Morphometric distinction of sclerosing adenosis from tubular carcinoma of the breast.
Objective features have been identified that assist in distinguishing sclerosing adenosis from tubular carcinoma of the breast. Hematoxylin and eosin stained paraffin sections of 18 sclerosing adenoses and 18 tubular carcinomas were studied using a TAS Plus image analysis system. Histological measurements from lumens and glands included stereologic features of architecture and morphometry of size and shape (the latter by Fourier coefficients). Cytological measurements included nuclear area, perimeter, diameter and formfactor. Initial analysis suggested utility for several individual features. However, after a modified Bonferroni procedure only two of the features were statistically significant, i.e. the coefficient of variation of luminal form factor and the surface density of glands. Multivariate discriminant analysis using these two variables correctly classified 86% of the cases, with three adenoses and two carcinomas misclassified. Validity of the discriminant rules was supported by classification using measurements from a separate, independent set of cases (ten sclerosing adenoses and nine tubular carcinomas). The classification function computed from the first set misclassified only one case from the second set, a tubular carcinoma, leaving 95% of the cases successfully categorized. Chi square test for 2 x 2 contingency tables gave a p-value < 0.001 for both sets of cases. The results suggest that morphometric features are helpful in distinguishing tubular carcinoma from sclerosing adenosis and point out the need for conservative analysis of high-dimensional data sets.
Becker
R L
RL
Department of Cellular Pathology, Armed Forces Institute of Pathology, Washington D.C.
Mikel
U V
UV
O'Leary
T J
TJ
D000230:Adenocarcinoma / Q000473:pathology*; D001943:Breast Neoplasms / Q000473:pathology*; D003937:Diagnosis, Differential; D016002:Discriminant Analysis; D005260:Female; D005348:Fibrocystic Breast Disease / Q000473:pathology*; D006801:Humans; D007091:Image Processing, Computer-Assisted; D012598:Sclerosis