Abstract
BackgroundIntrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.PurposeThis study aimed to develop and validate a radiomics-based nomogram for predicting MVI in ICC patients preoperatively.MethodsA total of 163 pathologically confirmed ICC patients (training cohort: n = 130; validation cohort: n = 33) with postoperative Ga-DTPA-enhanced MR examination were enrolled, and a time-independent test cohort (n = 24) was collected for external validation. Univariate and multivariate analyses were used to determine the independent predictors of MVI status, which were then incorporated into the MVI prediction nomogram. Least absolute shrinkage and selection operator logistic regression was performed to select optimal features and construct radiomics models. The prediction performances of models were assessed by receiver operating characteristic (ROC) curve analysis. The performance of the MVI prediction nomogram was evaluated by its calibration, discrimination, and clinical utility.ResultsLarger tumor size (p = 0.003) and intrahepatic duct dilatation (p = 0.002) are independent predictors of MVI. The final radiomics model shows desirable and stable prediction performance in the training cohort (AUC = 0.950), validation cohort (AUC = 0.883), and test cohort (AUC = 0.812). The MVI prediction nomogram incorporates tumor size, intrahepatic duct dilatation, and the final radiomics model and achieves excellent predictive efficacy in training cohort (AUC = 0.953), validation cohort (AUC = 0.861), and test cohort (AUC = 0.819), fitting well in calibration curves (p > 0.05). Decision curve and clinical impact curve further confirm the clinical usefulness of the nomogram.ConclusionThe nomogram incorporating tumor size, intrahepatic duct dilatation, and the final radiomics model is a potential biomarker for preoperative prediction of the MVI status in ICC patients.
Highlights
Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer and accounts for 10%–15% of all cases, which arises from cholangiocytes of intrahepatic bile ducts or bile ductules [1–3]
We focused on mass-forming ICCs and aimed to develop and validate a radiomics nomogram integrating clinical, imaging, and radiomics features for preoperative prediction of microvascular invasion (MVI) in ICC
Univariate analysis of clinicoradiologic characteristics indicates that serum carcinoembryonic antigen (CEA) level (p = 0.035; OR = 2.716, 95% CI: 1.065–6.918), serum carbohydrate antigen 19-9 (CA199) level (p = 0.030; OR = 2.346, 95% CI: 1.092–5.139), EdmondsonSteiner grade (p = 0.021; OR = 3.126, 95% CI: 1.254–8.977), tumor size (p < 0.001; OR = 1.033, 95% CI: 1.016–1.052), tumor morphology (p= 0.071; OR = 1.604, 95% CI: 0.964–2.708), and intrahepatic duct dilatation (p < 0.001; OR =5.610, 95% CI: 2.505– 13.308) are significantly associated with MVI
Summary
Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer and accounts for 10%–15% of all cases, which arises from cholangiocytes of intrahepatic bile ducts or bile ductules [1–3]. Several studies have reported increasing incidence of ICC in the last decades [5, 6] and the 5year survival rate is still lower than 10% [7]. Hepatectomy is still the most effective treatment for long-term survival of ICC patients [8, 9], and several poor prognostic factors have been reported, including lymph node metastasis, microvascular invasion (MVI), tumor size ≥5 cm, and multiple nodules [10]. As a poor prognostic factor, MVI correlates early recurrence and poor outcomes and is an independent factor for overall survival in ICC patients [12, 13]. Intrahepatic cholangiocarcinoma (ICC) is the second most common primary liver cancer with increasing incidence in the last decades. Microvascular invasion (MVI) is a poor prognostic factor for patients with ICC, which correlates early recurrence and poor prognosis, and it can affect the selection of personalized therapeutic regime.
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