Yang Zhou1,2, Guofeng Zhou2,3, Jiulou Zhang1, Chen Xu4, Xiaolin Wang2, Pengju Xu5,6. 1. Department of Radiology, The First Affiliated Hospital of Nanjing Medical University, Nanjing, 210029, China. 2. Shanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China. 3. Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. 4. Department of Pathology, Zhongshan Hospital, Fudan University, Shanghai, 200032, China. 5. Shanghai Institute of Medical Imaging, No.180 Fenglin Road, Xuhui District, Shanghai, 200032, China. xpjbfc@163.com. 6. Department of Radiology, Zhongshan Hospital, Fudan University, No. 180 Fenglin Road, Xuhui District, Shanghai, 200032, China. xpjbfc@163.com.
Abstract
OBJECTIVE: To develop a radiomics signature based on dynamic contrast-enhanced (DCE) MR images for preoperative prediction of microvascular invasion (MVI) in patients with mass-forming intrahepatic cholangiocarcinoma (IMCC). METHODS: One hundred twenty-six patients with surgically resected single IMCC (34 MVI-positive and 92 MVI-negative) were enrolled and allocated to training and validation cohorts (7:3 ratio). Findings of clinical characteristics and MR features were analyzed. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator (LASSO) regression algorithm in the training cohort. The prediction performance of radiomics signature was evaluated by receiver operating characteristics curve (ROC) analysis. Internal validation was performed on an independent cohort containing 38 patients. RESULTS: Larger tumor size and higher radiomics score were positively correlated with MVI in both training cohort (p < 0.001, < 0.001, respectively) and validation cohort (p = 0.008, 0.001, respectively). The radiomics signature, consisting of seven wavelet features, showed optimal prediction performance in both training (AUC = 0.873) and validation cohorts (AUC = 0.850). CONCLUSION: A radiomics signature derived from DCE-MRI of the liver can be a reliable imaging biomarker for predicting MVI of IMCC, which could aid in tailoring treatment strategies. KEY POINTS: • The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging can be a useful tool to preoperatively predict MVI of IMCC. • Larger tumor size is positively correlated with MVI of IMCC.
OBJECTIVE: To develop a radiomics signature based on dynamic contrast-enhanced (DCE) MR images for preoperative prediction of microvascular invasion (MVI) in patients with mass-forming intrahepatic cholangiocarcinoma (IMCC). METHODS: One hundred twenty-six patients with surgically resected single IMCC (34 MVI-positive and 92 MVI-negative) were enrolled and allocated to training and validation cohorts (7:3 ratio). Findings of clinical characteristics and MR features were analyzed. A radiomics signature was built on the basis of reproducible features by using the least absolute shrinkage and selection operator (LASSO) regression algorithm in the training cohort. The prediction performance of radiomics signature was evaluated by receiver operating characteristics curve (ROC) analysis. Internal validation was performed on an independent cohort containing 38 patients. RESULTS: Larger tumor size and higher radiomics score were positively correlated with MVI in both training cohort (p < 0.001, < 0.001, respectively) and validation cohort (p = 0.008, 0.001, respectively). The radiomics signature, consisting of seven wavelet features, showed optimal prediction performance in both training (AUC = 0.873) and validation cohorts (AUC = 0.850). CONCLUSION: A radiomics signature derived from DCE-MRI of the liver can be a reliable imaging biomarker for predicting MVI of IMCC, which could aid in tailoring treatment strategies. KEY POINTS: • The radiomics signature based on dynamic contrast-enhanced magnetic resonance imaging can be a useful tool to preoperatively predict MVI of IMCC. • Larger tumor size is positively correlated with MVI of IMCC.
Entities:
Keywords:
Diagnosis; Intrahepatic cholangiocarcinoma; Magnetic resonance imaging; Radiomics