TY - JOUR A1 - Röhrl, Norbert A1 - Iglesias-Rozas, José R. A1 - Weidl, Galia T1 - A modern reproducible method for the histologic grading of astrocytomas with statistical classification tools T2 - Analytical and quantitative cytology and histology / the International Academy of Cytology [and] American Society of Cytology N2 - To investigate whether statistical classification tools can infer the correct World Health Organization (WHO) grade from standardized histologic features in astrocytomas and how these tools compare with GRADO-IGL, an earlier computer-assisted method. A total of 794 human brain astrocytomas were studied between January 1976 and June 2005. The presence of 50 histologic features was rated in 4 categories from 0 (not present) to 3 (abundant) by visual inspection of the sections under a microscope. All tumors were also classified with the corresponding WHO grade between I and IV. We tested the prediction performance of several statistical classification tools (learning vector quantization [LVQ], supervised relevance neural gas [SRNG], support vector machines [SVM], and generalized regression neural network [GRNN]) for this data set. The WHO grade was predicted correctly from histologic features in close to 80% of the cases by 2 modern classifiers (SRNG and SVM), and GRADO-IGL was predicted correctly in > 84% of the cases by a GRNN. A standardized report, based the 50 histologic features, can be used in conjunction with modern classification tools as an objective and reproducible method for histologic grading of astrocytomas. KW - Cytologie KW - Histologie KW - Hirntumor Y1 - 2008 UR - https://opus4.kobv.de/opus4-h-ab/frontdoor/index/index/docId/2179 UR - https://pubmed.ncbi.nlm.nih.gov/18459585/ VL - 2008 IS - 30/1 SP - 33 EP - 8 ER -