Using Synthetic PET From CT Scans to Improve Diagnosis and Treatment of Non-Small Cell Lung Cancer in a Multicenter Observational Study

What this Trial Is About

Researchers are evaluating a new way to improve the diagnosis and treatment of lung cancer by creating synthetic PET images from CT scans. This method aims to keep important biological details and add clinical value by linking anatomical CT images with metabolic PET scans. The study is observational and takes place across multiple centers to validate the usefulness of this approach for lung cancer patients. Participants will undergo paired diagnostic CT and FDG-PET scans as part of their routine clinical care, with the PET-CT scan performed before starting systemic treatment for the tumor. The study focuses on analyzing these imaging data to develop a model that maps anatomical details to metabolic activity, without adding extra treatment or interventions. During the study, researchers will measure how closely the synthetic PET images match the real ones using metrics like structural similarity, peak signal-to-noise ratio, and metabolic parameter consistency. They will also assess the predictive performance of the model. The study runs from December 2025 to December 2026, involving patients with non-small cell lung cancer who consent to participate and have both CT and FDG-PET scans available.

Synthetic PET From CT Improves Precision Diagnosis and Treatment of Lung Cancer: a Prospective, Observational, Multicenter Study