AIM: To design a classification tool for the histological assessment of hepatocellular carcinoma (HCC), dysplastic nodules (DN), and macroregenerative nodules (MRN) in cirrhotic liver. METHODS: Two hundred and twelve hepatocellular nodules (106 HCC; 74 MRN; 32 DN) were assessed systematically, quantitatively, and semiquantitatively as appropriate for 10 histological features that have been described as helpful in distinguishing small HCC, DN, and MRN in cirrhotic livers. The data were analyzed by multiple correspondence analysis (MCA). RESULTS: MCA distributed HCC, DN, and MRN as defined by traditional histological evaluation as well as the individual histological variables, in a "malignancy scale". Based on the MCA data representation, we created a classification tool, which categorizes an individual nodular lesion as MRN, DN, or HCC based on the balance of all histological features (i.e., vascular invasion, capsular invasion, tumor necrosis, tumor heterogeneity, reticulin loss, capillarization of sinusoids, trabecular thickness, nuclear atypia, and mitotic activity). The classification tool classified most (83%) of a validation set of 47 nodules in the same way as the routine histological assessment. No discrepancies were present for DN and MRN between the routine histological assignment and the classification tool. Of 25 HCC assigned by routine assessment in the validation set, 8 were assigned to the DN category by the classification tool. CONCLUSION: We have designed a classification tool for the histological assessment of HCC and its putative precursors in cirrhotic liver. Application of this tool systematically records histological features of diagnostic importance in the evaluation of small HCC.
AIM: To design a classification tool for the histological assessment of hepatocellular carcinoma (HCC), dysplastic nodules (DN), and macroregenerative nodules (MRN) in cirrhotic liver. METHODS: Two hundred and twelve hepatocellular nodules (106 HCC; 74 MRN; 32 DN) were assessed systematically, quantitatively, and semiquantitatively as appropriate for 10 histological features that have been described as helpful in distinguishing small HCC, DN, and MRN in cirrhotic livers. The data were analyzed by multiple correspondence analysis (MCA). RESULTS: MCA distributed HCC, DN, and MRN as defined by traditional histological evaluation as well as the individual histological variables, in a "malignancy scale". Based on the MCA data representation, we created a classification tool, which categorizes an individual nodular lesion as MRN, DN, or HCC based on the balance of all histological features (i.e., vascular invasion, capsular invasion, tumor necrosis, tumor heterogeneity, reticulin loss, capillarization of sinusoids, trabecular thickness, nuclear atypia, and mitotic activity). The classification tool classified most (83%) of a validation set of 47 nodules in the same way as the routine histological assessment. No discrepancies were present for DN and MRN between the routine histological assignment and the classification tool. Of 25 HCC assigned by routine assessment in the validation set, 8 were assigned to the DN category by the classification tool. CONCLUSION: We have designed a classification tool for the histological assessment of HCC and its putative precursors in cirrhotic liver. Application of this tool systematically records histological features of diagnostic importance in the evaluation of small HCC.
Authors: J Bruix; M Sherman; J M Llovet; M Beaugrand; R Lencioni; A K Burroughs; E Christensen; L Pagliaro; M Colombo; J Rodés Journal: J Hepatol Date: 2001-09 Impact factor: 25.083
Authors: F Kondo; M Ebara; N Sugiura; K Wada; K Kita; N Hirooka; Y Nagato; Y Kondo; M Ohto; K Okuda Journal: Hepatology Date: 1990-09 Impact factor: 17.425