A radiomic-based model of different contrast-enhanced CT phase for differentiate intrahepatic cholangiocarcinoma from inflammatory mass with hepatolithiasis.

BACKGROUND

Intrahepatic cholangiocarcinoma (ICC) is hard to distinguish from inflammatory mass (IM) complicated with hepatolithiasis in clinical practice preoperatively. This study looked to develop and confirm the radiomics models to make a distinction between ICC with hepatolithiasis from IM and to compare the results of different contrast-enhanced computed tomography (CT) phase.

METHODS

The models were developed in a training cohort of 110 patients from January 2005 to June 2020. Radiomics features were extracted from both arterial phase and portal venous phase contrast-enhanced computed tomography (CT) scans. The radiomics scores based on radiomics features, were built by logistic regression after using the least absolute shrinkage and selection operator (LASSO) method. The rad-scores of two contrast -enhanced CT phases and clinical features were incorporated into a novel model. The performance of the models were determined by theirs discrimination, calibration, and clinical usefulness. The models were externally validated in 35 consecutive patients.

RESULTS

The radiomics signature comprised two features in arterial phase (training cohort, AUC = 0.809, sensitivity 0.700, specificity 0.848, and accuracy 0.774;validation cohort, AUC = 0.790, sensitivity 0.714, specificity 0.800, and accuracy 0.757) and three related features in portal venous phase (training cohort, AUC = 0.801, sensitivity 0.800, specificity 0.717, and accuracy 0.759; validation cohort, AUC = 0.830, sensitivity 0.700, specificity 0.750, and accuracy 0.775) showed significant association with ICC in both cohorts (P < 0.05).We also developed a model only based on clinical variables (training cohort, AUC = 0.778, sensitivity 0.567, specificity 0.891, and accuracy 0.729; validation cohort, AUC = 0.788, sensitivity 0.571, specificity 0.950, and accuracy 0.761). The radiomics-based model contained rad-score of two phases and two clinical factors (CEA and CA19-9) showed the best performance (training cohort, AUC = 0.864, sensitivity 0.867, specificity 0.804, and accuracy 0.836; validation cohort, AUC = 0.843, sensitivity 0.643, specificity 0.980, and accuracy 0.821).

CONCLUSIONS

Our radiomics-based models provided a diagnostic tool for differentiate intrahepatic cholangiocarcinoma (ICC) from inflammatory mass (IM) with hepatolithiasis both in arterial phase and portal venous phase. To go a step further, the diagnostic accuracy will improved by a clinico-radiologic model.