Synthetic PET From CT Improves Precision Diagnosis and Treatment of Lung Cancer: a Prospective, Observational, Multicenter Study
Trial Parameters
Brief Summary
This study aims to synthesise PET data that preserves biological relevance and adds clinical value to the diagnosis and prognosis of lung cancer by establishing anatomical-to-metabolic mapping based on paired diagnostic CT and FDG-PET scans, thereby prospectively validating the clinical utility of the model.
Eligibility Criteria
Inclusion Criteria: 1. Patients with non-small cell lung cancer scheduled to undergo PET-CT and pathological examinations; 2. Voluntarily participate and sign an informed consent form; Exclusion Criteria: 1. History of other malignant tumours; 2. Image artefacts; 3. Without pathological diagnostic information; 4. Without paired CT and FDG-PET scan images.