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Delta-radiomics in cancer immunotherapy response prediction: A systematic review

BACKGROUND: The new immunotherapies have not only changed the oncological therapeutic approach but have also made it necessary to develop new imaging methods for assessing the response to treatment. Delta radiomics consists of the analysis of radiomic features variation between different medical ima...

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Autores principales: Abbas, Engy, Fanni, Salvatore Claudio, Bandini, Claudio, Francischello, Roberto, Febi, Maria, Aghakhanyan, Gayane, Ambrosini, Ilaria, Faggioni, Lorenzo, Cioni, Dania, Lencioni, Riccardo Antonio, Neri, Emanuele
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371799/
https://www.ncbi.nlm.nih.gov/pubmed/37520768
http://dx.doi.org/10.1016/j.ejro.2023.100511
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author Abbas, Engy
Fanni, Salvatore Claudio
Bandini, Claudio
Francischello, Roberto
Febi, Maria
Aghakhanyan, Gayane
Ambrosini, Ilaria
Faggioni, Lorenzo
Cioni, Dania
Lencioni, Riccardo Antonio
Neri, Emanuele
author_facet Abbas, Engy
Fanni, Salvatore Claudio
Bandini, Claudio
Francischello, Roberto
Febi, Maria
Aghakhanyan, Gayane
Ambrosini, Ilaria
Faggioni, Lorenzo
Cioni, Dania
Lencioni, Riccardo Antonio
Neri, Emanuele
author_sort Abbas, Engy
collection PubMed
description BACKGROUND: The new immunotherapies have not only changed the oncological therapeutic approach but have also made it necessary to develop new imaging methods for assessing the response to treatment. Delta radiomics consists of the analysis of radiomic features variation between different medical images, usually before and after therapy. PURPOSE: This review aims to evaluate the role of delta radiomics in the immunotherapy response assessment. METHODS: A systematic search was performed in PubMed, Scopus, and Web Of Science using “delta radiomics AND immunotherapy” as search terms. The included articles' methodological quality was measured using the Radiomics Quality Score (RQS) tool. RESULTS: Thirteen articles were finally included in the systematic review. Overall, the RQS of the included studies ranged from 4 to 17, with a mean RQS total of 11,15 ± 4,18 with a corresponding percentage of 30.98 ± 11.61 %. Eleven articles out of 13 performed imaging at multiple time points. All the included articles performed feature reduction. No study carried out prospective validation, decision curve analysis, or cost-effectiveness analysis. CONCLUSIONS: Delta radiomics has been demonstrated useful in evaluating the response in oncologic patients undergoing immunotherapy. The overall quality was found law, due to the lack of prospective design and external validation. Thus, further efforts are needed to bring delta radiomics a step closer to clinical implementation.
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spelling pubmed-103717992023-07-28 Delta-radiomics in cancer immunotherapy response prediction: A systematic review Abbas, Engy Fanni, Salvatore Claudio Bandini, Claudio Francischello, Roberto Febi, Maria Aghakhanyan, Gayane Ambrosini, Ilaria Faggioni, Lorenzo Cioni, Dania Lencioni, Riccardo Antonio Neri, Emanuele Eur J Radiol Open Article BACKGROUND: The new immunotherapies have not only changed the oncological therapeutic approach but have also made it necessary to develop new imaging methods for assessing the response to treatment. Delta radiomics consists of the analysis of radiomic features variation between different medical images, usually before and after therapy. PURPOSE: This review aims to evaluate the role of delta radiomics in the immunotherapy response assessment. METHODS: A systematic search was performed in PubMed, Scopus, and Web Of Science using “delta radiomics AND immunotherapy” as search terms. The included articles' methodological quality was measured using the Radiomics Quality Score (RQS) tool. RESULTS: Thirteen articles were finally included in the systematic review. Overall, the RQS of the included studies ranged from 4 to 17, with a mean RQS total of 11,15 ± 4,18 with a corresponding percentage of 30.98 ± 11.61 %. Eleven articles out of 13 performed imaging at multiple time points. All the included articles performed feature reduction. No study carried out prospective validation, decision curve analysis, or cost-effectiveness analysis. CONCLUSIONS: Delta radiomics has been demonstrated useful in evaluating the response in oncologic patients undergoing immunotherapy. The overall quality was found law, due to the lack of prospective design and external validation. Thus, further efforts are needed to bring delta radiomics a step closer to clinical implementation. Elsevier 2023-07-18 /pmc/articles/PMC10371799/ /pubmed/37520768 http://dx.doi.org/10.1016/j.ejro.2023.100511 Text en © 2023 The Authors. Published by Elsevier Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Abbas, Engy
Fanni, Salvatore Claudio
Bandini, Claudio
Francischello, Roberto
Febi, Maria
Aghakhanyan, Gayane
Ambrosini, Ilaria
Faggioni, Lorenzo
Cioni, Dania
Lencioni, Riccardo Antonio
Neri, Emanuele
Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title_full Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title_fullStr Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title_full_unstemmed Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title_short Delta-radiomics in cancer immunotherapy response prediction: A systematic review
title_sort delta-radiomics in cancer immunotherapy response prediction: a systematic review
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10371799/
https://www.ncbi.nlm.nih.gov/pubmed/37520768
http://dx.doi.org/10.1016/j.ejro.2023.100511
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