstructed DBT screening examinations acquired between 2011 and 2016. Reference tissue segmentations were generated using previously validated software that uses 3D reconstructed slices and raw 2D DBT data. We developed a deep learning (DL) model that segments dense and fatty breast tissue from background. We then applied this model to estimate %VBD and absolute dense volume (ADV) in cm3 in a separate case-control sample (180 cases and 654 controls). We created two conditional logistic regression models, relating each model-derived density measurement to likelihood of contralateral breast cancer diagnosis, adjusted for age, BMI, family history, and menopausal status. The DL model achieved unweighted and weighted Dice scores of 0.88 (standard deviation [SD] = 0.08) and 0.76 (SD = 0.15), respectively, on the held-out test set, demonstrating good agreement between the model and 3D reference segmentations. There was a significant association between the odds of breast cancer diagnosis and model-derived VBD (odds ratio [OR], 1.41 [95 % CI, 1.13 to 1.77]; P = .002), with an AUC of 0.65 (95% CI, 0.60 to 0.69). ADV was also significantly associated with breast cancer diagnosis (OR, 1.45 [95% CI, 1.22 to 1.73]; P < .001) with an AUC of 0.67 (95% CI, 0.62 to 0.71). DL-derived density measures derived from 3D reconstructed DBT images are associated with breast cancer diagnosis.

Benchmarking forcefields for molecular dynamics simulations of polyamide-based reverse-osmosis membranes

Molecular dynamics simulations offer unique insights about solvent and solute transport through the active layer of reverse-osmosis membranes at sub-nanometer to nanometer length scales. Over the last two decades, several cross-linked polyamide membranes, formed by trimesoyl chloride and m-phenylenediamine, have been simulated with different forcefields and water models. However, a clear rationale for choosing a forcefield-water combination is missing. In this work, the accuracy of eleven forcefield-water combinations is evaluated by a direct comparison of properties against experimentally synthesized polyamide membranes with similar chemical compositions. Overall, six forcefields and three water models are compared. The polyamide membranes are simulated in equilibrium in both dry and hydrated states, as well as in a non-equilibrium reverse osmosis. The best-performing forcefields predicted the experimental pure water permeability of 3D printed polyamide membranes within a 95 % confidence interval. Finally, the best forcefield was used to elucidate membrane properties for a range of desalination conditions. At experimentally relevant pressure pure-water permeability was validated and dense interconnected free volume regions (pores) were observed in the membrane that connected feed- and permeate-side. The desalination studies demonstrated increased salt partitioning with feed-side pressure, however, at very high pressures partitioning decreased due to membrane compaction.

Percentage mammographic density or absolute breast density for risk stratification in breast screening: Possible implications for socioeconomic health disparity.

Obesity levels and mortality from breast cancer are higher in more deprived areas of the UK, despite lower breast cancer incidence. Supplemental imaging for women with dense breasts has been proposed as a potential improvement to screening, but it is not clear how stratification by percentage mammographic density (%MD) would be reflected across socioeconomic groups. This study aims to clarify the associations between breast composition (dense and fatty tissue) and socioeconomic status in a multi-ethnic screening population. Demographic characteristics were collected for 62,913 participants in a UK breast screening programme (age, ethnicity, Index of Multiple Deprivation (IMD)). Automated mammographic measurements were derived: dense volume (DV), non-dense volume (NDV) and percent density (%MD). Correlations between deprivation and mammographic composition were examined before and after adjustment for age, ethnicity and NDV, using non-dense breast volume as a proxy for body mass index (BMI). There was negligible correlation between deprivation and DV (r = 0.017; P < 0.001 in all cases), but NDV increased with increasing deprivation (Pearson r = 0.101). Correlations were weaker in the Asian and Chinese ethnic groups. %MD decreased with deprivation (r = -0.094) and adjustment for ethnicity did not alter the association between %MD and IMD (relative change, most to least deprived quintile IMD: 1.18; 95% confidence interval: 1.16, 1.21). Deprivation-related differences in %MD in the screening population are largely explained by differences in breast fat volume (NDV) which reflects BMI. Women in more deprived areas, where obesity and breast cancer mortality rates are higher, have increased breast adiposity and may miss out on risk-adapted screening if stratification is based solely on %MD or BIRADS classification.

PFAS Levels, Early Life Factors, and Mammographic Breast Density in Premenopausal Women.

