Gd-EOB-DTPA-enhanced MRI radiomics to predict vessels encapsulating tumor clusters (VETC) and patient prognosis in hepatocellular carcinoma.
Eur Radiol
; 32(2): 959-970, 2022 Feb.
Article
en En
| MEDLINE
| ID: mdl-34480625
ABSTRACT
OBJECTIVES:
The study was to develop a Gd-EOB-DTPA-enhanced MRI radiomics model for preoperative prediction of VETC and patient prognosis in hepatocellular cancer (HCC).METHODS:
The study included 182 (training cohort 128; validation cohort 54) HCC patients who underwent preoperative Gd-EOB-DTPA-enhanced MRI. Volumes of interest including intratumoral and peritumoral regions were manually delineated in the hepatobiliary phase images, from which 1316 radiomics features were extracted. The least absolute shrinkage and selection operator (LASSO) and multivariable logistic regression were used to select the useful features. Clinical, intratumoral, peritumoral, combined radiomics, and clinical radiomics models were established using machine learning algorithms. The Kaplan-Meier survival analysis was used to assess early recurrence and progression-free survival (PFS) in the VETC + and VETC- patients.RESULTS:
In the validation cohort, the area under the curves (AUCs) of radiomics models were higher than that of the clinical model using random forest (all p < 0.05). The peritumoral radiomics model (AUC = 0.972;95% confidence interval [CI]0.887-0.998) had significantly higher AUC than intratumoral model (AUC = 0.919; 95% CI 0.811-0.976) (p = 0.044). There were no significant differences in AUC between intratumoral or peritumoral radiomics model (PR) and combined radiomics model (p > 0.05). Early recurrence and PFS were significantly different between the PR-predicted VETC + and VETC- HCC patients (p < 0.05). PR-predicted VETC was independent predictor of early recurrence (hazard ratio [HR] 2.08[1.31-3.28]; p = 0.002) and PFS (HR 1.95[1.20-3.17]; p = 0.007).CONCLUSIONS:
The intratumoral or peritumoral radiomics model may be useful in predicting VETC and patient prognosis preoperatively. The peritumoral radiomics model may yield an incremental value over intratumoral model. KEY POINTS ⢠Radiomics models are useful for predicting vessels encapsulating tumor clusters (VETC) and patient prognosis preoperatively. ⢠Peritumoral radiomics model may yield an incremental value over intratumoral model in prediction of VETC. ⢠Peritumoral radiomics-model-predicted VETC was an independent predictor of early recurrence and progression-free survival.Palabras clave
Texto completo:
1
Colección:
01-internacional
Base de datos:
MEDLINE
Asunto principal:
Carcinoma Hepatocelular
/
Neoplasias Hepáticas
Tipo de estudio:
Observational_studies
/
Prognostic_studies
/
Risk_factors_studies
Límite:
Humans
Idioma:
En
Revista:
Eur Radiol
Asunto de la revista:
RADIOLOGIA
Año:
2022
Tipo del documento:
Article
País de afiliación:
China