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Preoperative prediction of postsurgical outcomes in mass-forming intrahepatic cholangiocarcinoma based on clinical, radiologic, and radiomics features

Authors
Park, Hyo JungPark, BumwooPark, Seo YoungChoi, Sang HyunRhee, HyungjinPark, Ji HoonCho, Eun-SukYeom, Suk-KeuPark, SumiPark, Mi-SukLee, Seung Soo
Issue Date
Nov-2021
Publisher
SPRINGER
Keywords
Cholangiocarcinoma; Image processing; Multidetector computed tomography; Precision medicine; Prognosis; computer-assisted
Citation
EUROPEAN RADIOLOGY, v.31, no.11, pp.8638 - 8648
Indexed
SCIE
SCOPUS
Journal Title
EUROPEAN RADIOLOGY
Volume
31
Number
11
Start Page
8638
End Page
8648
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/135833
DOI
10.1007/s00330-021-07926-6
ISSN
0938-7994
Abstract
Objectives Current prognostic systems for intrahepatic cholangiocarcinoma (IHCC) rely on surgical pathology data and are not applicable to a preoperative setting. We aimed to develop and validate preoperative models to predict postsurgical outcomes in mass-forming IHCC patients based on clinical, radiologic, and radiomics features. Methods This multicenter retrospective cohort study included patients who underwent curative-intent resection for mass-forming IHCC. In the development cohort (single institution data), three preoperative multivariable Cox models for predicting recurrence-free survival (RFS) were constructed, including the clinical-radiologic, radiomics, and clinical-radiologic-radiomics (CRR) models based on clinical and CT findings, CT-radiomics features, and a combination of both, respectively. Model performance was evaluated in the test cohort (data from five institutions) using Harrell's C-index and compared with postoperative prognostic systems. Results A total of 345 patients (233, development cohort; 112, test cohort) were evaluated. The clinical-radiologic model included five independent CT predictors (infiltrative contour, multiplicity, periductal infiltration, extrahepatic organ invasion, and suspicious metastatic lymph node) and showed similar performance in predicting RFS to the radiomics model (C-index, 0.65 vs. 0.68; p = 0.43 in the test cohort). The CRR model showed significantly improved performance (C-index, 0.71; p = 0.01) than the clinical-radiologic model and demonstrated similar performance to the postoperative prognostic systems in predicting RFS (C-index, 0.71-0.73 vs. 0.70-0.73; p >= 0.40) and overall survival (C-index, 0.68-0.71 vs. 0.64-0.74; p >= 0.27) in the test cohort. Conclusions A model integrating clinical, CT, and radiomics information may be useful for the preoperative assessment of postsurgical outcomes in patients with mass-forming IHCC.
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