Mammographic breast density (MBD) is a strong risk factor and an intermediate phenotype for breast cancer, yet there are limited studies on how environmental pollutants are associated with MBD. We investigated associations of perfluorooctane sulfonate (PFOS), perfluorooctanoic acid (PFOA), and perfluorohexane sulfonate (PFHxS) levels with measures of MBD and evaluated if early life factors modified any associations. Metabolon performed metabolomics analysis using ultrahigh-performance liquid chromatography/tandem accurate mass spectrometry in fasting blood from 705 premenopausal women completing their annual screening mammogram in St. Louis, Missouri. We calculated least square means (LSM) of mammographic volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV) by quartiles (Q) of PFOS, PFOA, and PFHxS from multivariable linear regression modeling overall and stratified by recruitment period, race, age at menarche, and body shape at age 10. Models were adjusted for age, age at menarche, body fat percentage, race, family history of breast cancer, oral contraceptive use, alcohol consumption, parity/age at first birth, and body shape at age 10. PFOS, PFOA, and PFHxS were not significantly associated with VPD or NDV. PFHxS was significantly positively associated with DV (, , , ; ). PFOS was positively associated with DV (, , , ; ) with DV being 8.1%, 12%, and 12.3% higher in Q2, Q3, and Q4 compared to Q1. Among women who were underweight/normal weight at age 10, PFOS was positively associated with VPD (, , , ; ) while there was an inverse association among women who were overweight/obese at age 10 (, , , ; ) (). We report novel associations of PFHxS and PFOS with DV in premenopausal women. PFOS, PFOA, and PFHxS were not associated with VPD and NDV. In addition, body shape at age 10 may modify the associations of PFOS with MBD. Further studies are needed to validate our findings and to evaluate the associations of other per- and polyfluoroalkyl substances (PFAS), as well as mixtures of PFAS, with MBD. https://doi.org/10.1289/EHP14065.

Associations between quantitative measures of mammographic density and terminal ductal lobular unit involution in Chinese breast cancer patients

BackgroundHigher mammographic density (MD), a radiological measure of the proportion of fibroglandular tissue in the breast, and lower terminal duct lobular unit (TDLU) involution, a histological measure of the amount of epithelial tissue in the breast, are independent breast cancer risk factors. Previous studies among predominantly white women have associated reduced TDLU involution with higher MD.MethodsIn this cohort of 611 invasive breast cancer patients (ages 23–91 years [58.4% ≥ 50 years]) from China, where breast cancer incidence rates are lower and the prevalence of dense breasts is higher compared with Western countries, we examined the associations between TDLU involution assessed in tumor-adjacent normal breast tissue and quantitative MD assessed in the contralateral breast obtained from the VolparaDensity software. Associations were estimated using generalized linear models with MD measures as the outcome variables (log-transformed), TDLU measures as explanatory variables (categorized into quartiles or tertiles), and adjusted for age, body mass index, parity, age at menarche and breast cancer subtype.ResultsWe found that, among all women, percent dense volume (PDV) was positively associated with TDLU count (highest tertile vs. zero: Expbeta = 1.28, 95% confidence interval [CI] 1.08–1.51, ptrend = < .0001), TDLU span (highest vs. lowest tertile: Expbeta = 1.23, 95% CI 1.11–1.37, ptrend = < .0001) and acini count/TDLU (highest vs. lowest tertile: Expbeta = 1.22, 95% CI 1.09–1.37, ptrend = 0.0005), while non-dense volume (NDV) was inversely associated with these measures. Similar trend was observed for absolute dense volume (ADV) after the adjustment of total breast volume, although the associations for ADV were in general weaker than those for PDV. The MD-TDLU associations were generally more pronounced among breast cancer patients ≥ 50 years and those with luminal A tumors compared with patients < 50 years and with luminal B tumors.ConclusionsOur findings based on quantitative MD and TDLU involution measures among Chinese breast cancer patients are largely consistent with those reported in Western populations and may provide additional insights into the complexity of the relationship, which varies by age, and possibly breast cancer subtype.

