Intra- and Peri-tumoral Radiomics Based on Dynamic Contrast Enhanced-MRI to Identify Lymph Node Metastasis and Prognosis in Intrahepatic Cholangiocarcinoma.

Autor: Pan YJ; Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.; Shanghai Institute of Medical Imaging, Shanghai, China., Wu SJ; Department of Radiology, The First Affiliated Hospital of Wenzhou Medical University, Wenzhou, Zhejiang, China., Zeng Y; Department of Research Center, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China., Cao ZR; Department of Research Center, Shanghai United Imaging Intelligence Co., Ltd., Shanghai, China., Shan Y; Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.; Shanghai Institute of Medical Imaging, Shanghai, China., Lin J; Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.; Shanghai Institute of Medical Imaging, Shanghai, China., Xu PJ; Department of Radiology, Zhongshan Hospital, Fudan University, Shanghai, China.; Shanghai Institute of Medical Imaging, Shanghai, China.
Jazyk: angličtina
Zdroj: Journal of magnetic resonance imaging : JMRI [J Magn Reson Imaging] 2024 Dec; Vol. 60 (6), pp. 2669-2680. Date of Electronic Publication: 2024 Apr 12.
DOI: 10.1002/jmri.29390
Abstrakt: Background: Lymph node metastasis (LNM) in patients with intrahepatic cholangiocarcinoma (iCCA) affects treatment strategies and prognosis. However, preoperative imaging is not reliable enough for identifying LNM.
Purpose: To develop and validate a radiomics nomogram based on dynamic contrast enhanced (DCE)-MR images for identifying LNM and prognosis in iCCA.
Study Type: Retrospective.
Subjects: Two hundred four patients with pathologically proven iCCA who underwent curative-intent resection and lymphadenectomy (training cohort: N = 107, internal test cohort: N = 46, and external test cohort: N = 51).
Field Strength/sequence: T1- and T2-weighted imaging, diffusion-weighted imaging and DCE imaging at 1.5 T or 3.0 T.
Assessment: Radiomics features were extracted from intra- and peri-tumoral regions on preoperative DCE-MR images. Imaging features were evaluated by three radiologists, and significant variables in univariable and multivariable regression analysis were included in clinical model. The best-performing radiomics signature and clinical characteristics (intrahepatic duct dilatation, MRI-reported LNM) were combined to build a nomogram. Patients were divided into high-risk and low-risk groups based on their nomogram scores (cutoff = 0.341). Patients were followed up for 1-102 months (median 12) after surgery, the overall survival (OS) and recurrence-free survival (RFS) were calculated.
Statistical Tests: Receiver operating characteristic (ROC) curve, calibration, decision curve, Delong test, Kaplan-Meier curves, log rank test. Two tailed P < 0.05 was considered statistically significant.
Results: The nomogram incorporating intra- and peri-tumoral radiomics features, intrahepatic duct dilatation and MRI-reported LNM obtained the best discrimination for LNM, with areas under the ROC curves of 0.946, 0.913, and 0.859 in the training, internal, and external test cohorts. In the entire cohort, high-risk patients had significantly lower RFS and OS than low-risk patients. High-risk of LNM was an independent factor of unfavorable OS and RFS.
Data Conclusion: The nomogram integrating intra- and peri-tumoral radiomics signatures has potential to identify LNM and prognosis in iCCA.
Evidence Level: 3 TECHNICAL EFFICACY: Stage 2.
(© 2024 International Society for Magnetic Resonance in Medicine.)
Databáze: MEDLINE
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