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Imaging response assessment for oncology: An algorithmic approach
Treatment response assessment by imaging plays a vital role in evaluating changes in solid tumors during oncology therapeutic clinical trials. Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 is the reference standard imaging response criteria and provides details regarding image acquisitio...
Autores principales: | , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184854/ https://www.ncbi.nlm.nih.gov/pubmed/35693043 http://dx.doi.org/10.1016/j.ejro.2022.100426 |
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author | Ruchalski, Kathleen Dewan, Rohit Sai, Victor McIntosh, Lacey J. Braschi-Amirfarzan, Marta |
author_facet | Ruchalski, Kathleen Dewan, Rohit Sai, Victor McIntosh, Lacey J. Braschi-Amirfarzan, Marta |
author_sort | Ruchalski, Kathleen |
collection | PubMed |
description | Treatment response assessment by imaging plays a vital role in evaluating changes in solid tumors during oncology therapeutic clinical trials. Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 is the reference standard imaging response criteria and provides details regarding image acquisition, image interpretation and categorical response classification. While RECIST 1.1 is applied for the majority of clinical trials in solid tumors, other criteria and modifications have been introduced when RECIST 1.1 outcomes may be incomplete. Available criteria beyond RECIST 1.1 can be explored in an algorithmic fashion dependent on imaging modality, tumor type and method of treatment. Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) is available for use with PET/CT. Modifications to RECIST 1.1 can be tumor specific, including mRECIST for hepatocellular carcinoma and mesothelioma. Choi criteria for gastrointestinal stromal tumors incorporate tumor density with alterations to categorical response thresholds. Prostate Cancer Working Group 3 (PCWG3) imaging criteria combine RECIST 1.1 findings with those of bone scans. In addition, multiple response criteria have been created to address atypical imaging responses in immunotherapy. |
format | Online Article Text |
id | pubmed-9184854 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-91848542022-06-11 Imaging response assessment for oncology: An algorithmic approach Ruchalski, Kathleen Dewan, Rohit Sai, Victor McIntosh, Lacey J. Braschi-Amirfarzan, Marta Eur J Radiol Open Article Treatment response assessment by imaging plays a vital role in evaluating changes in solid tumors during oncology therapeutic clinical trials. Response Evaluation Criteria in Solid Tumors (RECIST) 1.1 is the reference standard imaging response criteria and provides details regarding image acquisition, image interpretation and categorical response classification. While RECIST 1.1 is applied for the majority of clinical trials in solid tumors, other criteria and modifications have been introduced when RECIST 1.1 outcomes may be incomplete. Available criteria beyond RECIST 1.1 can be explored in an algorithmic fashion dependent on imaging modality, tumor type and method of treatment. Positron Emission Tomography Response Criteria in Solid Tumors (PERCIST) is available for use with PET/CT. Modifications to RECIST 1.1 can be tumor specific, including mRECIST for hepatocellular carcinoma and mesothelioma. Choi criteria for gastrointestinal stromal tumors incorporate tumor density with alterations to categorical response thresholds. Prostate Cancer Working Group 3 (PCWG3) imaging criteria combine RECIST 1.1 findings with those of bone scans. In addition, multiple response criteria have been created to address atypical imaging responses in immunotherapy. Elsevier 2022-06-07 /pmc/articles/PMC9184854/ /pubmed/35693043 http://dx.doi.org/10.1016/j.ejro.2022.100426 Text en © 2022 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 Ruchalski, Kathleen Dewan, Rohit Sai, Victor McIntosh, Lacey J. Braschi-Amirfarzan, Marta Imaging response assessment for oncology: An algorithmic approach |
title | Imaging response assessment for oncology: An algorithmic approach |
title_full | Imaging response assessment for oncology: An algorithmic approach |
title_fullStr | Imaging response assessment for oncology: An algorithmic approach |
title_full_unstemmed | Imaging response assessment for oncology: An algorithmic approach |
title_short | Imaging response assessment for oncology: An algorithmic approach |
title_sort | imaging response assessment for oncology: an algorithmic approach |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9184854/ https://www.ncbi.nlm.nih.gov/pubmed/35693043 http://dx.doi.org/10.1016/j.ejro.2022.100426 |
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