| 1. |
- de Bel, Thomas, et al.
(författare)
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Automated quantification of levels of breast terminal duct lobular (TDLU) involution using deep learning
- 2022
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Ingår i: npj Breast Cancer. - : Nature Portfolio. - 2374-4677. ; 8:1
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Tidskriftsartikel (refereegranskat)abstract
- Convolutional neural networks (CNNs) offer the potential to generate comprehensive quantitative analysis of histologic features. Diagnostic reporting of benign breast disease (BBD) biopsies is usually limited to subjective assessment of the most severe lesion in a sample, while ignoring the vast majority of tissue features, including involution of background terminal duct lobular units (TDLUs), the structures from which breast cancers arise. Studies indicate that increased levels of age-related TDLU involution in BBD biopsies predict lower breast cancer risk, and therefore its assessment may have potential value in risk assessment and management. However, assessment of TDLU involution is time-consuming and difficult to standardize and quantitate. Accordingly, we developed a CNN to enable automated quantitative measurement of TDLU involution and tested its performance in 174 specimens selected from the pathology archives at Mayo Clinic, Rochester, MN. The CNN was trained and tested on a subset of 33 biopsies, delineating important tissue types. Nine quantitative features were extracted from delineated TDLU regions. Our CNN reached an overall dice-score of 0.871 (+/- 0.049) for tissue classes versus reference standard annotation. Consensus of four reviewers scoring 705 images for TDLU involution demonstrated substantial agreement with the CNN method (unweighted kappa = 0.747 +/- 0.01). Quantitative involution measures showed anticipated associations with BBD histology, breast cancer risk, breast density, menopausal status, and breast cancer risk prediction scores (p < 0.05). Our work demonstrates the potential to improve risk prediction for women with BBD biopsies by applying CNN approaches to generate automated quantitative evaluation of TDLU involution.
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| 2. |
- Ogony, Joshua, et al.
(författare)
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Towards defining morphologic parameters of normal parous and nulliparous breast tissues by artificial intelligence
- 2022
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Ingår i: Breast Cancer Research. - : BMC. - 1465-5411 .- 1465-542X. ; 24:1
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Tidskriftsartikel (refereegranskat)abstract
- Background Breast terminal duct lobular units (TDLUs), the source of most breast cancer (BC) precursors, are shaped by age-related involution, a gradual process, and postpartum involution (PPI), a dramatic inflammatory process that restores baseline microanatomy after weaning. Dysregulated PPI is implicated in the pathogenesis of postpartum BCs. We propose that assessment of TDLUs in the postpartum period may have value in risk estimation, but characteristics of these tissues in relation to epidemiological factors are incompletely described. Methods Using validated Artificial Intelligence and morphometric methods, we analyzed digitized images of tissue sections of normal breast tissues stained with hematoxylin and eosin from donors <= 45 years from the Komen Tissue Bank (180 parous and 545 nulliparous). Metrics assessed by AI, included: TDLU count; adipose tissue fraction; mean acini count/TDLU; mean dilated acini; mean average acini area; mean "capillary" area; mean epithelial area; mean ratio of epithelial area versus intralobular stroma; mean mononuclear cell count (surrogate of immune cells); mean fat area proximate to TDLUs and TDLU area. We compared epidemiologic characteristics collected via questionnaire by parity status and race, using a Wilcoxon rank sum test or Fishers exact test. Histologic features were compared between nulliparous and parous women (overall and by time between last birth and donation [recent birth: <= 5 years versus remote birth: > 5 years]) using multivariable regression models. Results Normal breast tissues of parous women contained significantly higher TDLU counts and acini counts, more frequent dilated acini, higher mononuclear cell counts in TDLUs and smaller acini area per TDLU than nulliparas (all multivariable analyses p < 0.001). Differences in TDLU counts and average acini size persisted for > 5 years postpartum, whereas increases in immune cells were most marked <= 5 years of a birth. Relationships were suggestively modified by several other factors, including demographic and reproductive characteristics, ethanol consumption and breastfeeding duration. Conclusions Our study identified sustained expansion of TDLU numbers and reduced average acini area among parous versus nulliparous women and notable increases in immune responses within five years following childbirth. Further, we show that quantitative characteristics of normal breast samples vary with demographic features and BC risk factors.
