Eur Rev Med Pharmacol Sci 2022; 26 (8): 2891-2899
DOI: 10.26355/eurrev_202204_28620

Project for interventional Oncology LArge-database in liveR Hepatocellular carcinoma – Preliminary CT-based radiomic analysis (POLAR Liver 1.1)

R. Iezzi, C. Casà, A. Posa, P. Cornacchione, F. Carchesio, L. Boldrini, A. Tanzilli, L. Cerrito, B. Fionda, V. Longo, L. Miele, V. Lancellotta, F. Cellini, H.E. Tran, F.R. Ponziani, F. Giuliante, G.L. Rapaccini, A. Grieco, M. Pompili, A. Gasbarrini, V. Valentini, M.A. Gambacorta, L. Tagliaferri, R. Manfredi, on behalf of HepatoCatt Study Group

Dipartimento di Diagnostica per Immagini, Radioterapia Oncologica ed Ematologia – U.O.C. Radiologia Diagnostica e Interventistica Generale, Fondazione Policlinico Universitario A. Gemelli IRCCS, Rome, Italy. roberto.iezzi.md@gmail.com


OBJECTIVE: The objective of this study is to find a contrast-enhanced CT-radiomic signature to predict clinical incomplete response in patients affected by hepatocellular carcinoma who underwent locoregional treatments.

PATIENTS AND METHODS: 190 patients affected by hepatocellular carcinoma treated using focal therapies (radiofrequency or microwave ablation) from September 2018 to October 2020 were retrospectively enrolled. Treatment response was evaluated on a per-target-nodule basis on the 6-months follow-up contrast-enhanced CT or MR imaging using the mRECIST criteria. Radiomics analysis was performed using an in-house developed open-source R library. Wilcoxon-Mann-Whitney test was applied for univariate analysis; features with a p-value lower than 0.05 were selected. Pearson correlation was applied to discard highly correlated features (cut-off=0.9). The remaining features were included in a logistic regression model and receiver operating characteristic curves; sensitivity, specificity, positive and negative predictive value were also computed. The model was validated performing 2000 bootstrap resampling.

RESULTS: 56 treated lesions from 42 patients were selected. Treatment responses were: complete response for 26 lesions (46.4%), 18 partial responses (32.1%), 10 stable diseases (17.9%), 2 progression diseases (3.6%). Area-Under-Curve value was 0.667 (95% CI: 0.527-0.806); accuracy, sensitivity, specificity, positive and negative predictive values were respectively 0.66, 0.85, 0.50, 0.59 and 0.79.

CONCLUSIONS: This contrast-enhanced CT-based model can be helpful to early identify poor responder’s hepatocellular carcinoma patients and personalize treatments.

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R. Iezzi, C. Casà, A. Posa, P. Cornacchione, F. Carchesio, L. Boldrini, A. Tanzilli, L. Cerrito, B. Fionda, V. Longo, L. Miele, V. Lancellotta, F. Cellini, H.E. Tran, F.R. Ponziani, F. Giuliante, G.L. Rapaccini, A. Grieco, M. Pompili, A. Gasbarrini, V. Valentini, M.A. Gambacorta, L. Tagliaferri, R. Manfredi, on behalf of HepatoCatt Study Group
Project for interventional Oncology LArge-database in liveR Hepatocellular carcinoma – Preliminary CT-based radiomic analysis (POLAR Liver 1.1)

Eur Rev Med Pharmacol Sci
Year: 2022
Vol. 26 - N. 8
Pages: 2891-2899
DOI: 10.26355/eurrev_202204_28620