Efficiency of Contemporary Off-line Adaptive Radiotherapy for Lung Cancer

What this Trial Is About

Locally advanced non-small cell lung cancer (LA-NSCLC) is a common and deadly form of lung cancer often treated with a combination of systemic therapy, radiotherapy, and immunotherapy. Researchers are studying adaptive radiotherapy (ART), which adjusts treatment plans during radiotherapy to account for tumor and anatomical changes, potentially improving survival. This trial focuses on improving the efficiency of ART by using modern AI tools and advanced imaging to reduce labor and patient burden. The study involves a prospective phase where 30 patients undergo mid-treatment plan adaptations using repeated four-dimensional CT scans and AI-assisted contouring and planning tools, such as Syngo.via® and RapidPlan®. A retrospective phase will then evaluate the feasibility of using cone-beam CT (CBCT) imaging, routinely used for position verification, as a replacement for repeated planning CTs. This approach aims to reduce additional radiation exposure and appointments by generating synthetic CTs from CBCT images for treatment adaptation. Participants will have repeated imaging and treatment plan adjustments during their radiotherapy course, which lasts up to seven weeks. Researchers will measure the time required for each step of the ART workflow, compare treatment plan quality using dose-volume histograms, and assess contour accuracy with similarity metrics. The study also includes quality checks by medical physicists and physicians. The retrospective phase will analyze the performance of the CBCT-based workflow up to six months after treatment completion.

Efficiency of Contemporary Off-line Adaptive Radiotherapy for Lung Cancer