Using Digital Pathology to Understand Epithelial Characteristics of Benign Breast Disease among Women Undergoing Diagnostic Image-Guided Breast Biopsy.
Maeve MulloolySamantha PuvanesarajahShaoqi FanRuth M PfeifferLinnea T OlssonManila HadaErin L KirkPamela M VacekDonald L WeaverJohn ShepherdAmir MahmoudzadehJeff WangSerghei MalkovJason M JohnsonStephen M HewittSally D HerschornMark E ShermanMelissa A TroesterGretchen L GierachPublished in: Cancer prevention research (Philadelphia, Pa.) (2019)
Delayed terminal duct lobular unit (TDLU) involution is associated with elevated mammographic breast density (MD). Both are independent breast cancer risk factors among women with benign breast disease (BBD). Prior digital analyses of normal breast tissues revealed that epithelial nuclear density (END) and TDLU involution are inversely correlated. Accordingly, we examined associations of END, TDLU involution, and MD in BBD clinical biopsies. This study included digitized images of 262 representative image-guided hematoxylin and eosin-stained biopsies from 224 women diagnosed with BBD, enrolled within the cross-sectional BREAST-Stamp project that were visually assessed for TDLU involution (TDLU count/100 mm2, median TDLU span and median acini count per TDLU). A digital algorithm estimated nuclei count per unit epithelial area, or END. Single X-ray absorptiometry of prebiopsy ipsilateral craniocaudal digital mammograms measured global and localized MD surrounding the biopsy region. Adjusted ordinal logistic regression models assessed relationships between tertiles of TDLU and END measures. Analysis of covariance examined mean differences in MD across END tertiles. TDLU measures were positively associated with increasing END tertiles [TDLU count/100 mm2, ORT3vsT1: 3.42, 95% confidence interval (CI), 1.87-6.28; acini count/TDLUT3vsT1, OR: 2.40, 95% CI, 1.39-4.15]. END was significantly associated with localized, but not, global MD. Relationships were most apparent among patients with nonproliferative BBD. These findings suggest that quantitative END reflects different but complementary information to the histologic information captured by visual TDLU and radiologic MD measures and merits continued evaluation in assessing cellularity of breast parenchyma to understand the etiology of BBD.
Keyphrases
- molecular dynamics
- cross sectional
- risk factors
- peripheral blood
- ultrasound guided
- high resolution
- deep learning
- polycystic ovary syndrome
- gene expression
- body composition
- machine learning
- healthcare
- bone mineral density
- metabolic syndrome
- young adults
- pregnant women
- skeletal muscle
- postmenopausal women
- fine needle aspiration
- contrast enhanced