Effect of colchicine on progression of known coronary atherosclerosis in patients with STable CoROnary artery disease CoMpared to placebo (EKSTROM) trial—rationale and design

BackgroundCardiovascular disease is the major cause of mortality in the United States. Despite lifestyle modification and traditional risk factor control residual inflammatory risk remains an untreated concern. Colchicine is an oral, medication that has been used for gout, mediterranean fever and pericarditis for decades. In recent trials, colchicine has been shown to reduce major adverse cardiovascular events, however the mechanism of benefit remains unclear. The objective of the randomized, double-blind, placebo controlled EKSTROM trial is to evaluate the effects of colchicine 0.5mg/day on atherosclerotic plaque. MethodsEighty-four participants will be enrolled after obtaining informed consent and followed for 12 months. Eligible patients will be randomly assigned to colchicine 0.5mg/day or placebo in a 1:1 fashion as add-on to their standard of care. All participants will undergo coronary computed tomography angiography (CCTA) at baseline and at 12 months. ResultsAs of November 2023, the study is 100% enrolled with an expected end of study by the second quarter of 2024. The primary endpoint is change in low attenuation plaque volume as measured by CCTA. Secondary endpoints include change in volume of different plaque types (including total atheroma volume, noncalcified plaque volume, dense calcified plaque volume, remodeling index), change in inflammatory markers (IL-6, IL-1β, IL-18, hs-CRP), change in pericoronary adipose tissue attenuation, change in epicardial adipose tissue volume and attenuation and change in brachial flow mediated dilation. ConclusionEKSTROM is the first randomized study to assess the effects of colchicine on plaque progression, pericoronary and epicardial fat. EKSTROM will provide important information on the mechanistic effects of colchicine on the cardiovascular system. Trial registrationRegistry: clinicaltrials.gov, Registration Number: NCT06342609 url: https://www.clinicaltrials.gov/study/NCT06342609?term=EKSTROM&rank=1

Hollow fiber thin-film composite membrane regulated by macrocyclic polyamine molecules for high performance organic solvent nanofiltration

Organic solvent nanofiltration (OSN) technology has the potential to separate and purify organic solvents in high efficiency. The self-supporting structure and ease scaling-up merit of hollow fiber (HF) type membrane make it an attractive option for OSN application. Nevertheless, low solvent permeance is one of technical limitation in conventional HF OSN membranes due to their excessively dense separation layer and limited free volume. Herein, we propose a straightforward methodology to fabricate HF thin-film composite (TFC) OSN membranes having exceptional solvent permeance and solute rejection. This methodology is conducted through the incorporation of macrocyclic molecules, 1,4,7,10-tetraazacyclododecane (Cyclen), into the aqueous monomer solution of m-Phenylenediamine (MPD) during the interfacial polymerization to modulate the separation layer. In this way, the average pore size of the separation layer could be precisely enlarged and narrowed on a sub-nanometer scale. Consequently, the Cyclen-modulated HF TFC OSN membrane exhibits excellent separation performance, with a pure methanol permeance of 76.7 L m−2 h−1 MPa−1 and a pure ethanol permeance of 26.5 L m−2 h−1 MPa−1, which is nearly 60 % increase compared with the baseline TFC membrane, while the Rhodamine B (RDB) rejection only shows a neglectable decrease from 99.7 % to 99.6 % at optimal fabrication conditions. Furthermore, the optimal membrane exhibits remarkable solvent resistance, withstanding a 35 d immersion in N, N-dimethylformamide (DMF) at room temperature without a significant decline in RDB rejection. Additionally, the optimal membrane shows higher than 99 % rejection for Rifampicin (823 Da), which is considerable potential for applications in the separation and recovery of pharmaceuticals. In summary, incorporating macrocyclic polyamine Cyclen into the polyamide layer is a viable method for regulating the physical structure and strengthening the performance of HF OSN membrane.

Aspirin Metabolites and Mammographic Breast Density in Premenopausal Women.

Studies investigating the associations of self-reported aspirin use and mammographic breast density (MBD) have reported conflicting results. Therefore, we investigated the associations of aspirin metabolites with MBD in premenopausal women. We performed this study on 705 premenopausal women who had a fasting blood draw for metabolomic profiling. We performed covariate-adjusted linear regression models to calculate the least square means of volumetric measures of MBD [volumetric percent density (VPD), dense volume (DV), and nondense volume (NDV)] by quartiles of aspirin metabolites [salicyluric glucuronide, 2-hydroxyhippurate (salicylurate), salicylate, and 2,6-dihydroxybenzoic acid]. Approximately 13% of participants reported taking aspirin in the past 12 months. Aspirin users had higher levels of 2-hydroxyhippurate (salicylurate), salicylate, and salicyluric glucuronide (peak area) than nonusers, but only the mean peak area of salicyluric glucuronide was increased by both dose (1-2 tablets per day = 1,140,663.7 and ≥3 tablets per day = 1,380,476.0) and frequency (days per week: 1 day = 888,129.3, 2-3 days = 1,199,897.9, and ≥4 days = 1,654,637.0). Aspirin metabolites were not monotonically associated with VPD, DV, or NDV. Given the null results, additional research investigating the associations of aspirin metabolites in breast tissue and MBD is necessary. Impact: Elucidating the determinants of MBD, a strong risk factor for breast cancer, can play an important role in breast cancer prevention. Future studies should determine the associations of nonaspirin NSAID metabolites with MBD.

