18F-FDG PET/CT Radiomics Models for Precision Diagnosis and Prognosis in NSCLC

Condition(s) studied

Study summary

This multicenter retrospective study aims to investigate the value of 18F-FDG PET/CT radiomics features in the preoperative precision staging, pathological typing, gene mutation status prediction, and prognostic risk stratification of patients with Non-Small Cell Lung Cancer (NSCLC). The study involves constructing and validating machine learning models to provide imaging-based evidence for individualized precision clinical decision-making.

Eligibility

Primary outcome measure(s)

• Diagnostic Performance for TNM Staging and Histological Subtyping — Baseline
  Assessed by the Area Under the Receiver Operating Characteristic Curve (AUC), Sensitivity, and Specificity of the radiomics model in predicting T-stage, N-stage, and histological subtypes (ADC vs. SCC).
• Predictive Accuracy for EGFR Mutation Status — Baseline
  Assessed by the AUC, Sensitivity, and Specificity of the radiomics model in discriminating EGFR mutation status (positive vs. negative) compared to genetic testing results.
• Prognostic Value — From date of surgery up to 5 years
  Evaluation of Disease-Free Survival (DFS) and Overall Survival (OS). DFS is defined as time to recurrence or death. OS is defined as time to death from any cause.

Trial sites (4)

More Second Affiliated Hospital, Zhejiang University, School of Medicine trials in China

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