Caruso M, Stanzione A, Prinster A, Pizzuti LM, Brunetti A, Maurea S, Mainenti PP. Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases. World J Gastroenterol 2023; 29(3): 521-535 [PMID: 36688023 DOI: 10.3748/wjg.v29.i3.521]
Corresponding Author of This Article
Arnaldo Stanzione, MD, PhD, Postdoc, Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini 5, Napoli 80131, Italy. arnaldo.stanzione@unina.it
Research Domain of This Article
Radiology, Nuclear Medicine & Medical Imaging
Article-Type of This Article
Minireviews
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (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: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastroenterol. Jan 21, 2023; 29(3): 521-535 Published online Jan 21, 2023. doi: 10.3748/wjg.v29.i3.521
Role of advanced imaging techniques in the evaluation of oncological therapies in patients with colorectal liver metastases
Martina Caruso, Arnaldo Stanzione, Anna Prinster, Laura Micol Pizzuti, Arturo Brunetti, Simone Maurea, Pier Paolo Mainenti
Martina Caruso, Arnaldo Stanzione, Arturo Brunetti, Simone Maurea, Department of Advanced Biomedical Sciences, University of Naples "Federico II", Napoli 80131, Italy
Anna Prinster, Laura Micol Pizzuti, Pier Paolo Mainenti, Institute of Biostructures and Bioimaging, National Research Council, Napoli 80131, Italy
Author contributions: All authors contributed to the literature search, evidence review, manuscript drafting and revision; All authors have read and approve the final manuscript.
Conflict-of-interest statement: All the authors report no relevant conflicts of interest for this article.
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: Arnaldo Stanzione, MD, PhD, Postdoc, Department of Advanced Biomedical Sciences, University of Naples "Federico II", Via S. Pansini 5, Napoli 80131, Italy. arnaldo.stanzione@unina.it
Received: October 6, 2022 Peer-review started: October 6, 2022 First decision: October 21, 2022 Revised: November 25, 2022 Accepted: January 3, 2023 Article in press: January 3, 2023 Published online: January 21, 2023 Processing time: 97 Days and 19.2 Hours
Abstract
In patients with colorectal liver metastasis (CRLMs) unsuitable for surgery, oncological treatments, such as chemotherapy and targeted agents, can be performed. Cross-sectional imaging [computed tomography (CT), magnetic resonance imaging (MRI), 18-fluorodexoyglucose positron emission tomography with CT/MRI] evaluates the response of CRLMs to therapy, using post-treatment lesion shrinkage as a qualitative imaging parameter. This point is critical because the risk of toxicity induced by oncological treatments is not always balanced by an effective response to them. Consequently, there is a pressing need to define biomarkers that can predict treatment responses and estimate the likelihood of drug resistance in individual patients. Advanced quantitative imaging (diffusion-weighted imaging, perfusion imaging, molecular imaging) allows the in vivo evaluation of specific biological tissue features described as quantitative parameters. Furthermore, radiomics can represent large amounts of numerical and statistical information buried inside cross-sectional images as quantitative parameters. As a result, parametric analysis (PA) translates the numerical data contained in the voxels of each image into quantitative parameters representative of peculiar neoplastic features such as perfusion, structural heterogeneity, cellularity, oxygenation, and glucose consumption. PA could be a potentially useful imaging marker for predicting CRLMs treatment response. This review describes the role of PA applied to cross-sectional imaging in predicting the response to oncological therapies in patients with CRLMs.
Core Tip: Chemotherapy and targeted agents can be administered to patients with colorectal liver metastasis (CRLM) unsuitable for surgery. The risk of toxicity requires identification of imaging biomarkers that can estimate the likelihood of response and drug resistance before starting therapy. Clinical validation may aid clinicians in tailoring their individual treatment regimens. In this setting, parametric analysis applied to cross-sectional imaging plays a crucial role in evaluating in vivo peculiar neoplastic features, such as perfusion, structural heterogeneity, cellularity, oxygenation, and glucose consumption. However, there is no consensus on the most promising imaging quantitative parameter to predict therapy response in CRLMs patients.