Association of area- and volumetric-mammographic density and breast cancer risk in women of Asian descent: a case control study

BackgroundMammographic density (MD) has been shown to be a strong and independent risk factor for breast cancer in women of European and Asian descent. However, the majority of Asian studies to date have used BI-RADS as the scoring method and none have evaluated area and volumetric densities in the same cohort of women. This study aims to compare the association of MD measured by two automated methods with the risk of breast cancer in Asian women, and to investigate if the association is different for premenopausal and postmenopausal women.MethodsIn this case–control study of 531 cases and 2297 controls, we evaluated the association of area-based MD measures and volumetric-based MD measures with breast cancer risk in Asian women using conditional logistic regression analysis, adjusting for relevant confounders. The corresponding association by menopausal status were assessed using unconditional logistic regression.ResultsWe found that both area and volume-based MD measures were associated with breast cancer risk. Strongest associations were observed for percent densities (OR (95% CI) was 2.06 (1.42–2.99) for percent dense area and 2.21 (1.44–3.39) for percent dense volume, comparing women in highest density quartile with those in the lowest quartile). The corresponding associations were significant in postmenopausal but not premenopausal women (premenopausal versus postmenopausal were 1.59 (0.95–2.67) and 1.89 (1.22–2.96) for percent dense area and 1.24 (0.70–2.22) and 1.96 (1.19–3.27) for percent dense volume). However, the odds ratios were not statistically different by menopausal status [p difference = 0.782 for percent dense area and 0.486 for percent dense volume].ConclusionsThis study confirms the associations of mammographic density measured by both area and volumetric methods and breast cancer risk in Asian women. Stronger associations were observed for percent dense area and percent dense volume, and strongest effects were seen in postmenopausal individuals.

Quantitative coronary computed tomography assessment for differentiating between total occlusions and severe stenoses

BackgroundsThe impact of quantitative assessment to differentiate total occlusions (TOs) from severe stenoses on coronary computed tomography angiography (CCTA) remains unknown. ObjectiveThis study investigated whether quantitative characteristics assessed on CCTA could help differentiate a TO from a severe stenosis on invasive coronary angiography (ICA). MethodsThis study is a sub-analysis of the FASTTRACK CABG (NCT04142021) in which both CCTA and ICA were routinely performed. Quantitative analysis was performed with semi-automated CCTA plaque-analysis software. Blinded analysts compared TOs on CCTA, defined as a complete lack of contrast opacification within the coronary occlusion, with corresponding ICA. ResultsEighty-four TOs were seen on CCTA in 59 of the 114 patients enrolled in the trial. The concordance in diagnosing a TO between ICA and CCTA was 56.0% (n ​= ​47). Compared to severe stenoses, TOs had a significantly longer lesion length (25.1 ​± ​23.0 ​mm vs 9.4 ​± ​11.2 ​mm, P ​< ​0.001). The best cut-off value to differentiate a TO from severe stenosis was a lesion length of 5.5 ​mm (area under the curve 0.77, 95% CI: 0.66–0.87), with a 91.1% sensitivity and 61.1% specificity. Dense calcium percentage atheroma volume (PAV) was significantly higher in TOs compared to severe stenoses (18.7 ​± ​19.6% vs. 6.6 ​± ​13.0%, P ​< ​0.001), whilst the opposite was seen for fibro-fatty PAV (31.3 ​± ​14.2% vs. 19.5 ​± ​10.5%, P ​< ​0.001). On a multivariable logistic regression analysis, lesion length (>5.5 ​mm) was the only parameter associated with differentiating a TO from a severe stenosis. ConclusionIn quantitative CCTA analysis, a lesion length >5.5 ​mm was the only independent predictor differentiating a TO from a severe stenosis. NCT registration numberNCT04142021.

