Tumor Characterization Using [18F]FDG PET Radiomics in a PD-L1-Positive NSCLC Cohort
Bernadett Erzsébet Kálmán, Agnieszka Bos-Liedke, Dániel Dezső, Ewelina Kaminska, Mateusz Matusewicz, Ferenc Budán, Domokos Mathe, János Girán, Dávid Sipos, Éva Pusztai, Árpád Boronkai, Zsombor Ritter

TL;DR
This study shows that [18F]FDG PET radiomics can help distinguish lung cancer types and predict PD-L1 status and prognosis in patients.
Contribution
The study identifies novel radiomic features associated with PD-L1 status and prognosis in squamous NSCLC.
Findings
Radiomic features like maximum diameter and metabolic tumor volume differ between squamous and adenocarcinoma subtypes.
PD-L1-positive squamous tumors show distinct imaging patterns compared to PD-L1-negative tumors.
Certain radiomic features correlate with NLR-based prognosis in PD-L1-positive patients.
Abstract
Background: Durvalumab consolidation following radiochemotherapy is now the standard treatment for unresectable stage III non-small cell lung cancer (NSCLC). [18F]FDG PET/CT offers valuable insights not just for staging but also for tumor characterization via radiomics, which can potentially predict histology, immunophenotype, and prognosis. Methods: We conducted a retrospective analysis of [18F]FDG PET/CT scans from stage IIIA–IIIB NSCLC patients treated at the Clinical Centre, University of Pécs. All biopsy samples were classified histologically (squamous vs. adenocarcinoma) and tested for PD-L1. Lung tumors were segmented using MEDISO InterViewTM FUSION software (version 3.12.002.0000). with an SUVmax threshold of four. Imaging features were extracted and compared based on histology, PD-L1 status, and neutrophil-to-lymphocyte ratio (NLR)-based prognosis groups. Statistical analyses…
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Taxonomy
TopicsRadiomics and Machine Learning in Medical Imaging · Cancer Immunotherapy and Biomarkers · Lung Cancer Diagnosis and Treatment