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| 3. |
- Sherman, Mark E., et al.
(författare)
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Serum hormone levels and normal breast histology among premenopausal women
- 2022
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Ingår i: Breast Cancer Research and Treatment. - New York, NY, United States : Springer. - 0167-6806 .- 1573-7217. ; 194, s. 149-158
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Tidskriftsartikel (refereegranskat)abstract
- Purpose Breast terminal duct lobular units (TDLUs) are the main source of breast cancer (BC) precursors. Higher serum concentrations of hormones and growth factors have been linked to increased TDLU numbers and to elevated BC risk, with variable effects by menopausal status. We assessed associations of circulating factors with breast histology among premenopausal women using artificial intelligence (AI) and preliminarily tested whether parity modifies associations.Methods Pathology AI analysis was performed on 316 digital images of H&E-stained sections of normal breast tissues from Komen Tissue Bank donors ages ≤ 45 years to assess 11 quantitative metrics. Associations of circulating factors with AI metrics were assessed using regression analyses, with inclusion of interaction terms to assess effect modification.Results Higher prolactin levels were related to larger TDLU area (p<0.001) and increased presence of adipose tissue proximate to TDLUs (p<0.001), with less significant positive associations for acini counts (p = 0.012), dilated acini (p = 0.043), capillary area (p = 0.014), epithelial area (p = 0.007), and mononuclear cell counts (p = 0.017). Testosterone levels were associated with increased TDLU counts (p<0.001), irrespective of parity, but associations differed by adipose tissue content. AI data for TDLU counts generally agreed with prior visual assessments.Conclusion Among premenopausal women, serum hormone levels linked to BC risk were also associated with quantitative features of normal breast tissue. These relationships were suggestively modified by parity status and tissue composition. We conclude that the microanatomic features of normal breast tissue may represent a marker of BC risk.
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| 4. |
- Strell, Carina, et al.
(författare)
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Impact of Epithelial-Stromal Interactions on Peritumoral Fibroblasts in Ductal Carcinoma in Situ
- 2019
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Ingår i: Journal of the National Cancer Institute. - : Oxford University Press (OUP). - 0027-8874 .- 1460-2105. ; 111:9, s. 983-995
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Tidskriftsartikel (refereegranskat)abstract
- Background: A better definition of biomarkers and biological processes related to local recurrence and disease progression is highly warranted for ductal breast carcinoma in situ (DCIS). Stromal-epithelial interactions are likely of major importance for the biological, clinical, and pathological distinctions between high- and low-risk DCIS cases. Methods: Stromal platelet derived growth factor receptor (PDGFR) was immunohistochemically assessed in two DCIS patient cohorts (n = 458 and n = 80). Cox proportional hazards models were used to calculate the hazard ratios of recurrence. The molecular mechanisms regulating stromal PDGFR expression were investigated in experimental in vitro co-culture systems of DCIS cells and fibroblasts and analyzed using immunoblot and quantitative real-time PCR. Knock-out of JAG1 in DCIS cells and NOTCH2 in fibroblasts was obtained through CRISPR/Cas9. Experimental data were validated by mammary fat pad injection of DCIS and DCIS-JAG1 knock-out cells (10 mice per group). All statistical tests were two-sided. Results: PDGFR alpha((low))/PDGFR beta((high)) fibroblasts were associated with increased risk for recurrence in DCIS (univariate hazard ratio = 1.59, 95% confidence interval [CI] = 1.02 to 2.46; P = .04 Wald test; multivariable hazard ratio = 1.78, 95% CI = 1.07 to 2.97; P = .03). Tissue culture and mouse model studies indicated that this fibroblast phenotype is induced by DCIS cells in a cell contact-dependent manner. Epithelial Jagged1 and fibroblast Notch2 were identified through loss-of-function studies as key juxtacrine signaling components driving the formation of the poor prognosis-associated fibroblast phenotype. Conclusions: A PDGFR alpha((low))/PDGFR beta((high)) fibroblast subset was identified as a marker for high-risk DCIS. The Jagged-1/Notch2/PDGFR stroma-epithelial pathway was described as a novel signaling mechanism regulating this poor prognosis-associated fibroblast subset. In general terms, the study highlights epithelial-stromal crosstalk in DCIS and contributes to ongoing efforts to define clinically relevant fibroblast subsets and their etiology.
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