Abstract PS10-06: Contribution of a breast cancer polygenic risk score to mammography artificial intelligence models and breast density for long term breast cancer risk prediction

Abstract Artificial intelligence (AI) models based on deep learning of mammogram images have been developed for lesion detection and diagnosis as well as breast cancer (BC) risk. We and others have shown that these AI models, coupled with breast density, predict long-term breast cancer risk. Common germline genetic variation, in particular a polygenic risk score (PRS) that captures the cumulative impact of hundreds of common risk variants, has been shown associated with 3-fold increased BC risk. The BC-PRS may complement imaging risk factors to improve identification of women at high BC risk and better target prevention strategies. We evaluated the contribution of a BC-PRS to two imaging-based AI models (Transpara AI cancer detection system and Mirai 5-year risk) and breast density measures to long-term BC risk. We hypothesized that the BC-PRS will improve long-term risk prediction above AI and density measures. We examined this hypothesis within a cohort of 10,271 women enrolled to the Mayo Clinic Biobank between 2009 and 2015. Eligible women had no prior cancer, were ages 35 to 85, had a full-field digital screening mammogram within two years of enrollment and genotyping by Regeneron. Incident invasive and DCIS BC was identified through the Mayo tumor registry and follow-up questionnaires, and person years were calculated from date of mammogram through date of BC, last mammogram at Mayo or last questionnaire. We estimated Transpara AI malignancy score (1-10), 5-year Mirai risk and Volpara volumetric density measures (volumetric percent density, dense volume) on screening mammograms at enrollment and obtained clinical BI-RADS density. We calculated the BC-PRS using 268 SNPs (of the 313-SNP score) and the weighted sum of the SNPs using odds ratios from the largest BC GWAS of European ancestry to date. We performed cox proportional hazards regression adjusting for age and BMI to estimate hazard ratios (HRs), 95% confidence intervals (CI), and C-statistics (AUC) to describe the contribution of BC-PRS (per standard deviation (SD)) to the association of AI scores and breast density with BC risk. Likelihood ratio tests (LRT) and bootstrapping were used to compare model performance with vs. without inclusion of BC-PRS, at 10-years follow-up. Comparisons to the Tyrer-Cuzick model are ongoing. Over a median of 9.1 years (Interquartile range, 6.8 to 10.6), 446 incident BC were identified of which 285 invasive and 103 DCIS were confirmed by pathology report (60 were self-reported); 399 (256 invasive) occurred within 10 years and were used in primary analyses. Transpara score [HR per 1 unit=1.18 (1.14, 1.23), AUC=0.655 (0.628, 0.682)] and Mirai risk [HR per SD log risk=1.54 (1.43, 1.65), AUC=0.681 (0.655, 0.706)] were both associated with BC. All three breast density measures were also significantly associated with BC, including in models with AI scores (Table). Addition of the BC-PRS to models with AI scores and breast density improved both model fit (All PLRT &amp;lt; 0.001; Table) and discrimination, with increases in AUC ranging from 0.033 to 0.034 for models with Transpara and density and 0.025 to 0.026 for models with Mirai and density (all P-values &amp;lt; 0.001; Table). Analyses restricted to invasive BC showed identical results. But, the BC-PRS contribution at 5-year follow-up was attenuated. In this cohort study, we found BC-PRS contributed to long-term risk prediction of BC above imaging AI models and breast density. Imaging and genetic risk factors are complementary and may outperform existing risk models and provide more accurate risk assessment to aid in precision prevention strategies. Citation Format: Celine Vachon, Christopher Scott, Imon Banerjee, Ramon Correa Moderno, Dan Hursh, Matthew Jensen, Yvonne Wang, Kathleen Brandt, Karla Kerlikowske, Sandhya Pruthi, Fergus Couch, Stacey Winham. Contribution of a breast cancer polygenic risk score to mammography artificial intelligence models and breast density for long term breast cancer risk prediction [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS10-06.

