This retrospective single-center study investigates whether four-dimensional CT (4DCT)-based lung ventilation imaging can guide functional lung avoidance radiotherapy (FLAR) for patients with primary lung cancer.

Ventilation maps generated from planning 4DCT are used to identify well-ventilated lung regions, enabling paired comparison between functional lung avoidance radiotherapy plans and conventional anatomic radiotherapy plans.

The study aims to assess whether incorporating functional lung information into radiotherapy planning can reduce radiation exposure to well-ventilated lung while maintaining adequate tumor coverage, and to explore its relationship with radiation-induced lung injury.

All analyses are based on existing clinical imaging, treatment planning data, and follow-up records. No additional interventions, imaging, or procedures are performed as part of this study.

This study retrospectively evaluates a functional lung-guided radiotherapy planning workflow based on four-dimensional CT (4DCT) ventilation imaging in patients with primary lung cancer who previously underwent thoracic radiotherapy.

High-quality 4DCT datasets acquired during routine simulation are processed to generate voxel-based lung ventilation maps using deformable image registration and Jacobian-based computational methods. These ventilation maps are spatially registered to planning CT images and incorporated into the treatment planning system to delineate high-function lung subregions.

For each eligible patient, paired radiotherapy plans are retrospectively generated and analyzed: a conventional anatomic radiotherapy plan and a functional lung avoidance radiotherapy (FLAR) plan that incorporates ventilation-defined avoidance structures. Both plans are optimized to achieve comparable target coverage while differing in lung avoidance strategy.

Dosimetric and clinical data are obtained from existing treatment planning records and routine clinical follow-up to support comparative analyses of functional lung sparing and associated pulmonary outcomes. All analyses are conducted retrospectively using data derived from standard clinical care. No prospective enrollment, additional imaging, or study-specific interventions are performed.

Inclusion Criteria:

• Histologically confirmed primary lung cancer (adenocarcinoma, squamous cell carcinoma, or small-cell carcinoma) treated with thoracic radiotherapy.
• High-quality 4DCT scans performed before radiotherapy, enabling generation of ventilation or perfusion maps.
• Radiotherapy plans designed using IMRT.
• Availability of both functional lung avoidance plans and conventional anatomical radiotherapy plans for paired analysis.
• Complete treatment and follow-up records, including radiation-induced lung injury (e.g., radiation pneumonitis) and pulmonary function tests.

Exclusion Criteria:

• Incomplete or poor-quality imaging data preventing accurate ventilation/perfusion map generation.
• Radiotherapy interrupted or incomplete for any reason.
• Severe underlying lung diseases (e.g., extensive emphysema, pulmonary fibrosis, active tuberculosis) that may confound treatment outcomes or toxicity assessment.
• Presence of other untreated primary malignancies during the study period.
• Prior lung surgery or local therapies (e.g., ablation) that may affect evaluation of radiation-induced lung injury.
• Missing follow-up data, making assessment of radiation-induced lung injury or long-term lung function changes impossible.

Single-center retrospective cohort of consecutive adults (≥18 years) with primary lung cancer treated with thoracic radiotherapy planned with IMRT, with adequate 4DCT scans for ventilation mapping (2022-01-01 to 2025-09-09).

De-identified individual participant data (IPD) underlying the primary results will be available to qualified researchers upon reasonable request after publication. Available data include demographics, key clinical outcomes (e.g., radiation-induced lung injury), 4DCT-derived ventilation maps, radiotherapy dose/plan files and DVH metrics. Direct identifiers will be removed; data will be shared in compliance with ethics approval and local regulations.

De-identified IPD and supporting documents will be available from publication of the primary results until 2035-08-31. Requests will be reviewed within 30 days of receipt and, if approved, data will be shared within 60 days after execution of a Data Use Agreement.

Qualified researchers with a methodologically sound proposal and evidence of IRB/ethics approval may request access. A Data Use Agreement with the sponsor institution is required. Only de-identified data will be shared; no re-identification, redistribution, or commercial use is permitted. Data will be transferred via secure, access-controlled methods. Please contact Zhi Chen (2023440076@stu.cqmu.edu.cn).