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dc.contributor.authorSchaadt, Nadine S
dc.contributor.authorSchönmeyer, Ralf
dc.contributor.authorForestier, Germain
dc.contributor.authorBrieu, Nicolas
dc.contributor.authorBraubach, Peter
dc.contributor.authorNekolla, Katharina
dc.contributor.authorMeyer-Hermann, Michael
dc.contributor.authorFeuerhake, Friedrich
dc.date.accessioned2020-03-06T10:51:43Z
dc.date.available2020-03-06T10:51:43Z
dc.date.issued2020-02-01
dc.identifier.citationPLoS Comput Biol. 2020 Feb 21;16(2):e1007385. doi: 10.1371/journal.pcbi.1007385. eCollection 2020 Feb.en_US
dc.identifier.issn1553-7358
dc.identifier.pmid32084130
dc.identifier.doi10.1371/journal.pcbi.1007385
dc.identifier.urihttp://hdl.handle.net/10033/622191
dc.description.abstractOur 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.en_US
dc.language.isoenen_US
dc.publisherPLOSen_US
dc.rightsAttribution-NonCommercial-ShareAlike 4.0 International*
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/4.0/*
dc.subjectB cellsen_US
dc.subjectGraphsen_US
dc.subjectT cellsen_US
dc.subjectimmune cellsen_US
dc.subjectdentritic structureen_US
dc.subjectpathologistsen_US
dc.subjectlymphocytesen_US
dc.subjectsupport vector machinesen_US
dc.titleGraph-based description of tertiary lymphoid organs at single-cell level.en_US
dc.typeArticleen_US
dc.contributor.departmentBRICS, Braunschweiger Zentrum für Systembiologie, Rebenring 56,38106 Braunschweig, Germany.en_US
dc.identifier.journalPLOS computational biologyen_US
refterms.dateFOA2020-03-06T10:51:44Z
dc.source.journaltitlePLoS computational biology


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