Objective: To explore data from a set of cases of adrenal cortical adenomas with different endocrine syndromes and carcinomas to determine whether quantitative image analysis of nuclear features might be used to separate the groups.
Study design: Fifteen adrenal cortical tumors in which clinical information and optimally preserved, paraffin-embedded tissue were available were used. There were 10 adenomas and 5 carcinomas. Among the adenomas, five were associated with primary hyperaldosteronism (Conn's syndrome) and five with Cushing's syndrome. Five-micrometer-thick sections were stained with hematoxylin and eosin. In each case 50 nuclei were measured, and a number of morphometric and densitometric features were extracted. The data were subjected to multivariate analysis.
Results: Quantitative analysis showed that nuclei from adrenal carcinomas are larger than those from adenomas. Total optical density (OD) had a near-diploid distribution in the adenomas, while it was clearly aneuploid in the carcinomas. The pixel OD histograms were almost identical for all groups. Differences in nuclear chromatin texture were found between adenomas and carcinomas and also between the two adenoma categories. Multivariate analysis showed good discrimination between carcinomas and adenomas (Wilks lambda = .628, P < .0001) and between adenomas. However, based on Bayesian decision boundaries, 20-25% of carcinoma nuclei could be expected to be in the range of adenoma, and about 12% of Cushing's adenoma nuclei and 15% of Conn's adenoma nuclei would be classified as carcinoma.
Conclusion: Computer-assisted analysis of nuclear characteristics proved useful in identifying and describing differences between groups of tumors arising in the adrenal cortex.