Computed tomography-based radiomics for the differential diagnosis of pneumonitis in stage IV non-small cell lung cancer patients treated with immune checkpoint inhibitors

Autor: Fariba Tohidinezhad, Dennis Bontempi, Zhen Zhang, Anne-Marie Dingemans, Joachim Aerts, Gerben Bootsma, Johan Vansteenkiste, Sayed Hashemi, Egbert Smit, Hester Gietema, Hugo JWL. Aerts, Andre Dekker, Lizza E.L. Hendriks, Alberto Traverso, Dirk De Ruysscher
Přispěvatelé: Pulmonary Medicine, RS: GROW - R2 - Basic and Translational Cancer Biology, Radiotherapie, Beeldvorming, RS: GROW - R3 - Innovative Cancer Diagnostics & Therapy, Pulmonologie, MUMC+: MA Med Staf Spec Longziekten (9), MUMC+: DA BV Medisch Specialisten Radiologie (9), MUMC+: DA BV Research (9), RS: Carim - B06 Imaging, RS: FSE BISS, Clinical Data Science, Maastro clinic, Pulmonary medicine, AII - Cancer immunology, CCA - Cancer Treatment and quality of life, CCA - Cancer biology and immunology
Jazyk: angličtina
Rok vydání: 2023
Předmět:
Zdroj: European Journal of Cancer, 183, 142-151. Elsevier Ltd.
European Journal of Cancer, 183, 142-151. ELSEVIER SCI LTD
Tohidinezhad, F, Bontempi, D, Zhang, Z, Dingemans, A-M, Aerts, J, Bootsma, G, Vansteenkiste, J, Hashemi, S, Smit, E, Gietema, H, Aerts, H J WL, Dekker, A, Hendriks, L E L, Traverso, A & de Ruysscher, D 2023, ' Computed tomography-based radiomics for the differential diagnosis of pneumonitis in stage IV non-small cell lung cancer patients treated with immune checkpoint inhibitors ', European Journal of Cancer, vol. 183, pp. 142-151 . https://doi.org/10.1016/j.ejca.2023.01.027
European Journal of Cancer, 183, 142-151. Pergamon
ISSN: 0959-8049
Popis: Introduction: Immunotherapy-induced pneumonitis (IIP) is a serious side-effect which requires accurate diagnosis and management with high-dose corticosteroids. The differ-ential diagnosis between IIP and other types of pneumonitis (OTP) remains challenging due to similar radiological patterns. This study was aimed to develop a prediction model to differentiate IIP from OTP in patients with stage IV non-small cell lung cancer (NSCLC) who developed pneumonitis during immunotherapy. Methods: Consecutive patients with metastatic NSCLC treated with immunotherapy in six centres in the Netherlands and Belgium from 2017 to 2020 were reviewed and cause-specific pneumonitis events were identified. Seven regions of interest (segmented lungs and sphe-roidal/cubical regions surrounding the inflammation) were examined to extract the most pre-dictive radiomic features from the chest computed tomography images obtained at pneumonitis manifestation. Models were internally tested regarding discrimination, calibra-tion and decisional benefit. To evaluate the clinical application of the models, predicted labels were compared with the separate clinical and radiological judgements. Results: A total of 556 patients were reviewed; 31 patients (5.6%) developed IIP and 41 pa-tients developed OTP (7.4%). The line of immunotherapy was the only predictive factor in the clinical model (2nd versus 1st odds ratio Z 0.08, 95% confidence interval:0.01-0.77). The best radiomic model was achieved using a 75-mm spheroidal region of interest which showed an optimism-corrected area under the receiver operating characteristic curve of 0.83 (95% confidence interval:0.77-0.95) with negative and positive predictive values of 80% and 79%, respectively. Good calibration and net benefits were achieved for the radiomic model across the entire range of probabilities. A correct diagnosis was provided by the radiomic model in 10 out of 12 cases with non-conclusive radiological judgements. Conclusion: Radiomic biomarkers applied to computed tomography imaging may support cli-nicians making the differential diagnosis of pneumonitis in patients with NSCLC receiving immunotherapy, especially when the radiologic assessment is non-conclusive. 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
Databáze: OpenAIRE
Externí odkaz: