The value of positron emission tomography scan in predicting pathologic response of non-small cell lung cancer managed by neoadjuvant chemo-immunotherapy

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Authors: Louis-Emmanuel Chriqui, Maged Zaher, Etienne Abdelnour-Berchtold, Hasna Bouchaab, Nuria Mederos, Sabina Berezowska, Michel Gonzalez, Matthieu Zellweger, Solange Peters, Thorsten Krueger, Niklaus G. Schaefer, Jean Yannis Perentes
Cited by: 1

Abstract

Background: Neoadjuvant chemo-immunotherapy improves overall survival in resectable stage II–III non-small cell lung cancer (NSCLC). Post-induction re-staging remains challenging and typically relies on contrast-enhanced computed tomography (CT). We assessed the predictive value of 18F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) for tumor pathologic response and patient survival after induction therapy. Methods: We analyzed all stage II–III, node-positive NSCLC patients from a collected database [2017–2023] who received neoadjuvant chemo-immunotherapy followed by surgery, with pre- and post-induction cancer assessment by 18F-FDG PET/CT. We identified 37 patients and determined their demographic characteristics, initial tumor burden, surgical outcomes, pathologic response and overall survival. We then correlated cancer pathologic response and patient overall survival with the mean and max standard uptake value change (ΔSUV) of the primary tumor and lymph nodes between the pre- and post-induction 18F-FDG PET/CTs using receiver operating characteristic (ROC) and Kaplan-Meier analyses, respectively. Results: Seventeen women and 20 men (mean age 64±7 years) had mostly stage III adenocarcinomas. Open lobectomies (59%) were the most common procedures. Ninety-two percent of resections were R0. Major pathologic response (MPR) and pathologic complete response (pCR) occurred in 51% and 30% of patients, respectively. Mean/max tumor ΔSUV predicted pCR [area under the curve (AUC) =0.8135, P=0.004/AUC =0.8086, P=0.0045] but mean/max lymph node ΔSUV predicted pCR better (AUC =0.9044, P

Fields of Study & Subjects

Cancer Immunotherapy and Biomarkers Lung Cancer Diagnosis and Treatment Radiomics and Machine Learning in Medical Imaging

Publication details

Journal / source
Journal of Thoracic Disease
Publisher
AME Publishing Company
Volume
18
Issue
2
Pages
115–115
Publication date
1 February 2026
Language
EN