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PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival

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Intrahepatic cholangiocarcinoma (IHC) is an aggressive disease with few reliable preoperative biomarkers. This study aims to elucidate if radiomics extracted from preoperative [18F]FDG PET/CT may grant a non-invasive biological characterization of IHC and predict outcome after complete resection of the tumor.


All patients preoperatively imaged by [18F]FDG PET/CT who underwent hepatectomy for mass-forming IHC in the period 2010–2019 were retrospectively evaluated. On PET images, manual slice-by-slice segmentation of IHC was performed (Tumor-VOI). A 5-mm margin region was semi-automatically generated around the tumor (Margin-VOI). Textural analysis was performed using the LifeX software. Analyzed outcomes included tumor grading (G3 vs. G1-2), microvascular invasion (MVI), overall survival (OS), and progression-free survival (PFS). The performances of the combined clinical-radiomic models were compared with those of standard clinical models.


Overall, 74 patients (40 females, median age 68 years) were included. Considering tumor grading and MVI, the models combining the clinical data and radiomics of the Tumor-VOI had better performances than the clinical ones (AUC = 0.78 vs. 0.72 for grading; 0.87 vs. 0.78 for MVI). The inclusion into the models of radiomics of the Margin-VOI further improved the prediction of grading (AUC = 0.83), but not of MVI. Considering OS and PFS, the models including the preoperative clinical data and radiomics of the Tumor-VOI and Margin-VOI had better performances than the pure clinical ones (C-index = 0.81 vs. 0.76 for OS; 0.81 vs. 0.72 for PFS) and similar to the models including the pathology and postoperative data (C-index = 0.81 for OS; 0.79 for PFS). No model retained the standard SUV measures.


The PET-based radiomics of IHC can predict pathology data and allow a reliable preoperative evaluation of prognosis. The radiomics of both the tumoral and peritumoral areas had clinical relevance. The combined clinical-radiomic models outperformed the pure preoperative clinical ones and achieved performances non-inferior to the postoperative models.

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Data availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.


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The present study was supported by the AIRC (Italian Association for Cancer Research) [grant #2019–23822] (PI: Luca Viganò).

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Authors and Affiliations



All authors contributed to the study conception and design. Material preparation, data collection, and analysis were performed by FF, CM, GC, MS, FI, and LV. The first draft of the manuscript was written by FF, CM, GC, MS, and LV, and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.

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Correspondence to Luca Viganò.

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Ethics approval

This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of Humanitas Clinical and Research Hospital (date 23/02/2021: protocol number 5/21).

Informed consent

Because of the retrospective nature of the analysis, the need for informed consent was waived.

Competing interests

The authors declare no competing interests. Considering the conflicts of interest in general, we state that (1) L.V. received speaker’s honoraria from Johnson & Johnson; (2) A.C. received speaker’s honoraria from Advanced Accelerator Applications, General Electric Healthcare, Sirtex Medical Europe, and AmGen Europe; received travel grants from General Electric Healthcare and Sirtex Medical Europe; is a member of Blue Earth Diagnostics’ and Advanced Accelerator Applications’ advisory boards; and received scientific support, in terms of a 3-year Ph.D. fellowship, from the Sanofi Genzyme; (3) F.F. has been a consultant for the MSD Sharp & Dohme GmbH (LLC).

The funders had no role in the design of the study; in the collection, analyses, or interpretation of the data; in the writing of the manuscript; or in the decision to publish the results.

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Fiz, F., Masci, C., Costa, G. et al. PET/CT-based radiomics of mass-forming intrahepatic cholangiocarcinoma improves prediction of pathology data and survival. Eur J Nucl Med Mol Imaging 49, 3387–3400 (2022).

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