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Updated: Nov 20, 2025
Predictive Immune Modeling of Solid Tumors
Published on: February 25, 2020
A CT-based Radiomics Signature Is Associated with Response to Immune Checkpoint Inhibitors in Advanced Solid Tumors
Marta Ligero1, Alonso Garcia-Ruiz1, Cristina Viaplana1
1From the Radiomics Group, Vall d'Hebron Institute of Oncology (VHIO), Cellex Center, Natzaret 115-117, Barcelona 08035, Spain (M.L., A.G.R., R.P.L.); Oncology Data Science (ODysSey) Group, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain (C.V., G.V., R.D.); Institute of Radiology, Foundation IRCCS Polyclinic San Matteo, Pavia, Italy (M.V.R.); Department of Radiology, Bellvitge University Hospital, L'Hospitalet de Llobregat, Spain (J.L.); Department of Medical Oncology, Vall d'Hebron University Hospital and Institute of Oncology (VHIO), Barcelona, Spain (I.M., J.M.L., M.O.d.O., C.H., J.M., M.G., R.M.B., C.S., J.R., E.E., I.B., E.M.C., A.O., E.F., J.T., J.C., E.G.); Department of Molecular Oncology, Vall d'Hebron Institute of Oncology (VHIO), Barcelona, Spain (R.F., P.N.); Computer Vision Center, Department of Computer Science, Autonomous University of Barcelona, Cerdanyola del Vallès, Spain (D.G.); Vall d'Hebron Institute of Oncology (VHIO), Vall d'Hebron University Hospital (HUVH), Autonomous University of Barcelona, Institució Catalana de Recerca i Estudis Avançats (ICREA) and CIBERONC, Barcelona, Spain (C.R.P., J.S.); Department of Radiology, Vall d'Hebron University Hospital, Barcelona, Spain (M.E., R.P.L.); and Department of Medicine, Autonomous University of Barcelona (UAB), Barcelona, Spain (J.T.).
Abstract:
Background Reliable predictive imaging markers of response to immune checkpoint inhibitors are needed. Purpose To develop and validate a pretreatment CT-based radiomics signature to predict response to immune checkpoint inhibitors in advanced solid tumors. Materials and Methods In this retrospective study, a radiomics signature was developed in patients with advanced solid tumors (including breast, cervix, gastrointestinal) treated with anti-programmed cell death-1 or programmed cell death ligand-1 monotherapy from August 2012 to May 2018 (cohort 1). This was tested in patients with bladder and lung cancer (cohorts 2 and 3). Radiomics variables were extracted from all metastases delineated at pretreatment CT and selected by using an elastic-net model. A regression model combined radiomics and clinical variables with response as the end point. Biologic validation of the radiomics score with RNA profiling of cytotoxic cells (cohort 4) was assessed with Mann-Whitney analysis. Results The radiomics signature was developed in 85 patients (cohort 1: mean age, 58 years ± 13 [standard deviation]; 43 men) and tested on 46 patients (cohort 2: mean age, 70 years ± 12; 37 men) and 47 patients (cohort 3: mean age, 64 years ± 11; 40 men). Biologic validation was performed in a further cohort of 20 patients (cohort 4: mean age, 60 years ± 13; 14 men). The radiomics signature was associated with clinical response to immune checkpoint inhibitors (area under the curve [AUC], 0.70; 95% CI: 0.64, 0.77; P < .001). In cohorts 2 and 3, the AUC was 0.67 (95% CI: 0.58, 0.76) and 0.67 (95% CI: 0.56, 0.77; P < .001), respectively. A radiomics-clinical signature (including baseline albumin level and lymphocyte count) improved on radiomics-only performance (AUC, 0.74 [95% CI: 0.63, 0.84; P < .001]; Akaike information criterion, 107.00 and 109.90, respectively). Conclusion A pretreatment CT-based radiomics signature is associated with response to immune checkpoint inhibitors, likely reflecting the tumor immunophenotype. © RSNA, 2021 Online supplemental material is available for this article. See also the editorial by Summers in this issue.
