The combined use of the decision tree technique and the computer-assisted microscope analysis of feulgen-stained nuclei as an aid for astrocytic tumor aggressiveness characterization.

A systematic and thus objective method is proposed to characterize astrocytic tumor aggressiveness. This method relies upon the combined use of a specific decisional algorithm (the decision tree) and 23 parameters which include 15 morphonuclear parameters describing the geometric, densitometric, and textural features of a cell nucleus, and 8 parameters describing the various levels of nuclear DNA content. These 23 parameters were objectively quantified by means of the digital cell image analysis of Feulgen-stained nuclei. This methodology was used to investigate whether it could be applied as a diagnostic tool. The biological model chosen included 12 cell lines adapted to grow in vitro and stemming from 4 astrocytomas (weakly malignant astrocytic tumors) and 6 glioblastomas (highly malignant ones). The 2 additional cell lines were from two medulloblastomas (MED) (2 highly malignant primitive neuro-ectodermal tumors). The results demonstrate unambiguously that it is actually possible to distinguish between low-grade and high-grade tumors on the basis of these parameters, which describe their morphonuclear features and the amount of their nuclear content. However, a clear-cut distinction between these different types of tumors can only be attained when a specific technique is used. In the present case this was the decision tree technique. We were not able to distinguish between these various histopathological groups when we used conventional statistical methods including the one-way-variance analysis of data or the carrying out of the X(2) test.