Morphometric and multivariate statistical methods were used to discrim
inate endometrial carcinoma from benign cells in cytologic studies. Cl
umps of epithelial cells that appeared most diagnostically relevant we
re selected from aspirated samples of 70 endometrial cancer patients.
The cells' cytologic character was reduced to a combination of five qu
antitative parameters-nuclear size, degree of anisokaryosis, nuclear f
orm index, homogeneity of nuclear chromatin texture, and regularity of
nuclear arrangement. The 5-variate cluster analysis demonstrated that
the 70 cases could be classified into three definite groups: Group A
(17 cases) was characterized by cells of small nuclear size, slight an
isokaryosis, homogeneous chromatin texture, and regular nuclear arrang
ement; Group C (12 cases) by cells of large nuclear size, marked aniso
karyosis, heterogeneous chromatin texture, and irregular nuclear arran
gement; and Group B (41 cases) by cells of intermediate parameter valu
es. Group C was derived from 10 cases of adenocarcinoma and 2 of atypi
cal hyperplasia, while Groups A and B were not derived from any cases
of malignancy. The computer-assisted morphometric statistical method c
an objectively classify the endometrial cells into malignant and benig
n, with improved validity and reproducibility. The cytopathologic find
ing, if detected by this method, may serve as a surrogate endpoint bio
marker. (C) 1995 Wiley Liss, Inc.