Graph-based description of tertiary lymphoid organs at single-cell level

Abstract: Our aim is to complement observer-dependent approaches of immune cell evaluation in microscopy images with reproducible measures for spatial composition of lymphocytic infiltrates. Analyzing such patterns of inflammation is becoming increasingly important for therapeutic decisions, for example in transplantation medicine or cancer immunology. We developed a graph-based assessment of lymphocyte clustering in full whole slide images. Based on cell coordinates detected in the full image, a Delaunay triangulation and distance criteria are used to build neighborhood graphs. The composition of nodes and edges are used for classification, e.g. using a support vector machine. We describe the variability of these infiltrates on CD3/CD20 duplex staining in renal biopsies of long-term functioning allografts, in breast cancer cases, and in lung tissue of cystic fibrosis patients. The assessment includes automated cell detection, identification of regions of interest, and classification of lymphocytic clusters according to their degree of organization. We propose a neighborhood feature which considers the occurrence of edges with a certain type in the graph to distinguish between phenotypically different immune infiltrates. Our work addresses a medical need and provides a scalable framework that can be easily adjusted to the requirements of different research questions

Standort
Deutsche Nationalbibliothek Frankfurt am Main
Umfang
Online-Ressource
Sprache
Englisch
Anmerkungen
PLOS computational biology. - 16, 2 (2020) , e1007385, ISSN: 1553-7358

Ereignis
Veröffentlichung
(wo)
Freiburg
(wer)
Universität
(wann)
2020
Urheber
Schaadt, Nadine S.
Schönmeyer, Ralf
Forestier, Germain
Brieu, Nicolas
Braubach, Peter Paul Johann
Nekolla, Katharina
Meyer-Hermann, Michael
Feuerhake, Friedrich

DOI
10.1371/journal.pcbi.1007385
URN
urn:nbn:de:bsz:25-freidok-1670606
Rechteinformation
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Letzte Aktualisierung
25.03.2025, 13:51 MEZ

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Beteiligte

Entstanden

  • 2020

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