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The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

ABSTRACT: Extensive mammographic density (MD), a well-established breast cancer risk factor, is a radiological representation of stromal and epithelial breast tissue content. In studies conducted predominantly among Caucasian women, histologic measures of reduced terminal duct lobular unit (TDLU) involution have been correlated with extensive MD, but independently associated with breast cancer risk. We therefore examined associations between TDLU measures and MD among Chinese women, a low-risk population but with high prevalence of dense breasts. Diagnostic pre-treatment digital mammograms were obtained from 144 breast cancer cases at a tertiary hospital in Beijing and scored using the Breast Imaging Reporting and Data System (BI-RADS) density classification. TDLU features were assessed using three standardized measures (count/100 mm2 , span [?m], and acini count/TDLU) in benign tissues. Associations between each of TDLU measures and MD were examined using generalized linear models for TDLU count and span and polytomous logistic regression for acini count with adjustment for potential confounders stratified by age. Among women ?50 years, 63% had dense breasts; cases with dense breasts (BI-RADS, c-d) had greater TDLU count (21.1 [SE = 2.70] vs. 9.0 [SE = 1.83]; p = 0.0004), longer span (480.6 ?m [SE = 24.6] vs. 393.8 ?m [SE = 31.8]; p = 0.03), and greater acini count (ORtrend = 16.1; 95%CI = 4.08-63.1; ptrend < 0.0001) compared to those with non-dense breasts (BI-RADS, a-b). Among women <50 years, 91% had dense breasts, precluding our ability to detect associations. Our findings are consistent with previously reported associations between extensive MD and reduced TDLU involution, supporting the hypothesis that breast cancer risk associated with extensive MD may be related to the amount of "at-risk" epithelium.

SUBMITTER: Sung H

PROVIDER: S-EPMC6488407 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

Sung Hyuna H Guo Changyuan C Li Erni E Li Jing J Pfeiffer Ruth M RM Guida Jennifer L JL Cora Renata R Hu Nan N Deng Joseph J Figueroa Jonine D JD Sherman Mark E ME Gierach Gretchen L GL Lu Ning N Yang Xiaohong R XR

International journal of cancer 20190107 1

Extensive mammographic density (MD), a well-established breast cancer risk factor, is a radiological representation of stromal and epithelial breast tissue content. In studies conducted predominantly among Caucasian women, histologic measures of reduced terminal duct lobular unit (TDLU) involution have been correlated with extensive MD, but independently associated with breast cancer risk. We therefore examined associations between TDLU measures and MD among Chinese women, a low-risk population ...[more]

PMID: 30561789

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Project description: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.

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.

Dataset Information

The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

Publications

The relationship between terminal duct lobular unit features and mammographic density among Chinese breast cancer patients.

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