Synthetic PET From CT Improves Precision Diagnosis and Treatment of Lung Cancer: a Prospective, Observational, Multicenter Study
Trial Snapshot
- Phase
- Not Applicable
- Status
- Recruiting
- Sponsor
- Enrollment
- 10,000
- Locations
- 5
- Primary Endpoint
- Structural similarity
Study Overview
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.
Study Design
- Study Type
- Observational
- Observational Model
- Cohort
- Time Perspective
- Prospective
Eligibility Criteria
- Ages
- 18 Years to 85 Years (Adult, Older Adult)
- Sex
- All
- Accepts Healthy Volunteers
- No
Inclusion Criteria
- •Patients with non-small cell lung cancer scheduled to undergo PET-CT and pathological examinations;
- •Voluntarily participate and sign an informed consent form;
Exclusion Criteria
- •History of other malignant tumours;
- •Image artefacts;
- •Without pathological diagnostic information;
- •Without paired CT and FDG-PET scan images.
Outcomes
Primary Outcomes
Structural similarity
Time Frame: 2025.12.1-2026.12.1
This is a core outcome measure evaluating the degree of resemblance between the structural characteristics of synthetic PET images and reference PET images. It reflects whether the synthetic PET retains the key structural information of the original image, which is a fundamental indicator for confirming the structural relevance of synthetic PET.
Peak Signal-to-Noise Ratio (PSNR)
Time Frame: 2025.12.1-2026.12.1
A commonly used objective evaluation index in image quality assessment, calculated based on the mean square error between the synthetic PET image and the reference image. It quantifies the ratio of the maximum possible signal value in the image to the noise power that affects image quality. Higher PSNR values indicate that the synthetic PET image has less noise interference and better consistency with the reference image in terms of signal characteristics, thereby reflecting better retention of structural information.
Structural Similarity Index (SSIM)
Time Frame: 2025.12.1-2026.12.1
An index designed to simulate human visual perception to evaluate image structural similarity, which comprehensively considers three aspects: brightness, contrast, and structural consistency between the synthetic PET image and the reference image. The value range is between 0 and 1; a value closer to 1 means that the synthetic PET image has a higher degree of structural consistency with the reference image, indicating that the structural relevance is well retained.
Metabolic Parameter Consistency
Time Frame: 2025.12.1-2026.12.1
A key outcome measure for verifying the biological relevance of synthetic PET, which evaluates whether the metabolic characteristic parameters derived from synthetic PET are consistent with those from reference PET. Metabolic parameters are directly related to the biological functions of tissues/organs, so their consistency is crucial to ensuring that synthetic PET can be used for accurate biological activity assessment.
Secondary Outcomes
- predictive performance(2025.12.1-2026.12.1)
Investigators
Chang Chen
Chief Physician
Shanghai Pulmonary Hospital, Shanghai, China