Optimizing CT and MRI criteria for differentiating intrahepatic mass-forming cholangiocarcinoma and hepatocellular carcinoma.


Journal

Acta radiologica (Stockholm, Sweden : 1987)
ISSN: 1600-0455
Titre abrégé: Acta Radiol
Pays: England
ID NLM: 8706123

Informations de publication

Date de publication:
Mar 2023
Historique:
pubmed: 29 7 2022
medline: 22 3 2023
entrez: 28 7 2022
Statut: ppublish

Résumé

Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options. To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC). A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve. Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871; The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

Sections du résumé

BACKGROUND BACKGROUND
Accurate diagnosis of intrahepatic mass-forming cholangiocarcinoma (IMCC) is crucial with regard to the choice of patient management and treatment options.
PURPOSE OBJECTIVE
To evaluate the feasibility and diagnostic performance of the LI-RADS M (LR-M) targetoid criteria on computed tomography (CT) and gadoxetic acid-enhanced magnetic resonance imaging (EOB-MRI) in differentiating IMCC from hepatocellular carcinoma (HCC).
MATERIAL AND METHODS METHODS
A total of 118 patients with IMCC and HCC were included who underwent CT and EOB-MRI examinations. Multivariate analysis was used to determine the strongest predictors differentiating IMCC from HCC. Using these predictors, a predictive model for differentiating IMCC from HCC was constructed and the performance of the model was confirmed using the receiver operating characteristic curve.
RESULTS RESULTS
Multivariate analyses revealed rim-like arterial phase hyperenhancement (rim APHE) on CT and rim APHE, delayed central enhancement (DCE), and targetoid hepatobiliary phase (HBP) on MRI as independent variables significantly differentiating IMCC from HCC. The multivariate logistic regression model incorporating the three variables on EOB-MRI was constructed with an area under the curve (AUC) of 0.946, sensitivity of 87.80%, specificity of 92.21%, and accuracy of 94.60%. Per the DeLong test, the multivariate logistic regression model showed significantly higher AUC than rim APHE on CT (0.946 vs. 0.871;
CONCLUSION CONCLUSIONS
The multivariate logistic regression model based on rim APHE, DCE, and targetoid HBP on EOB-MRI can effectively distinguish IMCC from HCC and is superior to any other targetoid appearance criterion of LI-RADS on CT and EOB-MRI.

Identifiants

pubmed: 35898164
doi: 10.1177/02841851221113265
doi:

Substances chimiques

Contrast Media 0
Gadolinium DTPA K2I13DR72L

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

926-935

Auteurs

Hongzhen Wu (H)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

Yingying Liang (Y)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

Zihua Wang (Z)

Department of Radiology, 593063Foshan Hospital of Traditional Chinese Medicine, Foshan Guangdong, PR China.

Caihong Tan (C)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

Ruimeng Yang (R)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

Xinhua Wei (X)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

Xinqing Jiang (X)

Department of Radiology, 74668Guangzhou First People's Hospital, School of Medicine, South China University of Technology, Guangzhou, Guangdong, PR China.

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