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

Authors :
Iezzi R
Casà C
Posa A
Cornacchione P
Carchesio F
Boldrini L
Tanzilli A
Cerrito L
Fionda B
Longo V
Miele L
Lancellotta V
Cellini F
Tran HE
Ponziani FR
Giuliante F
Rapaccini GL
Grieco A
Pompili M
Gasbarrini A
Valentini V
Gambacorta MA
Tagliaferri L
Manfredi R
Source :
European review for medical and pharmacological sciences [Eur Rev Med Pharmacol Sci] 2022 Apr; Vol. 26 (8), pp. 2891-2899.
Publication Year :
2022

Abstract

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.<br />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.<br />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.<br />Conclusions: This contrast-enhanced CT-based model can be helpful to early identify poor responder's hepatocellular carcinoma patients and personalize treatments.

Details

Language :
English
ISSN :
2284-0729
Volume :
26
Issue :
8
Database :
MEDLINE
Journal :
European review for medical and pharmacological sciences
Publication Type :
Academic Journal
Accession number :
35503635
Full Text :
https://doi.org/10.26355/eurrev_202204_28620