Systematic bioinformatics analysis of whole slide images reveals significant neighborhood preferences of tumor cells in Hodgkin lymphoma

ABSTRACT: In pathology, tissue images are mainly evaluated using a light microscope, relying on the expertise and experience of pathologists. There is a great demand on computational methods to quantify and standardize histological observations. Thus, computational quantification methods become more and more essential to evaluate tissue images. In particular, the distribution of tumor cells is 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 special tumor arising in lymph nodes, and inflammation of lymph nodes called lymphadenitis. We considered properties of more than 400; 000 immuno-histochemically stained, CD30-positive cells in 35 whole slide images of tissue sections from the main subtypes of the classical Hodgkin lymphoma, nodular sclerosis and mixed cellularity, as well as from lymphadenitis, which describes a non-malignant inflammation of the lymph node. We found that, according to their morphological features, cells of specific morphology exhibit significant preferences for and aversions to cells of certain morphology as spatial nearest neighbor. This information is important to valuate 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 significant neighborhood relations of CD30-positive tumor cells in the different lymph node types. The approach is general and can easily be applied to whole slide image analysis of other tumor types.

SUBMITTER: Jörg Ackermann 

PROVIDER: S-BSST228 | biostudies-other |

REPOSITORIES: biostudies-other