An Imaging Signature to Predict Outcome in Metastatic Colorectal Cancer Using Routine Computed Tomography Scans.

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 f panitumumab (n = 331, 350) and FOLFIRI f aflibercept (n = 437, 466). In the training set (n = 720), an algorithm was trained to predict OS land -marked 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.(C) 2021 Elsevier Ltd. All rights reserved.