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Radiomics nomogram based on optimal VOI of multi-sequence MRI for predicting microvascular invasion in intrahepatic cholangiocarcinoma

OBJECTIVE: Microvascular invasion (MVI) is a significant adverse prognostic indicator of intrahepatic cholangiocarcinoma (ICC) and affects the selection of individualized treatment regimens. This study sought to establish a radiomics nomogram based on the optimal VOI of multi-sequence MRI for predic...

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Detalles Bibliográficos
Autores principales: Ma, Xijuan, Qian, Xianling, Wang, Qing, Zhang, Yunfei, Zong, Ruilong, Zhang, Jia, Qian, Baoxin, Yang, Chun, Lu, Xin, Shi, Yibing
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Milan 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10620280/
https://www.ncbi.nlm.nih.gov/pubmed/37679641
http://dx.doi.org/10.1007/s11547-023-01704-8
Descripción
Sumario:OBJECTIVE: Microvascular invasion (MVI) is a significant adverse prognostic indicator of intrahepatic cholangiocarcinoma (ICC) and affects the selection of individualized treatment regimens. This study sought to establish a radiomics nomogram based on the optimal VOI of multi-sequence MRI for predicting MVI in ICC tumors. METHODS: 160 single ICC lesions with MRI scanning confirmed by postoperative pathology were randomly separated into training and validation cohorts (TC and VC). Multivariate analysis identified independent clinical and imaging MVI predictors. Radiomics features were obtained from images of 6 MRI sequences at 4 different VOIs. The least absolute shrinkage and selection operator algorithm was performed to enable the derivation of robust and effective radiomics features. Then, the best three sequences and the optimal VOI were obtained through comparison. The MVI prediction nomogram combined the independent predictors and optimal radiomics features, and its performance was evaluated via the receiver operating characteristics, calibration, and decision curves. RESULTS: Tumor size and intrahepatic ductal dilatation are independent MVI predictors. Radiomics features extracted from the best three sequences (T1WI-D, T1WI, DWI) with VOI(10mm) (including tumor and 10 mm peritumoral region) showed the best predictive performance, with AUC(TC) = 0.987 and AUC(VC) = 0.859. The MVI prediction nomogram obtained excellent prediction efficacy in both TC (AUC = 0.995, 95%CI 0.987–1.000) and VC (AUC = 0.867, 95%CI 0.798–0.921) and its clinical significance was further confirmed by the decision curves. CONCLUSION: A nomogram combining tumor size, intrahepatic ductal dilatation, and the radiomics model of MRI multi-sequence fusion at VOI(10mm) may be a predictor of preoperative MVI status in ICC patients. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1007/s11547-023-01704-8.