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Efficiency of Contemporary Off-line Adaptive Radiotherapy for Lung Cancer
Sponsor: Universitaire Ziekenhuizen KU Leuven
Summary
Locally advanced non-small cell lung cancer (LA-NSCLC) patients could benefit in overall and progression-free survival from regular dosimetric treatment plan adaptations during radiotherapy. This is known as adaptive radiotherapy (ART). However, implementing an adaptive radiotherapy workflow presents a highly cumbersome process. First, repeated planning-CT imaging during treatment is required, which results in additional radiation dose for patients. Second, an ART workflow includes the repetition of various manual and semi-automated tasks such as target and organ-at-risk contouring on the images and dosimetric treatment planning. These obstacles hinder widespread ART implementation. To avoid repeated planning-CT imaging, position-verification imaging can be utilized. Modern cone-beam CT (CBCT) imaging, integrated into the treatment unit, assists radiation therapists (RTTs) in administering the dose. Recent improvements in CBCT imaging sources and detectors have enhanced image quality. Moreover, it may be possible to calculate radiation dose directly on these CBCTs. Utilizing CBCT imaging for plan adaptation could also eliminate the need for an additional CT procedure, thereby increasing patient comfort. To address the labor-intensive contouring and treatment planning steps, CE-marked and validated commercial AI applications are already being used to support organ contouring and accelerate the treatment-planning process. These tools are currently applied to pre-treatment planning CTs. The time efficiency of these contemporary tools in a prospective ART workflow has yet to be studied, as has the feasibility of applying these applications within a CBCT-based ART workflow.
Key Details
Gender
All
Age Range
Any - Any
Study Type
INTERVENTIONAL
Enrollment
30
Start Date
2024-06-21
Completion Date
2026-12-31
Last Updated
2025-12-02
Healthy Volunteers
No
Interventions
CBCT-based adaptive radiotherapy
The objective is to temporarily implement and study the efficiency of a prospective ART workflow for LA-NSCLC using repeated planning-CT imaging. This initiative aims to contour and plan in accordance with the contemporary clinical AI-tools already being standard-of-care in the pre-treatment workflow, with a specific focus on evaluating and reporting the time efficiency of the process. Following the prospective part, we want to retrospectively study a CBCT-based ART workflow for LA-NSCLC using CBCT imaging in comparison with the CT-based ART workflow. The contours and treatment plans generated utilizing 4DCT imaging serve as ground truth. These retrospective tests are fully outside the clinical flow. We will evaluate whether it is possible to implement an adaptive workflow without repeated planning-CT imaging. For this objective, we will utilize the same commercial AI tools, with a focus on reporting both the time efficiency and the quality of contours and plans in comparison.
Locations (1)
UZ Leuven
Leuven, Vlaams-Brabant, Belgium