Imaging response assessment for oncology: An algorithmic approach
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UMass Chan AffiliationsDepartment of Radiology
Document TypeJournal Article
Response Evaluation Criteria in Solid Tumors
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AbstractTreatment 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.
Ruchalski K, Dewan R, Sai V, McIntosh LJ, Braschi-Amirfarzan M. Imaging response assessment for oncology: An algorithmic approach. Eur J Radiol Open. 2022 Jun 7;9:100426. doi: 10.1016/j.ejro.2022.100426. PMID: 35693043; PMCID: PMC9184854. Link to article on publisher's site
Permanent Link to this Itemhttp://hdl.handle.net/20.500.14038/48641
Rights© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
Except where otherwise noted, this item's license is described as © 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).