Review
Copyright ©The Author(s) 2023. Published by Baishideng Publishing Group Inc. All rights reserved.
World J Gastroenterol. May 21, 2023; 29(19): 2888-2904
Published online May 21, 2023. doi: 10.3748/wjg.v29.i19.2888
Radiomics in colorectal cancer patients
Riccardo Inchingolo, Cesare Maino, Roberto Cannella, Federica Vernuccio, Francesco Cortese, Michele Dezio, Antonio Rosario Pisani, Teresa Giandola, Marco Gatti, Valentina Giannini, Davide Ippolito, Riccardo Faletti
Riccardo Inchingolo, Francesco Cortese, Michele Dezio, Unit of Interventional Radiology, F. Miulli Hospital, Acquaviva delle Fonti 70021, Italy
Cesare Maino, Teresa Giandola, Davide Ippolito, Department of Radiology, Fondazione IRCCS San Gerardo dei Tintori, Monza 20900, Italy
Roberto Cannella, Department of Biomedicine, Neuroscience and Advanced Diagnostics (BiND), University of Palermo, Palermo 90127, Italy
Federica Vernuccio, Institute of Radiology, University Hospital of Padova, Padova 35128, Italy
Antonio Rosario Pisani, Interdisciplinary Department of Medicine, Section of Nuclear Medicine, University of Bari “Aldo Moro”, Bari 70121, Italy
Marco Gatti, Valentina Giannini, Riccardo Faletti, Department of Surgical Sciences, University of Turin, Turin 10126, Italy
Author contributions: Inchingolo R, Maino C, Cannella R, Vernuccio F, Cortese F, Dezio M, Pisani AR, Giandola T, Gatti M, Giannini V, Ippolito D, and Faletti R equally contributed to this paper with conception and design of the study, literature review and analysis, drafting and critical revision and editing; and all authors gave final approval of the final version.
Conflict-of-interest statement: All the authors are aware of the content of the manuscript and have no conflict of interest.
Open-Access: This article is an open-access article that was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution NonCommercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: https://creativecommons.org/Licenses/by-nc/4.0/
Corresponding author: Riccardo Inchingolo, MD, Director, Doctor, Unit of Interventional Radiology, F. Miulli Hospital, Sp per Santeramo, Acquaviva delle Fonti 70021, Italy. riccardoin@hotmail.it
Received: February 16, 2023
Peer-review started: February 16, 2023
First decision: March 24, 2023
Revised: April 7, 2023
Accepted: April 25, 2023
Article in press: April 25, 2023
Published online: May 21, 2023
Processing time: 89 Days and 1.7 Hours
Core Tip

Core Tip: Stratifying colorectal cancer patients with high-risk disease and the evaluation of the overall chemotherapy benefit are a clinical challenge. Radiomics through radiological images analysis using automated computer-based techniques allows the extraction of quantitative features from radiological images, mainly invisible to the naked eye, that can be further analyzed by artificial intelligence algorithms. Several efforts have been made to develop radiomics signatures for colorectal cancer patient using computed tomography (CT), magnetic resonance imaging, and positron emission tomography/CT, in particular to understand tumor biology, to develop imaging biomarkers for diagnosis, staging, and prognosis, to predict treatment response and to monitor disease.