title: [Multidimensional analysis of automatically measured karyometric data on pituitary adenomas].
abstract: 131 pituitary adenomas (50 growth hormone-secreting adenomas, 19 prolactinomas, 7 adenomas associated with Cushing's disease and 55 endocrine-inactive adenomas) have been investigated morphometrically and densitometrically by use of a system for automated microscope picture analysis (AMBA). To classify the adenomas as good as possible we used a hierarchically structured classifier which uses the measured parameters. The adenomas associated with Cushing's disease differed mostly from the inactive tumors in their karyometric features. We found similar differences for growth hormone-secreting adenomas, whereas prolactinomas showed only small differences. Partly clear differences by multidimensional analysis appeared between adenomas associated with Cushing's disease, somatotropic adenomas and prolactinomas. Most of the clinically inactive tumours (37/55) showed similarities with the active adenomas. Only in 18 inactive tumors we could not find feature combinations corresponding with those of endocrine-active adenomas.
mesh_terms: D000172:Acromegaly; D000236:Adenoma / Q000145:classification / Q000378:metabolism / Q000648:ultrastructure*; D002467:Cell Nucleus / Q000648:ultrastructure; D003480:Cushing Syndrome; D013006:Growth Hormone / Q000378:metabolism; D006801:Humans; D007620:Karyometry / Q000379:methods; D010911:Pituitary Neoplasms / Q000145:classification / Q000378:metabolism / Q000648:ultrastructure*; D011388:Prolactin / Q000378:metabolism
chemical_list: D011388:Prolactin; D013006:Growth Hormone
vernacular_title: Mehrdimensionale Analyse automatisch gewonnener karyometrischer Daten von Hypophysenadenomen.