Bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumor cells in Hodgkin lymphoma
- In pathology, tissue images are evaluated using a light microscope, relying on the expertise and experience of pathologists. There is a great need for computational methods to quantify and standardize histological observations. Computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of tumor cells and their microenvironment are of special interest. Here, we systematically investigated tumor cell properties and their spatial neighborhood relations by a new application of statistical analysis to whole slide images of Hodgkin lymphoma, a tumor arising in lymph nodes, and inflammation of lymph nodes called lymphadenitis. We considered properties of more than 400, 000 immunohistochemically stained, CD30-positive cells in 35 whole slide images of tissue sections from subtypes of the classical Hodgkin lymphoma, nodular sclerosis and mixed cellularity, as well as from lymphadenitis. We found that cells of specific morphology exhibited significant favored and unfavored spatial neighborhood relations of cells in dependence of their morphology. This information is important to evaluate differences between Hodgkin lymph nodes infiltrated by tumor cells (Hodgkin lymphoma) and inflamed lymph nodes, concerning the neighborhood relations of cells and the sizes of cells. The quantification of neighborhood relations revealed new insights of relations of CD30-positive cells in different diagnosis cases. The approach is general and can easily be applied to whole slide image analysis of other tumor types.
Author: | Jennifer HannigORCiD, Hendrik Schäfer, Jörg AckermannORCiDGND, Marie Hebel, Tim SchäferORCiDGND, Claudia DöringORCiDGND, Sylvia HartmannORCiDGND, Martin-Leo HansmannGND, Ina KochORCiD |
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URN: | urn:nbn:de:hebis:30:3-525571 |
DOI: | https://doi.org/10.1371/journal.pcbi.1007516 |
ISSN: | 1553-7358 |
ISSN: | 1553-734X |
Pubmed Id: | https://pubmed.ncbi.nlm.nih.gov/31961873 |
Parent Title (English): | PLoS Computational Biology |
Publisher: | Public Library of Science |
Place of publication: | San Francisco, Calif. |
Contributor(s): | Jason A. Papin |
Document Type: | Article |
Language: | English |
Year of Completion: | 2020 |
Date of first Publication: | 2020/01/21 |
Publishing Institution: | Universitätsbibliothek Johann Christian Senckenberg |
Release Date: | 2020/02/05 |
Tag: | Cell staining; Hematoxylin staining; Histology; Hodgkin lymphoma; Image processing; Lymph nodes; Lymphocytes; Pathologists |
Volume: | 16 |
Issue: | (1): e1007516 |
Page Number: | 21 |
First Page: | 1 |
Last Page: | 21 |
Note: | Copyright: © 2020 Hannig et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. |
HeBIS-PPN: | 461425165 |
Institutes: | Informatik und Mathematik / Informatik |
Medizin / Medizin | |
Dewey Decimal Classification: | 5 Naturwissenschaften und Mathematik / 57 Biowissenschaften; Biologie / 570 Biowissenschaften; Biologie |
6 Technik, Medizin, angewandte Wissenschaften / 61 Medizin und Gesundheit / 610 Medizin und Gesundheit | |
Sammlungen: | Universitätspublikationen |
Licence (German): | Creative Commons - Namensnennung 4.0 |