Image analysis of immune cell patterns in the human mammary gland during the menstrual cycle refines lymphocytic lobulitis
Résumé
Purpose: To improve microscopic evaluation of immune cells relevant in breast cancer oncoimmunology, we aim at distinguishing normal infiltration patterns from lymphocytic lobulitis by advanced image analysis. We consider potential immune cell variations due to the menstrual cycle and oral contraceptives in non-neoplastic mammary gland tissue. Methods: Lymphocyte and macrophage distributions were analyzed in the anatomical context of the resting mammary gland in immunohistochemically stained digital whole slide images obtained from 53 reduction mammoplasty specimens. Our image analysis workflow NS Schaadt · A Grote · N Krönke · HH Kreipe · included automated regions of interest detection, immune cell recognition, and co-registration of regions of interest. Results: In normal lobular epithelium, seven CD8 + lymphocytes per 100 epithelial cells were present on average and about 70% of this T-lymphocyte population was lined up along the basal cell layer in close proximity to the epithelium. The density of CD8 + T-cell was 1.6 fold higher in the luteal than in the follicular phase in spontaneous menstrual cycles and 1.4 fold increased under influence of oral contraceptives, and not co-localized with epithelial proliferation. CD4 + T-cells were infrequent. Abundant CD163 + macrophages were widely spread, including the interstitial compartment, with minor variation during the menstrual cycle. Conclusions: Spatial patterns of different immune cell subtypes determine the range of normal, as opposed to inflammatory conditions of the breast tissue microen-vironment. Advanced image analysis enables quantifi-cation of hormonal effects, refines lymphocytic lobulitis, and shows potential for comprehensive biopsy evaluation in oncoimmunology. Keywords lymphocytic lobulitis · digital pathology · oncoimmunology · object-based image analysis · menstrual cycle · hormonal fluctuations This is the author's version of an article published in Breast Cancer Research and Treatment. The final authenticated version is available online at: https://doi.
Domaines
Intelligence artificielle [cs.AI]Origine | Fichiers produits par l'(les) auteur(s) |
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