Multiparametric MRI‐Based Radiomic Signature for Preoperative Evaluation of Overall Survival in Intrahepatic Cholangiocarcinoma After Partial Hepatectomy

• Published in: Journal of magnetic resonance imaging Vol. 56; no. 3; pp. 739 - 751
• Main Authors: Yang, Yang, Zou, Xianlun, Zhou, Wei, Yuan, Guanjie, Hu, Daoyu, Kuang, Dong, Shen, Yaqi, Xie, Qingguo, Zhang, Qingpeng, Hu, Xuemei, Li, Zhen
• Format: Journal Article
• Language: English
• Published: Hoboken, USA John Wiley & Sons, Inc 01.09.2022; Wiley Subscription Services, Inc
• Subjects: Accuracy; Auditory discrimination; Biomarkers; Cholangiocarcinoma; Contrast agents; Diffusion rate; Evaluation; Hepatectomy; intrahepatic cholangiocarcinoma; liver; Magnetic resonance imaging; Mathematical models; Medical imaging; Metastases; overall survival; Patients; prognostic stratification; Radiomics; Reclassification; Regression analysis; Regression models; Statistical analysis; Statistical tests; Surgery; Survival; Tumors; overall survival; radiomics; magnetic resonance imaging; prognostic stratification; liver; intrahepatic cholangiocarcinoma
• ISSN: 1053-1807; 1522-2586; 1522-2586
• DOI: 10.1002/jmri.28071

Background The clinical outcomes of patients with intrahepatic cholangiocarcinoma (ICC) after partial hepatectomy remain suboptimal. Identifying patients with poor outcomes before surgery is urgently required. Purpose To develop a multiparametric magnetic resonance imaging (MRI)‐based radiomic signature to evaluate overall survival (OS) preoperatively and to investigate its incremental value for disease stratification. Study Type Retrospective. Subjects One hundred and sixty‐three patients with pathologically defined ICC, divided into training (N = 115) and validation sets (N = 48). Sequence Three‐dimensional T1‐weighted gradient‐echo sequence with and without contrast agent, T2‐weighted fast spin‐echo sequence, and diffusion‐weighted imaging with single‐shot echo‐planar sequence at 1.5 T or 3.0 T. Assessment OS was defined as the time from the date of surgery to death or last contact. The radiomic signature was built based on the least absolute shrinkage and selection operator regression model. A clinicopathologic‐radiographic (CPR) model and a combined model integrating radiomic signature with CPR factors were developed with multivariable Cox regression models. Statistical Tests Harrell's concordance index (C‐index) was used to compare the discrimination of different models. Net reclassification index (NRI) and integrated discrimination improvement (IDI) were used to quantify the improvement of prognostic accuracy after adding radiomic signature. Results The high‐risk patients of death defined by the radiomic signature showed significantly lower OS compared with low‐risk patients in validation set (3‐year OS 17.1% vs. 56.4%, P < 0.001). Integrating radiomic signature into tumor, node, and metastasis (TNM) staging system significantly improved the prognostic accuracy compared with TNM stage alone (validation set C‐index 0.745 vs. 0.649, P = 0.039, NRI improvement 39.9%–43.8%, IDI improvement 16.1%–19.4%). The radiomic signature showed no significant difference of C‐index with postoperative CPR model (validation set, 0.698 vs. 0.674, P = 0.752). Incorporating the radiomic signature into CPR model significantly improved prognostic accuracy (NRI improvement 32.5%–34.3%, IDI improvement 8.1%–12.9%). Data Conclusion Multiparametric MRI‐based radiomic signature is a potential biomarker for preoperative prognostic evaluation of ICC patients. Level of Evidence 4 Technical Efficacy Stage 4