An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans Journal Article
| Authors: | Dercle, L.; Zhao, B.; Gönen, M.; Moskowitz, C. S.; Connors, D. E.; Yang, H.; Lu, L.; Reidy-Lagunes, D.; Fojo, T.; Karovic, S.; Maitland, M. L.; Oxnard, G. R.; Schwartz, L. H. |
| Article Title: | An imaging signature to predict outcome in metastatic colorectal cancer using routine computed tomography scans |
| Abstract: | Background & aims: Quantitative analysis of computed tomography (CT) scans of patients with metastatic colorectal cancer (mCRC) can identify imaging signatures that predict overall survival (OS). Methods: We retrospectively analysed CT images from 1584 mCRC patients on two phase III trials evaluating FOLFOX ± panitumumab (n = 331, 350) and FOLFIRI ± aflibercept (n = 437, 466). In the training set (n = 720), an algorithm was trained to predict OS landmarked from month 2; the output was a signature value on a scale from 0 to 1 (most to least favourable predicted OS). In the validation set (n = 864), hazard ratios (HRs) evaluated the association of the signature with OS using RECIST1.1 as a benchmark of comparison. Results: In the training set, the selected signature combined three features – change in tumour volume, change in tumour spatial heterogeneity, and tumour volume – to predict OS. In the validation set, RECIST1.1 classified patients in three categories: response (n = 166, 19.2%), stable disease (n = 636, 73.6%), and progression (n = 62, 7.2%). The HR was 3.93 (2.79–5.54). Using the same distribution for the signature, the HR was 21.04 (14.88–30.58), showing an incremental prognostic separation. Stable disease by RECIST1.1 was reclassified by the signature along a continuum where patients belonging to the most and least favourable signature quartiles had a median OS of 40.73 (28.49 to NA) months (n = 94) and 7.03 (5.66–7.89) months (n = 166), respectively. Conclusions: A signature combining three imaging features provides early prognostic information that can improve treatment decisions for individual patients and clinical trial analyses. © 2021 Elsevier Ltd |
| Keywords: | colorectal cancer; ct scan; radiomics |
| Journal Title: | European Journal of Cancer |
| Volume: | 161 |
| ISSN: | 0959-8049 |
| Publisher: | Elsevier Inc. |
| Date Published: | 2022-01-01 |
| Start Page: | 138 |
| End Page: | 147 |
| Language: | English |
| DOI: | 10.1016/j.ejca.2021.10.029 |
| PUBMED: | 34916122 |
| PROVIDER: | scopus |
| PMCID: | PMC10018811 |
| DOI/URL: | |
| Notes: | Article -- Export Date: 1 February 2022 -- Source: Scopus |
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