Enhancement patterns of intrahepatic cholangiocarcinoma: comparison between contrast-enhanced ultrasound and contrast-enhanced CT

2008 ◽  
Vol 81 (971) ◽  
pp. 881-889 ◽  
Author(s):  
L-D CHEN ◽  
H-X XU ◽  
X-Y XIE ◽  
M-D LU ◽  
Z-F XU ◽  
...  
2012 ◽  
Vol 56 ◽  
pp. S283-S284
Author(s):  
M. Iavarone ◽  
S. Vavassori ◽  
A. Sangiovanni ◽  
M. Fraquelli ◽  
L.V. Forzenigo ◽  
...  

2021 ◽  
Vol 11 ◽  
Author(s):  
Fei Xiang ◽  
Shumei Wei ◽  
Xingyu Liu ◽  
Xiaoyuan Liang ◽  
Lili Yang ◽  
...  

BackgroundMicrovascular invasion (MVI) has been shown to be closely associated with postoperative recurrence and metastasis in patients with intrahepatic cholangiocarcinoma (ICC). We aimed to develop a radiomics prediction model based on contrast-enhanced CT (CECT) to distinguish MVI in patients with mass-forming ICC.Methods157 patients were included and randomly divided into training (n=110) and test (n=47) datasets. Radiomic signatures were built based on the recursive feature elimination support vector machine (Rfe-SVM) algorithm. Significant clinical-radiologic factors were screened, and a clinical model was built by multivariate logistic regression. A nomogram was developed by integrating radiomics signature and the significant clinical risk factors.ResultsThe portal phase image radiomics signature with 6 features was constructed and provided an area under the receiver operating characteristic curve (AUC) of 0.804 in the training and 0.769 in the test datasets. Three significant predictors, including satellite nodules (odds ratio [OR]=13.73), arterial hypo-enhancement (OR=4.31), and tumor contour (OR=4.99), were identified by multivariate analysis. The clinical model using these predictors exhibited an AUC of 0.822 in the training and 0.756 in the test datasets. The nomogram combining significant clinical factors and radiomics signature achieved satisfactory prediction efficacy, showing an AUC of 0.886 in the training and 0.80 in the test datasets.ConclusionsBoth CECT radiomics analysis and radiologic factors have the potential for MVI prediction in mass-forming ICC patients. The nomogram can further improve the prediction efficacy.


2013 ◽  
Vol 58 (6) ◽  
pp. 1188-1193 ◽  
Author(s):  
Massimo Iavarone ◽  
Fabio Piscaglia ◽  
Sara Vavassori ◽  
Marzia Galassi ◽  
Angelo Sangiovanni ◽  
...  

2019 ◽  
Vol 2019 ◽  
pp. 1-7 ◽  
Author(s):  
Xuelei Ma ◽  
Wenwu Ling ◽  
Fan Xia ◽  
Yifan Zhang ◽  
Chenjing Zhu ◽  
...  

Purpose. We described imaging characteristics of different types of lymphomas using contrast-enhanced ultrasound (CEUS) and summarized some simple criteria to distinguish between normal lymph nodes and lymphomatous lymph nodes for clinical diagnosis. Materials and methods. Sixty-one lymphoma patients from 2014 to 2015 with 140 suspicious lymph nodes, who had been confirmed by histology and underwent chemotherapy, were enrolled in our study. The responses to chemotherapy were recorded by PET/CT, contrast-enhanced CT, or CEUS. Results. We summarized the CEUS enhancement patterns as two types when detecting lymphomatous lymph nodes, which could be the specific diagnostic criteria: (1) rapid well-distributed hyperenhancement, with 83.1% lesions exhibiting a fast-in hyperenhancement pattern in the arterial phase, and (2) rapid heterogeneous hyperenhancement, with 16.9% lesions exhibiting heterogeneous in the arterial phase. Particularly, we found that all the suspicious lesions of indolent lymphomas were rapid well-distributed hyperenhancement. CEUS successfully identified 117 lymphomatous lymph nodes, while PET/CT and contrast-enhanced CT detected 124 and 113 lymphomatous lymph nodes, respectively. CEUS had an accuracy of 83.57%, and the accuracy of PET/CT and contrast-enhanced CT was 88.57% and 80.71%, respectively (p=0.188). The false-negative rate was 16.43%, 11.43%, and 19.29%, respectively (p=0.188). Conclusion. CEUS could be a useful tool in detecting lymphomatous nodes. A rapid well-distributed hyperenhancement pattern in CEUS could be a useful diagnostic criterion in both aggressive lymphoma and indolent lymphoma. These results can help us distinguish between lymphomatous and benign lymph nodes and make better diagnostic and therapeutic decisions.


Sign in / Sign up

Export Citation Format

Share Document