Cells aspirated from breast lesions and smeared on slides were subjected to computer assisted morphometric analysis. Three groups of cases were studied. The first were those collected from patients with known benign and malignant lesions. The second group were 143 unselected consecutive aspirates from breast lesions and the third, a group with a needle aspirate cytodiagnosis "suspicious of malignancy". The analysis showed the malignant cells to have larger nuclei with more anisokaryosis and more variation in the nuclear cytoplasmic ratios when compared with benign cells. When this form of semiautomatic analysis was applied to the "suspicious" group the accuracy of cytodiagnosis was improved.

The relation between the DNA distribution pattern and the variables DNA content and nuclear area was investigated in 73 breast carcinomas. According to the DNA patterns, the tumors were subclassified into groups I, 11, 111, and IV (Auer's classification). The Auer's classes correlate with prognosis. In this investigation it was shown that Auer's classes strongly correlate with the standard deviation of DNA content and mean nuclear area. The carcinomas were subclassified using data of DNA content and nuclear area. For the establishment of this subclassification, multivariate analysis was applied. It was evident that Auer's group 111 was a hybrid group. Therefore a second classification rule was calculated without the data of Auer's group 111. This second classification rule was even more successful in determining the Auer's group of each individual case. Our investigation shows that it is possible to subclassify breast carcinomas objectively using DNA content and nuclear area of the tumor cells.