Radiomics of Intrahepatic Cholangiocarcinoma and Peritumoral Tissue Predicts Postoperative Survival: Development of a CT-Based Clinical-Radiomic Model

期刊论文
发表日期：

2024年5月26日

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Francesco Fiz,
Noemi Rossi,
Serena Langella,
Simone Conci,
Matteo Serenari,
Francesco Ardito,
Alessandro Cucchetti,
Teresa Gallo,
Giulia A. Zamboni,
Cristina Mosconi,
Luca Boldrini,
Mariateresa Mirarchi,
Stefano Cirillo,
Andrea Ruzzenente,
Ilaria Pecorella,
Nadia Russolillo,
Martina Borzi,
Giulio Vara,
Caterina Mele,
Giorgio Ercolani,
Felice Giuliante,
Matteo Cescon,
Alfredo Guglielmi,
Alessandro Ferrero,
Martina Sollini,
Arturo Chiti,
Guido Torzilli,
Francesca Ieva,
Luca Viganò

摘要

Background

For many tumors, radiomics provided a relevant prognostic contribution. This study tested whether the computed tomography (CT)-based textural features of intrahepatic cholangiocarcinoma (ICC) and peritumoral tissue improve the prediction of survival after resection compared with the standard clinical indices.

Methods

All consecutive patients affected by ICC who underwent hepatectomy at six high-volume centers (2009–2019) were considered for the study. The arterial and portal phases of CT performed fewer than 60 days before surgery were analyzed. A manual segmentation of the tumor was performed (Tumor-VOI). A 5-mm volume expansion then was applied to identify the peritumoral tissue (Margin-VOI).

Results

The study enrolled 215 patients. After a median follow-up period of 28 months, the overall survival (OS) rate was 57.0%, and the progression-free survival (PFS) rate was 34.9% at 3 years. The clinical predictive model of OS had a C-index of 0.681. The addition of radiomic features led to a progressive improvement of performances (C-index of 0.71, including the portal Tumor-VOI, C-index of 0.752 including the portal Tumor- and Margin-VOI, C-index of 0.764, including all VOIs of the portal and arterial phases). The latter model combined clinical variables (CA19-9 and tumor pattern), tumor indices (density, homogeneity), margin data (kurtosis, compacity, shape), and GLRLM indices. The model had performance equivalent to that of the postoperative clinical model including the pathology data (C-index of 0.765). The same results were observed for PFS.

Conclusions

The radiomics of ICC and peritumoral tissue extracted from preoperative CT improves the prediction of survival. Both the portal and arterial phases should be considered. Radiomic and clinical data are complementary and achieve a preoperative estimation of prognosis equivalent to that achieved in the postoperative setting.