Gadoxetic acid-enhanced MRI with a focus on LI-RADS v2018 imaging features predicts the prognosis after radiofrequency ablation in small hepatocellular carcinoma.
Front Oncol
; 13: 975216, 2023.
Article
en En
| MEDLINE
| ID: mdl-36816925
ABSTRACT
Introduction:
Gadoxetic acid-enhanced magnetic resonance imaging (MRI) contributes to evaluating the prognosis of small hepatocellular carcinoma (sHCC) following treatment. We have investigated the potential role of gadoxetic acid-enhanced MRI based on LI-RADS (Liver Imaging Reporting and Data System) v2018 imaging features in the prognosis prediction of patients with sHCC treated with radiofrequency ablation (RFA) as the first-line treatment and formulated a predictive nomogram.Methods:
A total of 204 patients with sHCC who all received RFA as the first-line therapy were enrolled. All patients had undergone gadoxetic acid-enhanced MRI examinations before RFA. Uni- and multivariable analyses for RFS were assessing using a Cox proportional hazards model. A novel nomogram was further constructed for predicting RFS. The clinical capacity of the model was validated according to calibration curves, the concordance index (C-index), and decision curve analyses.Results:
Alpha fetoprotein (AFP) > 100 ng/ml (HR, 2.006; 95% CI, 1.111-3.621; P = 0.021), rim arterial phase hyperenhancement (APHE) (HR, 2.751; 95% CI, 1.511-5.011; P = 0.001), and targetoid restriction on diffusion-weighted imaging (DWI) (HR, 3.289; 95% CI, 1.832-5.906; P < 0.001) were considered as the independent risk features for recurrence in patients with sHCC treated with RFA. The calibration curves and C-indexes (C-index values of 0.758 and 0.807) showed the superior predictive performance of the integrated nomogram in both the training and validation groups.Discussion:
The gadoxetic acid-enhanced MRI features based on LI-RADS v2018, including rim APHE, targetoid restriction on DWI, and the AFP level, are the independent risk factors of recurrence in patients with sHCC treated with RFA as the first-line therapy. The predictive clinical-radiological nomogram model was constructed for clinicians to develop individualized treatment and surveillance strategies.
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Tipo de estudio:
Prognostic_studies
/
Risk_factors_studies
Idioma:
En
Revista:
Front Oncol
Año:
2023
Tipo del documento:
Article
País de afiliación:
China