MINIMUM SPANNING TREE ANALYSIS IN ADVANCED OVARIAN-CARCINOMA - AN INVESTIGATION OF SAMPLING METHODS, REPRODUCIBILITY AND CORRELATION WITH HISTOLOGIC GRADE

OBJECTIVE: To investigate sampling methods and reproducibility of mini mum spanning tree (MST) variables in advanced ovarian cancer and their discriminative power for histologic grade. STUDY DESIGN: For the meth odologic investigation, 30 cases of advanced ovarian cancer of the com mon epithelial types were used. These cases were equally distributed o ver the three histologic grades according to independent, ''blind'' as sessments by three observers: well (n = 10), moderately (n = 10) and p oorly (n = 10) differentiated. Additionally, the discriminative power of the MST variables for histologic grade was assessed in 64 cases (do uble-blind agreement upon grade by two observers). Measurements were p erformed on hematoxylin-eosin-stained tumor sections. In each field of vision the centers of gravity of tumor cell nuclei were interactively marked using a digitizing video overlay system, and an MST was comput ed. From each MST the number of points, total line length, average lin e length, minimum line length, maximum line length and percentage of p oints with one, two, three and four neighbors were obtained. Optimal p erformance (coefficient of error < 5%) of the method was established w hen the MST was constructed in 12 systematically randomly selected fie lds of vision at a final magnification of 1,900 x. RESULTS: Intraobser ver and interobserver reproducibility showed good correlation coeffici ents for most MST variables. Univariate analysis revealed that total, average between the three histologic grades. With a jackknifed stepwis e discriminant analysis an overall correct classification of 75% for t he three histologic grades was achieved in 64 cases, using the average line length, standard deviation of the line length and total line len gth. CONCLUSION: MST syntactic structure analysis offers an easy, fact and very reproducible technique that may be of help in objective grad ing of advanced ovarian cancers. Further studies are under way to inve stigate the prognostic value of MST analysis in advanced ovarian cance r.