Prediction of insufficient hepatic enhancement during the Hepatobiliary phase of Gd-EOB DTPA-enhanced MRI using machine learning classifier and feature selection algorithms

Gd-EOB-DTPA enhanced MRI based radiomics combined with clinical variables in stratifying hepatic functional reserve in HBV infected patients

PURPOSES

To evaluate radiomics from Gd-EOB-DTPA enhanced MR combined with clinical variables for stratifying hepatic functional reserve in hepatitis B virus (HBV) patients.

METHODS

Our study included 279 chronic HBV patients divided 8:2 for training and test cohorts. Radiomics features were extracted from the hepatobiliary phase (HBP) MR images. Radiomics features were selected to construct a Rad-score which was combined with clinical parameters in two models differentiating hepatitis vs. Child-Pugh A and Child-Pugh A vs. B/C. Performances of these stratifying models were compared using area under curve (AUC).

RESULTS

Rad-score alone discriminated hepatitis vs. Child-Pugh A with AUC = 0.890, 0.914 and Child-Pugh A vs. B/C with AUC = 0.862, 0.865 for the training and test cohorts, respectively. Model 1 [Rad-score + clinical parameters for hepatitis vs. Child-Pugh A] showed AUC = 0.978 for the test cohort, which was higher than ALBI [albumin-bilirubin] and MELD [model for end-stage liver disease], with AUCs of 0.716, 0.799, respectively (p < 0.001, < 0.001). Model 2 [Rad-score + clinical parameters for Child-Pugh A vs. B/C] showed AUC of 0.890 in the test cohort, which was similar to ALBI (AUC = 0.908, p = 0.760), and higher than MELD (AUC = 0.709, p = 0.018).

CONCLUSION

Rad-score combined with clinical variables stratifies hepatic functional reserve in HBV patients.