Affiliations: Institut für Pathologie (Neuropathologie).
Katharinenhospital,Stuttgart | Institut für Biomedizinische Technik, Stuttgart,
Note:  Address for correspondence: Priv.-Doz. Dr. med. J.R.
Iglesias-Rozas Klinikum Stuttgart. Katharinenhospital Institut für
Pathologie (Neuropathologie) (Ärzt. Dir.: Prof. Dr. med. A. Bosse)
Kriegsbergstr. 60 D-70174 Stuttgart Tel: ++ 49 +711/278 4918 Fax: ++49 +711/278
4909 E-Mail: [email protected][email protected]
Abstract: The histological variability of glioblastomas precludes the modern
assimilation of theses tumors into a single histological tumor group. There is
evidence for the genetic variability of glioblastomas. As an alternative to
statistical evaluation we investigated 1266 human glioblastomas in order to
discover whether they can be correct classified using SOM (Self-Organizing
Maps). In all tumors 45 histological features including age and sex of the
patients, were examined. The description of the presence of a specific
histological feature is given on a scale of four class. No prior statistical
knowledge or clustering is needed. Five clusters of glioblastomas with a
maximum significance were found. Cluster C1 contains glioblastomas with a great
component of glioblasts and astroblasts. Cluster C2 includes 93.75% of all
gliosarcomas. Cluster C3 contains 80.28 % of all monomorphe glioblastomas.
Cluster C4 shows similarities with the features of relative poverty of vessels,
scanty vessels anomalies and little thrombosis. Cluster C5 contains 60.68% of
all giant cell glioblastomas. Placing a series of component windows with their
maps side by side allows the immediate investigation of the dependencies on
variables. The nets SOM allow in our study a realistic histological
classification, comparable to the actual classification made by WHO, as well as
the visualization of multidimensional histological features of human
glioblastomas. With SOM one can learn to discriminate, discard and delete data,
select meaningful histological and clinic variables and consecutively to
influence the results of patients' management.