Abstract

BACKGROUNDPathological manifestations of hepatic tumours are often associated with prognosis. Although surgical specimens (SS) can provide more information, currently, pre-treatment needle core biopsy (NCB) is increasingly showing important value in understanding the nature of liver tumors and even in diagnosis and treatment decisions. However, the concordance of the clinicopathological characteristics and immunohistochemical (IHC) staining between NCB and SS from patients with hepatic tumours were less concerned.AIMTo introduce a more accurate method for interpreting the IHC staining results in order to improve the diagnostic value of hepatic malignancy in NCB samples.METHODA total of 208 patients who underwent both preoperative NCB and surgical resection for hepatocellular carcinoma (HCC) or intrahepatic cholangiocarcinoma (ICC) between 2008 and 2015 were enrolled in this study. The expression of CK19, GPC3, and HepPar1 were detected by IHC staining. Clinicopathological, NCB, and surgical data were collected and analysed using χ2 and kappa statistics.RESULTSMorphologically, the presence of compact tumour nests or a cord-like structure in NCB was considered the primary cause of misdiagnosis of HCC from ICC. The kappa statistic showed a moderate agreement in histomorphology (k = 0.504) and histological grade (k = 0.488) between NCB and SS of the tumours. A 4-tier (+++, ++, +, and -) scoring scheme that emphasized the focal neoplastic cell immunoreactivity of tumour cells revealed perfect concordance of CK19, GPC3 and HepPar1 between NCB and SS (k = 0.717; k = 0.768; k = 0.633). Furthermore, with the aid of a binary classification derived from the 4-tier score, a high concordance was achieved in interpreting the IHC staining of the three markers between NCB and final SS (k = 0.931; k = 0.907; k = 0.803), increasing the accuracy of NCB diagnosis C (k = 0.987; area under the curve = 0.997, 95%CI: 0.990-1.000; P < 0.001).CONCLUSIONThese findings imply that reasonable interpretation of IHC results in NCB is vital for improving the accuracy of tumour diagnosis. The simplified binary classification provides an easy and applicable approach.

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