Abstract 4431: Steroid hormone metabolites and mammographic breast density in premenopausal women

Abstract Background: Steroid hormones influence breast tissue development and play a role in breast carcinogenesis. Their associations with mammographic breast density (MBD), an established risk factor for breast cancer, are less clear. We, therefore, investigated the associations of steroid hormone metabolites with MBD in premenopausal women. Methods: Our study population consists of 705 premenopausal women recruited during their annual screening mammogram at the Washington University School of Medicine, St. Louis, MO. We assessed volumetric percent density (VPD), dense volume (DV), and non-dense volume (NDV) using Volpara. We assayed 54 steroid hormone metabolites from fasting blood samples at Metabolon. Linear regression models were used, after adjusting for covariates, to estimate the least square means of VPD, DV, and NDV across tertiles (T) of each metabolite. Sensitivity analysis was performed among the subset of participants with a history of oral contraceptive use (OCP). We used the Benjamini-Hochberg procedure to correct for multiple tests to control the false discovery rate (FDR) at a 5% level. Results: Five androgen metabolites (androstenediol (3beta,17beta) monosulfate 2, androstenediol (3beta,17beta) disulfate 1, 5alpha-androstan-3alpha,17beta-diol monosulfate 2, 5alpha-androstan-3alpha,17beta-diol disulfate, and 5alpha-androstan-3beta,17beta-diol disulfate) and two corticosteroid metabolites (tetrahydrocortisone glucuronide 5, and cortolone glucuronide 1) were inversely associated with VPD. Androstenediol (3beta,17beta) disulfate 1, and 5alpha-androstan-3alpha,17beta-diol disulfate displayed the strongest associations with VPD. The mean VPD decreased across tertiles of androstenediol (3beta,17beta) disulfate 1 from 9.0% in T1 to 8.5% in T2, and 7.5% in T3 (FDR p-value=0.02). Similarly, the mean VPD decreased from 8.8% in T1 to 8.4% in T2, and 7.6% in T3 of 5alpha-androstan-3alpha,17beta-diol disulfate (FDR p-value=0.03). Progestin steroid metabolites appeared to be positively associated with VPD but only 5alpha-pregnan-3beta,20alpha-diol monosulfate 2 was marginally significant after FDR correction (7.5% in T1, 8.3% in T2, and 8.8% in T3; FDR p-value=0.06). Four metabolites (three corticosteroids and one androgenic steroid) were positively associated with NDV. No metabolite was associated with DV. In sensitivity analysis limited to OCP users, mean VPDs were lower but the directions of associations were similar to those observed in the overall analysis. Conclusion: We report novel associations of corticosteroids and androgen metabolites with breast density in premenopausal women. Our findings shed important new insights into hormonal biomarkers and MBD. Citation Format: Kayode A. Matthew, Girish K. Vanapali, Kayla R. Getz, Myung S. Jeon, Chongliang Luo, Xingyi Guo, Jingqin Luo, Adetunji T. Toriola. Steroid hormone metabolites and mammographic breast density in premenopausal women [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2024; Part 1 (Regular Abstracts); 2024 Apr 5-10; San Diego, CA. Philadelphia (PA): AACR; Cancer Res 2024;84(6_Suppl):Abstract nr 4431.

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

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. Breast density measures were estimated for 1,961 Australian women aged 18-97years 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. The mean age was 38years (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. 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.

En Face and Volumetric Comparison of Hypertransmission Defects Evaluated by Cirrus and Spectralis Optical Coherence Tomography

PurposeTo evaluate and compare en face and 3-dimensional (D) properties of hypertransmission defects (HTDs) between different optical coherence tomography (OCT) devices using OCT volumes and reconstructed en face images. SettingsComparative diagnostic evaluation study. MethodsThirty eyes with dry age-related macular degeneration (AMD) that underwent dense OCT macular volume scans with both the Spectralis (97 B-scans/volume; 2,910 B-scans in total) and Cirrus OCT (128 B-scans/volume; 3,840 B-scans in total) from AMISH EYE STUDY cohort were included in this analysis. HTD regions were labeled on each B-scan and reconstructed into en face and 3-D volume images. Properties of HTD volume were compared between the two devices. ResultsQualitative score of en face images for HTD was higher for the Cirrus compared to the Spectralis (P < 0.01). The quality of Spectralis en face images improved after preprocessing and reconstruction. The 2-D HTD area on en face obtained from 2-D projections of 3-D volume did not differ between devices (P = 0.478; ICC 0.998; Jaccard index 0.721 ± 0.086). There was no difference in the number, volume, PALs, and surface areas of HTDs between devices in the volumetric analysis (all P ≥ 0.090). The signal intensity of HTD normalized by the mean choroidal signal intensity did not differ between devices (P = 0.861). ConclusionsThe visualization of HTD on en face images from Spectralis OCT could be enhanced through image processing. The equivalence in 3-D HTD parameters between the two devices suggests interchangeability for assessing these lesions in AMD.

