Lung Cancer, PET-CT
Conditions
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.
Interventions
DIAGNOSTIC_TESTPET-CT
A PET-CT scan is performed prior to initiating systemic treatment for the tumour.
Sponsors
Shanghai Pulmonary Hospital, Shanghai, China
Study design
Observational model
COHORT
Time perspective
PROSPECTIVE
Eligibility
Sex/Gender
ALL
Age
18 Years to 85 Years
Healthy volunteers
No
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.
Design outcomes
Primary
| Measure | Time frame | Description |
|---|---|---|
| Structural similarity | 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) | 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) | 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 | 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
| Measure | Time frame | Description |
|---|---|---|
| predictive performance | 2025.12.1-2026.12.1 | Validation study of indicators demonstrating the added value of synthetic PET in lung cancer diagnosis: Accuracy in distinguishing benign from malignant lesions, Accuracy in diagnosing lymph node metastasis, Accuracy in diagnosing distant metastasis, Including corresponding diagnostic sensitivity, specificity, positive predictive value, negative predictive value, area under the curve (AUC), etc. |
Countries
China
Contacts
Primary ContactXinchen Shen
Outcome results
None listed