A Study of Hepatocellular Carcinoma Using Morphometric and Densitometric Image Analysis

Abstract

Hepatocellular carcinoma is often difficult to diagnose in cytologic material and biopsy specimens. To demonstrate the utility of image analysis 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 sections from 42 patients with hepatocellular carcinoma. Nuclear measurements 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 evaluated. The best single discriminator of benign and malignant cells was the nuclear major axis. Classification of the test samples using optimized linear discriminant functions achieved the following positive predictive values (PV+) and negative predictive values (PV-) for hepatocellular 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- for 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 and malignant hepatocytes accurately.

Diagnostic Value of Computerized Nuclear Morphometry for the Prediction of Malignancy in Liver Fine Needle Aspiration Cytology

“…A number of studies have shown computerized morphometry could be a useful diagnostic tool for differential diagnosis and prognostic evaluation of various tumors in pathology and cytology. [2][3][4][14][15][16][17][18][19][20][21][22][23][24][25][26][27][28][29][30][31][32][33] In liver FNAC, a series of suitable values for morphometric parameters have not been constructed in the differential diagnosis of hepatocytes with regenerative atypia and WD-HCC. In this study we used a computerassisted image analysis system to evaluate the display of chosen nuclear parameters in hepatocytes with regenerative atypia and WD-HCC in liver FNAC smears.…”

“…and hepatocytes with regenerative atypia. [2][3][4] Numerous studies have shown the discrimination of WD-HCC from dysplasia or atypical hepatocytes in cirrhosis according to cytomorphologic features. [5][6][7][8][9][10][11][12][13] However, based on the equivocation of cell morphology features presented on FNAC, the diagnosis may vary among cytopathologists.…”

A morphometric model to minimize subjectivity in the histological assessment of hepatocellular carcinoma and its precursors in cirrhosis

“…We considered solitary arteries, reticulin loss, capillarization of sinusoids, and cytological atypia as the components of the classification tool most suitable for morphometry. In terms of cytological atypia, we carried out a nuclear morphometric analysis including the number in unit volume and size distribution of hepatocyte nuclei and mean hepatocyte nuclear diameter, as indicated by other authors (Erler et al, 1993b). The nuclear/cytoplasmic ratio was also derived, as appropriate.…”

The application of image analysis and neural network technology to the study of large-cell liver-cell dysplasia and hepatocellular carcinoma

“…Each case is assigned to the closest class, thus ''resubTwo hundred nuclei were measured from each slide and the nuclear stituting'' the ''diagnosis'' originally given by the pathologist. 26,29 image profiles sorted into two predefined classes of increasing DNA mass. NN Class 1 was defined as having a nuclear area ranging from 10 to…”

“…One of 12 LCD was diploid, 6 of 12 aneuploid, and 5 dysplastic hepatocytes with those of benign and malignant hepatocytes. 26,27,39,40 Very few studies, however, have comof 12 multiploid. Fourteen HCC were diploid, 24 of 40 aneuploid, and 2 of 40 multiploid.…”