Cigarette smoking and mammographic breast density in post-menopausal women from the EPIC Florence cohort.

Cigarette smoking has been recognized as a risk factor for breast cancer (BC) also if the biological mechanism remains poorly understood. High mammographic breast density (MBD) is associated with BC risk and many BC risk factors, such as genetic, anthropometric, reproductive and lifestyle factors and age, are also able to modulate MBD. The aim of the present study was to prospectively explore, in post-menopausal women, the association between smoking habits and MBD, assessed using an automated software, considering duration and intensity of smoking. The analysis was carried out in 3,774 women enrolled in the European Prospective Investigation into Cancer and Nutrition (EPIC) Florence cohort in 1993-98, participating in the 2004-06 follow up (FU) and with at least one full-field digital mammography (FFDM) performed after FU. For each woman, detailed information on smoking habits, anthropometry, lifestyle and reproductive history was collected at enrollment and at FU. Smoking information at baseline and at FU was integrated. The fully automated Volpara™ software was used to obtain total breast volume (cm3), absolute breast dense volume (DV, cm3) and volumetric percent density (VPD, %) from the first available FFDM (average 5.3 years from FU). Multivariable linear regression models were applied to evaluate the associations between smoking habits and VPD or DV. An inverse association between smoking exposure and VPD emerged (Diff% -7.96%, p <0.0001 for current smokers and -3.92%, p 0.01 for former smokers, compared with non-smokers). An inverse dose-response relationship with number of cigarettes/day, years of smoking duration and lifetime smoking exposure (pack-years) and a direct association with time since smoking cessation among former smokers emerged. Similar associations, with an attenuated effect, emerged when DV was considered as the outcome variable. This longitudinal study confirms the inverse association between active smoking, a known risk factor for BC, and MBD among post-menopausal women. The inclusion of smoking habits in the existing BC risk prediction models could be evaluated in future studies.

Providence and Science in a World of Contingency: Thomas Aquinas’ Metaphysics of Divine Action

Providence and Science in a World of Contingency: Thomas Aquinas’ Metaphysics of Divine Action

Providence and Science in a World of Contingency: Thomas Aquinas’ Metaphysics of Divine Action

Providence and Science in a World of Contingency: Thomas Aquinas’ Metaphysics of Divine Action

The importance of nonobstructive plaque characteristics in symptomatic and asymptomatic coronary artery disease

BackgroundWe examined obstructive and nonobstructive plaque volumes in populations with subclinical and clinically manifested coronary artery disease (CAD) using quantitative computed tomography (QCT). Methods855 participants with CAD (274 asymptomatic individuals, 254 acute chest pain patients without acute coronary syndrome (ACS), and 327 patients with ACS) underwent QCT of proximal coronary segments to assess participant-level plaque volumes of dense calcium, fibrous, fibrofatty, and necrotic core tissue. ResultsNonobstructive (<50% stenosis) plaque volumes were greater than obstructive plaque volumes, irrespective of population (all p<0.0001): Asymptomatic individuals (mean (95% CI)): 218 [190-250] vs. 16 [12-22] mm3; acute chest pain patients without ACS: 300 [263-341] vs. 51 [41-62] mm3; patients with ACS: 370 [332-412] vs. 159 [139-182] mm3. After multivariable adjustment, nonobstructive fibrous and fibrofatty tissue volumes were greater in acute chest pain patients without ACS compared to asymptomatic individuals (fibrous tissue: 122 [107-139] vs. 175 [155-197] mm3, p<0.01; fibrofatty tissue: 44 [38-50] vs. 71 [63-80] mm3, p<0.01. Necrotic core tissue was greater in ACS patients (29 [26-33] mm3) compared to both asymptomatic individuals (15 [13-18] mm3, p<0.0001) and acute chest pain patients without ACS (21 [18-24] mm3, p<0.05). Nonobstructive dense calcium volumes did not differ between the three populations: 29 [24-36], 29 [23-35], and 41 [34-48] mm3, p>0.3 respectively. ConclusionNonobstructive CAD was the predominant contributor to total atherosclerotic plaque volume in both subclinical and clinically manifested CAD. Nonobstructive fibrous, fibrofatty and necrotic core tissue volumes increased with worsening clinical presentation, while nonobstructive dense calcium tissue volumes did not.