Radiomics Model of Dynamic Contrast-Enhanced MRI for Evaluating Vessels Encapsulating Tumor Clusters and Microvascular Invasion in Hepatocellular Carcinoma.
Acad Radiol
; 2024 Jul 17.
Article
em En
| MEDLINE
| ID: mdl-39025700
ABSTRACT
RATIONALE AND OBJECTIVES:
To develop and validate a clinical-radiomics model of dynamic contrast-enhanced MRI (DCE-MRI) for the preoperative discrimination of Vessels encapsulating tumor clusters (VETC)- microvascular invasion (MVI) and prognosis of hepatocellular carcinoma (HCC). MATERIALS ANDMETHODS:
219 HCC patients from Institution 1 were split into internal training and validation groups, with 101 patients from Institution 2 assigned to external validation. Histologically confirmed VETC-MVI pattern categorizing HCC into VM-HCC+ (VETC+/MVI+, VETC-/MVI+, VETC+/MVI-) and VM-HCC- (VETC-/MVI-). The regions of intratumor and peritumor were segmented manually in the arterial, portal-venous and delayed phase (AP, PP, and DP, respectively) of DCE-MRI. Six radiomics models (intratumor and peritumor in AP, PP, and DP of DCE-MRI) and one clinical model were developed for assessing VM-HCC. Establishing intra-tumoral and peri-tumoral models through combining intratumor and peritumor features. The best-performing radiomics model and the clinical model were then integrated to create a Combined model.RESULTS:
In institution 1, pathological VM-HCC+ were confirmed in 88 patients (training set 61, validation set 27). In internal testing, the Combined model had an AUC of 0.85 (95% CI 0.76-0.93), which reached an AUC of 0.75 (95% CI 0.66-0.85) in external validation. The model's predictions were associated with early recurrence and progression-free survival in HCC patients.CONCLUSIONS:
The clinical-radiomics model offers a non-invasive approach to discern VM-HCC and predict HCC patients' prognosis preoperatively, which could offer clinicians valuable insights during the decision-making phase.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Idioma:
En
Revista:
Acad Radiol
Assunto da revista:
RADIOLOGIA
Ano de publicação:
2024
Tipo de documento:
Article