A STUDY OF HEPATOCELLULAR-CARCINOMA USING MORPHOMETRIC AND DENSITOMETRIC IMAGE-ANALYSIS

Hepatocellular carcinoma is often difficult to diagnose in cytologic m aterial and biopsy specimens. To demonstrate the utility of image anal ysis in discriminating benign and malignant hepatocytes, 42 malignant cell groups were compared with 26 benign cell groups with a wide range of nuclear morphology in hematoxylin and eosin-stained histologic sec tions from 42 patients with hepatocellular carcinoma. Nuclear measurem ents were performed with a relatively inexpensive microcomputer-based image analysis system using a highly flexible imaging software package . Twenty-two nuclear morphometric and densitometric parameters were ev aluated. The best single discriminator of benign and malignant cells w as the nuclear major axis. Classification of the test samples using op timized linear discriminant functions achieved the following positive predictive values (PV+) and negative predictive values (PV-) for hepat ocellular carcinoma: 95.0% PV+ and 85.7% PV- for the major axis; 90.5% PV+ and 84.6% PV- for five densitometric parameters; 100% PV+ and 86. 7% PV- for three morphometric parameters; and 95.5% PV+ and 100% PV- f or nine combined morphometric/densitometric parameters. These results demonstrate that multivariate linear discriminant functions of nuclear features measured by image analysis can be used to classify benign an d malignant hepatocytes accurately.