Dataset Information

Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities.

ABSTRACT: Elevated mammographic density (MD) is an established breast cancer risk factor. Reduced involution of terminal duct lobular units (TDLU), the histologic source of most breast cancers, has been associated with higher MD and breast cancer risk. We investigated relationships of TDLU involution with area and volumetric MD, measured throughout the breast and surrounding biopsy targets (perilesional). Three measures inversely related to TDLU involution (TDLU count/mm(2), median TDLU span, median acini count/TDLU) assessed in benign diagnostic biopsies from 348 women, ages 40-65, were related to MD area (quantified with thresholding software) and volume (assessed with a density phantom) by analysis of covariance, stratified by menopausal status and adjusted for confounders. Among premenopausal women, TDLU count was directly associated with percent perilesional MD (P trend = 0.03), but not with absolute dense area/volume. Greater TDLU span was associated with elevated percent dense area/volume (P trend<0.05) and absolute perilesional MD (P = 0.003). Acini count was directly associated with absolute perilesional MD (P = 0.02). Greater TDLU involution (all metrics) was associated with increased nondense area/volume (P trend ? 0.04). Among postmenopausal women, TDLU measures were not significantly associated with MD. Among premenopausal women, reduced TDLU involution was associated with higher area and volumetric MD, particularly in perilesional parenchyma. Data indicating that TDLU involution and MD are correlated markers of breast cancer risk suggest that associations of MD with breast cancer may partly reflect amounts of at-risk epithelium. If confirmed, these results could suggest a prevention paradigm based on enhancing TDLU involution and monitoring efficacy by assessing MD reduction.

SUBMITTER: Gierach GL

PROVIDER: S-EPMC4784982 | biostudies-literature | 2016 Feb

REPOSITORIES: biostudies-literature

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Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities.

Gierach Gretchen L GL Patel Deesha A DA Pfeiffer Ruth M RM Figueroa Jonine D JD Linville Laura L Papathomas Daphne D Johnson Jason M JM Chicoine Rachael E RE Herschorn Sally D SD Shepherd John A JA Wang Jeff J Malkov Serghei S Vacek Pamela M PM Weaver Donald L DL Fan Bo B Mahmoudzadeh Amir Pasha AP Palakal Maya M Xiang Jackie J Oh Hannah H Horne Hisani N HN Sprague Brian L BL Hewitt Stephen M SM Brinton Louise A LA Sherman Mark E ME

Cancer prevention research (Philadelphia, Pa.) 20151208 2

Elevated mammographic density (MD) is an established breast cancer risk factor. Reduced involution of terminal duct lobular units (TDLU), the histologic source of most breast cancers, has been associated with higher MD and breast cancer risk. We investigated relationships of TDLU involution with area and volumetric MD, measured throughout the breast and surrounding biopsy targets (perilesional). Three measures inversely related to TDLU involution (TDLU count/mm(2), median TDLU span, median acini ...[more]

PMID: 26645278

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Project description:Terminal duct lobular unit (TDLU) involution is the regression of milk-producing structures in the breast. Women with less TDLU involution are more likely to develop breast cancer. A major bottleneck in studying TDLU involution in large cohort studies is the need for labor-intensive manual assessment of TDLUs. We developed a computational pathology solution to automatically capture TDLU involution measures. Whole slide images (WSIs) of benign breast biopsies were obtained from the Nurses' Health Study. A set of 92 WSIs was annotated for acini, TDLUs and adipose tissue to train deep convolutional neural network (CNN) models for detection of acini, and segmentation of TDLUs and adipose tissue. These networks were integrated into a single computational method to capture TDLU involution measures including number of TDLUs per tissue area, median TDLU span and median number of acini per TDLU. We validated our method on 40 additional WSIs by comparing with manually acquired measures. Our CNN models detected acini with an F1 score of 0.73±0.07, and segmented TDLUs and adipose tissue with Dice scores of 0.84±0.13 and 0.87±0.04, respectively. The inter-observer ICC scores for manual assessments on 40 WSIs of number of TDLUs per tissue area, median TDLU span, and median acini count per TDLU were 0.71, 0.81 and 0.73, respectively. Intra-observer reliability was evaluated on 10/40 WSIs with ICC scores of >0.8. Inter-observer ICC scores between automated results and the mean of the two observers were: 0.80 for number of TDLUs per tissue area, 0.57 for median TDLU span, and 0.80 for median acini count per TDLU. TDLU involution measures evaluated by manual and automated assessment were inversely associated with age and menopausal status. We developed a computational pathology method to measure TDLU involution. This technology eliminates the labor-intensiveness and subjectivity of manual TDLU assessment, and can be applied to future breast cancer risk studies.

Project description:BackgroundExposure to certain outdoor air pollutants may be associated with a higher risk of breast cancer, though potential underlying mechanisms are poorly understood. We examined whether outdoor air pollution was associated with involution of terminal duct lobular units (TDLUs), the histologic site where most cancers arise and an intermediate marker of breast cancer risk.MethodsPathologist-enumerated TDLUs were assessed in H&E (hematoxylin and eosin)-stained breast tissue sections from 1904 US women ages 18-75 who donated to the Susan G. Komen Tissue Bank (2009-2012). The 2009 annual fine particulate matter < 2.5 μm in diameter (PM2.5) total mass (μg/m3) at each woman's residential address was estimated from the Environmental Protection Agency's Downscaler Model combining Community Multiscale Air Quality (CMAQ) System modeling with air quality monitoring data. We secondarily considered CMAQ-modeled components of PM2.5 and gaseous pollutants. We used K-means clustering to identify groups of individuals with similar levels of PM2.5 components, selecting groups via cluster stability analysis. Relative rates (RRs) and 95% confidence intervals (95% CIs) for the association between air pollutants and TDLU counts were estimated from a zero-inflated negative binomial regression model adjusted for potential confounders.ResultsPM2.5 total mass was associated with higher TDLU counts among all women (interquartile range (IQR) increase, RR = 1.06; 95% CI: 1.01-1.11). This association was evident among both premenopausal and postmenopausal women (premenopausal RR = 1.05, 95% CI: 1.00-1.11; postmenopausal RR = 1.11, 95% CI: 1.00-1.23). We identified 3 groups corresponding to clusters that varied geographically and roughly represented high, medium, and low levels of PM2.5 components relative to population mean levels. Compared to the cluster with low levels, the clusters with both high (RR = 1.74; 95% CI: 1.08-2.80) and medium (RR = 1.82; 95% CI: 1.13-2.93) levels were associated with higher TDLU counts; although not significantly different, the magnitude of the associations was stronger among postmenopausal women.ConclusionsHigher PM2.5 levels were associated with reduced TDLU involution as measured by TDLU counts. Air pollution exposure may influence the histologic characteristics of normal tissue which could in turn affect breast cancer risk.

Dataset Information

Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities.

Publications

Relationship of Terminal Duct Lobular Unit Involution of the Breast with Area and Volume Mammographic Densities.

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