Title:Ultrasound-based Radiomics Predicts Short-term Outcomes in Hepatitis B
Virus-related Acute-on-chronic Liver Failure
Volume: 20
Author(s): Xingzhi Huang, Songsong Yuan, Pan Xu, Yaohui Li and Aiyun Zhou*
Affiliation:
- Department of Ultrasonography, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China
Keywords:
Acute-on-chronic liver failure, Hepatitis B virus, Radiomics, Ultrasound, Machine learning, Nomogram.
Abstract:
Background:
The prognosis in hepatitis B virus-associated acute-on-chronic liver failure (HBV-ACLF) is challenging due to heterogeneity. Radiomics may
enable noninvasive outcome prediction.
Objective:
This study aimed to evaluate ultrasound-based radiomics for predicting outcomes in HBV-ACLF.
Methods:
We enrolled 264 HBV-ACLF patients, dividing them into a training cohort (n=184) and a validation cohort (n=80). From hepatic ultrasound
images, 455 radiomic features were extracted. Radiomics-based phenotypes were identified through unsupervised hierarchical clustering. A
radiomic signature was developed using a Cox-LASSO algorithm to predict 30-day mortality. Furthermore, we integrated the signature with
independent clinical predictors via multivariate Cox regression to construct a combined clinical-radiomic nomogram (CCR-nomogram). Integrated
discrimination improvement (IDI) and net reclassification improvement (NRI) assessed performance improvements achieved by adding radiomic
features to clinical data.
Results:
Both clustering and radiomic signature identified two distinct subgroups with significant differences in clinical characteristics and 30-day
prognosis. In the training cohort, the signature achieved a C-index of 0.746, replicated in validation with a C-index of 0.747. The CCR-nomogram
achieved C-indices of 0.834 and 0.819 for the training and validation cohorts. Incorporating radiomic features significantly improved the CCRnomogram
over the signature and clinical-only models, evidenced by IDI of 0.108-0.264 and NRI of 0.292-0.540 in both cohorts (all p0.05).
Conclusion:
Ultrasound-based radiomics offered prognostic information complementary to clinical data and demonstrated potential to enhance outcome
prediction in HBV-ACLF.