Time-dependent diffusion MRI combined with enhanced MRI and clinical indicators for preoperative prediction of CK19 expression status in hepatocellular carcinoma: a prospective study

Abstract

Objective: To explore the value of time-dependent diffusion MRI(Td-dMRI) in predicting the expression status of cytokeratin 19(CK19) in hepatocellular carcinoma(HCC) before surgery.

Materials and methods: Prospective inclusion of 72 HCC patients confirmed by surgical pathology (43 CK19-negative and 29 CK19-positive). All patients underwent time-dependent diffusion MRI (Td-dMRI) using a 3.0 T MR scanner before surgery, and quantitative parameters were calculated. Clinical data and MRI features of the patients were collected. Using univariate and multivariate logistic regression analysis to identify the risk factors for CK19 positive expression and establish a predictive model. The diagnostic performance of the model was evaluated using the area under the curve (AUC) of the receiver operating characteristic (ROC) curve, decision curve analysis (DCA), and calibration analysis.

Results: CK19-positive HCC exhibited significantly lower d and higher cellularity compared to CK19-negative HCC. CK19-positive HCC demonstrated significantly higher proportions of AFP (>200 ng/ml), CEA (>5 ng/ml), arterial phase rim enhancement, peritumoral hypointensity on hepatobiliary phase, peritumoral arterial hyperenhancement, and intratumoral necrosis/hemorrhage than CK19-negative HCC. Univariate and multivariate logistic regression analyses identified cellularity, AFP (>200 ng/ml), arterial phase rim enhancement, and peritumoral hypointensity on hepatobiliary phase as independent predictors of CK19 positivity. The combined model incorporating these four factors achieved an AUC of 0.889 (95 % CI: 0.809-0.968), with a sensitivity of 82.8 % and specificity of 86.0 %.

Conclusions: The cellularity value based on Td-dMRI was a potential quantitative biomarker for predicting CK19-positive HCC.

Keywords: Cytokeratin 19; Hepatocellular carcinoma; Nomogram; Quantitative parameters; Time-dependent diffusion MRI.