The vascular profile of regenerative and dysplastic nodules of the cirrhotic liver: Implications for diagnosis and classification
Open Access
- 1 November 1999
- journal article
- research article
- Published by Wolters Kluwer Health in Hepatology
- Vol. 30 (5) , 1174-1178
- https://doi.org/10.1002/hep.510300507
Abstract
We investigated the angiogenic phenotype of regenerative and dysplastic hepatocellular nodules to assess whether these lesions have distinct vascular profiles compared with the adjacent nonneoplastic or malignant liver. Forty-three liver nodules surgically removed from 18 patients were classified into regenerative and dysplastic categories. Serial sections of each nodule, adjacent cirrhotic liver (16 patients), and associated hepatocellular carcinoma (HCC) (6 patients), have been immunostained against CD31 and α-smooth muscle actin (αSMA) to detect capillary and muscular vessels. The study included 20 large regenerative nodules (LRNs), 13 low-grade dysplastic nodules (LGDNs), and 10 high-grade dysplastic nodules (HGDNs). The number of both capillary units and unpaired arteries was significantly increased in HGDNs and malignant lesions over LGDNs, regenerative, and cirrhotic nodules (P < .01), which showed an overlapping vascular profile. In addition, the number of capillary units, but not that of unpaired arteries, was significantly increased in HCC compared with HGDNs (P < .01). These results show that certain angiogenic features segregate HGDNs from other nonmalignant nodules such as LRNs and LGDNs. The former group of lesions is similar to HCC whereas the latter group is undistinguishable from the adjacent cirrhosis as far as their vascular profile is concerned. The adopted investigative approach does not support the morphological distinction between LRNs and LGDNs although it suggests that HGDNs are likely advanced precursors of HCC. An abnormal number of capillary units and/or unpaired arteries in a nonmalignant hepatocellular nodule can be diagnostically helpful to identify a precancerous lesion.Keywords
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