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18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis

The best treatment strategy for oesophageal cancer patients achieving a complete clinical response after neoadjuvant chemoradiation is a burning topic. The available diagnostic tools, such as 18F-FDG PET/CT performed routinely, cannot accurately evaluate the presence or absence of the residual tumou...

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Autores principales: Deantonio, Letizia, Garo, Maria Luisa, Paone, Gaetano, Valli, Maria Carla, Cappio, Stefano, La Regina, Davide, Cefali, Marco, Palmarocchi, Maria Celeste, Vannelli, Alberto, De Dosso, Sara
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965232/
https://www.ncbi.nlm.nih.gov/pubmed/35371989
http://dx.doi.org/10.3389/fonc.2022.861638
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author Deantonio, Letizia
Garo, Maria Luisa
Paone, Gaetano
Valli, Maria Carla
Cappio, Stefano
La Regina, Davide
Cefali, Marco
Palmarocchi, Maria Celeste
Vannelli, Alberto
De Dosso, Sara
author_facet Deantonio, Letizia
Garo, Maria Luisa
Paone, Gaetano
Valli, Maria Carla
Cappio, Stefano
La Regina, Davide
Cefali, Marco
Palmarocchi, Maria Celeste
Vannelli, Alberto
De Dosso, Sara
author_sort Deantonio, Letizia
collection PubMed
description The best treatment strategy for oesophageal cancer patients achieving a complete clinical response after neoadjuvant chemoradiation is a burning topic. The available diagnostic tools, such as 18F-FDG PET/CT performed routinely, cannot accurately evaluate the presence or absence of the residual tumour. The emerging field of radiomics may encounter the critical challenge of personalised treatment. Radiomics is based on medical image analysis, executed by extracting information from many image features; it has been shown to provide valuable information for predicting treatment responses in oesophageal cancer. This systematic review with a meta-analysis aims to provide current evidence of 18F-FDG PET-based radiomics in predicting response treatments following neoadjuvant chemoradiotherapy in oesophageal cancer. A comprehensive literature review identified 1160 studies, of which five were finally included in the study. Our findings provided that pooled Area Under the Curve (AUC) of the five selected studies was relatively high at 0.821 (95% CI: 0.737–0.904) and not influenced by the sample size of the studies. Radiomics models exhibited a good performance in predicting pathological complete responses (pCRs). This review further strengthens the great potential of 18F-FDG PET-based radiomics to predict pCRs in oesophageal cancer patients who underwent neoadjuvant chemoradiotherapy. Additionally, our review imparts additional support to prospective studies on 18F-FDG PET radiomics for a tailored treatment strategy of oesophageal cancer patients. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier CRD42021274636.
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spelling pubmed-89652322022-03-31 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis Deantonio, Letizia Garo, Maria Luisa Paone, Gaetano Valli, Maria Carla Cappio, Stefano La Regina, Davide Cefali, Marco Palmarocchi, Maria Celeste Vannelli, Alberto De Dosso, Sara Front Oncol Oncology The best treatment strategy for oesophageal cancer patients achieving a complete clinical response after neoadjuvant chemoradiation is a burning topic. The available diagnostic tools, such as 18F-FDG PET/CT performed routinely, cannot accurately evaluate the presence or absence of the residual tumour. The emerging field of radiomics may encounter the critical challenge of personalised treatment. Radiomics is based on medical image analysis, executed by extracting information from many image features; it has been shown to provide valuable information for predicting treatment responses in oesophageal cancer. This systematic review with a meta-analysis aims to provide current evidence of 18F-FDG PET-based radiomics in predicting response treatments following neoadjuvant chemoradiotherapy in oesophageal cancer. A comprehensive literature review identified 1160 studies, of which five were finally included in the study. Our findings provided that pooled Area Under the Curve (AUC) of the five selected studies was relatively high at 0.821 (95% CI: 0.737–0.904) and not influenced by the sample size of the studies. Radiomics models exhibited a good performance in predicting pathological complete responses (pCRs). This review further strengthens the great potential of 18F-FDG PET-based radiomics to predict pCRs in oesophageal cancer patients who underwent neoadjuvant chemoradiotherapy. Additionally, our review imparts additional support to prospective studies on 18F-FDG PET radiomics for a tailored treatment strategy of oesophageal cancer patients. SYSTEMATIC REVIEW REGISTRATION: https://www.crd.york.ac.uk/prospero/, identifier CRD42021274636. Frontiers Media S.A. 2022-03-15 /pmc/articles/PMC8965232/ /pubmed/35371989 http://dx.doi.org/10.3389/fonc.2022.861638 Text en Copyright © 2022 Deantonio, Garo, Paone, Valli, Cappio, La Regina, Cefali, Palmarocchi, Vannelli and De Dosso https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Oncology
Deantonio, Letizia
Garo, Maria Luisa
Paone, Gaetano
Valli, Maria Carla
Cappio, Stefano
La Regina, Davide
Cefali, Marco
Palmarocchi, Maria Celeste
Vannelli, Alberto
De Dosso, Sara
18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title_full 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title_fullStr 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title_full_unstemmed 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title_short 18F-FDG PET Radiomics as Predictor of Treatment Response in Oesophageal Cancer: A Systematic Review and Meta-Analysis
title_sort 18f-fdg pet radiomics as predictor of treatment response in oesophageal cancer: a systematic review and meta-analysis
topic Oncology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8965232/
https://www.ncbi.nlm.nih.gov/pubmed/35371989
http://dx.doi.org/10.3389/fonc.2022.861638
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