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  3. Hepatocellular Carcinoma Drug-Eluting Bead Transarterial Chemoembolization (DEB-TACE): Outcome Analysis Using a Model Based On Pre-Treatment CT Texture Features
 

Hepatocellular Carcinoma Drug-Eluting Bead Transarterial Chemoembolization (DEB-TACE): Outcome Analysis Using a Model Based On Pre-Treatment CT Texture Features

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BORIS DOI
10.48350/156546
Publisher DOI
10.3390/diagnostics11060956
PubMed ID
34073545
Description
(1) Introduction and Aim: The aim of this study is to investigate the prognostic value, in terms of response and survival, of CT-based radiomics features for patients with HCC undergoing drug-eluting beads transarterial chemoembolization (DEB-TACE). (2) Materials and Methods: Pre-treatment CT examinations of 50 patients with HCC, treated with DEB-TACE were manually segmented to obtain the tumor volumetric region of interest, extracting radiomics features with TexRAD. Response to therapy evaluation was performed basing on post-procedural CT examination compared to pre-procedural CT, using modified RECIST criteria for HCC. The prognostic value of texture analysis was evaluated, investigating the correlation between radiomics features, response to therapy and overall survival. Three models based on texture and clinical variables and a combination of them were finally built; (3) Results: Entropy, skewness, MPP and kurtosis showed a significant correlation with complete response (CR) to TACE (all p < 0.001). A predictive model to identify patients with a high and low probability of CR was evaluated with an ROC curve, with an AUC of 0.733 (p < 0.001). The three models built for survival prediction yielded an HR of 2.19 (95% CI: 2.03-2.35) using texture features, of 1.7 (95% CI: 1.54-1.9) using clinical data and of 4.61 (95% CI: 4.24-5.01) combining both radiomics and clinical data (all p < 0.0001). (4) Conclusion: Texture analysis based on pre-treatment CT examination is associated with response to therapy and survival in patients with HCC undergoing DEB-TACE, especially if combined with clinical data.
Date of Publication
2021
Publication Type
Article
Subject(s)
600 Technology > 610 Medicine & health
Language(s)
en
Contributor(s)
Tipaldi, Marcello Andrea
Ronconi, Edoardo
Lucertini, Elena
Krokidis, Miltiadis
Universitätsinstitut für Diagnostische, Interventionelle und Pädiatrische Radiologie
Zerunian, Marta
Polidori, Tiziano
Begini, Paola
Marignani, Massimo
Mazzuca, Federica
Caruso, Damiano
Rossi, Michele
Laghi, Andrea
Additional Credits
Universitätsinstitut für Diagnostische, Interventionelle und Pädiatrische Radiologie
Series
Diagnostics
Publisher
MDPI
ISSN
2075-4418
Access(Rights)
open.access
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