Efficiency of Contemporary Off-line Adaptive Radiotherapy for Lung Cancer (ECLAIR)

November 20, 2025 updated by: Universitaire Ziekenhuizen KU Leuven

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.

Study Overview

Status

Recruiting

Conditions

Intervention / Treatment

Detailed Description

Lung cancer ranks among the most commonly occurring cancer types globally and has the highest mortality rate. Non-small-cell lung cancer (NSCLC) is the predominant form, accounting for more than 85% of cases. Because symptoms often manifest late, many patients present with locally advanced disease (LA-NSCLC) at diagnosis. The cornerstone treatment for unresectable LA-NSCLC consists of a combination of systemic therapy and radiotherapy followed by immunotherapy.

Radiotherapy is preceded by a labor- and time-intensive treatment preparation process. This process first requires diagnostic imaging, such as PET-CT, followed by treatment-planning imaging using a dedicated breathing-guided four-dimensional (4D) planning CT. Subsequently, the tumor and surrounding organs at risk (OARs) must be contoured and independently reviewed by radiation oncologists according to internationally recommended guidelines. Commercial convolutional neural networks (CNNs) are currently used to support this contouring process. These models perform voxel-wise classification to label anatomical structures based on prior training data. A widely used commercial CE-marked application for OAR contouring is Syngo.via®.

After contouring, dosimetric treatment planning is performed. Plan creation begins with an optimization step followed by a dose calculation, aiming to achieve an acceptable balance between target coverage and OAR sparing. A commonly used CE-marked knowledge-based planning tool that streamlines this process is RapidPlan®. This system provides estimates of achievable dose distributions and guides dosimetrists and medical physicists toward high-quality plan generation. All preparatory steps are executed on the planning CT, which represents only a single anatomical snapshot at one moment in time.

Once preparation is complete, the radiotherapy course begins. Treatments are delivered daily over a period of up to seven weeks. Throughout this timeframe, both tumor and intrathoracic anatomical changes may occur, causing the initial contours and treatment plan to no longer match the patient's anatomy on the day of treatment. Adaptive radiotherapy (ART), in which the original plan is modified in response to anatomical changes, can therefore be beneficial. Clinical studies have demonstrated that patients with NSCLC may benefit from frequent treatment-plan adaptations in cases of tumor regression or intrathoracic shifts during the treatment course. Improvements in progression-free survival and overall survival have been reported, and routine mid-treatment offline ART is recommended for LA-NSCLC.

However, despite the evidence, very limited number of patients will receive adaptive radiotherapy. The extensive labor associated with contouring and treatment planning remains a major barrier to broad implementation of ART for all eligible patients.

Several contemporary tools have the potential to accelerate the adaptive process. In the present study, the investigators intend to prospectively perform mid-treatment adaptations in 30 patients with LA-NSCLC. These patients will undergo a repeated planning CT followed by renewed contouring and treatment planning, mirroring the pre-treatment workflow. This approach enables initial evaluation of the time efficiency of modern contouring and planning tools in an adaptive setting. All tools used are CE-marked and currently applied as part of standard clinical practice on the initial planning CT. Quality checks and manual reviews by medical physicists and physicians will be identical to pre-treatment procedures. For enrolled patients, the resulting treatment plan accounts for anatomical changes and may enhance tumor coverage and OAR protection.

A retrospective phase will begin after completion of all treatments. This phase will investigate the feasibility of incorporating state-of-the-art position-verification imaging-namely cone-beam CTs (CBCTs)-as a replacement for repeated planning CTs. If feasible, repeated 4DCT acquisition could be avoided, sparing patients additional imaging doses and reducing the burden of extra appointments. It will be essential to determine whether current contouring and planning tools can be applied effectively to CBCT data. The prospective workflow described above will serve as the benchmark for time efficiency and contouring and planning quality. This comparison will help determine whether transitioning from repeated 4DCTs to CBCTs within an ART workflow is viable and advantageous.

In the prospective ART workflow, the repeated 4D planning CT will be acquired, followed by automated OAR contouring using Syngo.via® and manual delineation of tumor lesions. Treatment planning will then be performed with RapidPlan®, which enhances optimization and reduces inter-observer variability. If the resulting adapted plan provides a dosimetric advantage, it will be implemented for the remainder of the radiotherapy course. Plan-verification procedures will mirror those used in pre-treatment planning, including approval by the responsible physicians and medical physicists. Time measurements will be recorded at each workflow step to serve as ground-truth data for the retrospective phase.

In the retrospective evaluation, the investigators will assess the performance of a CBCT-based ART workflow. Instead of a repeated 4DCT, daily CBCT images-acquired routinely for position verification-will be used. CBCT image quality for radiotherapy planning will be verified and converted into a synthetic CT using dedicated CE-marked software (MIM®). Synthetic CT generation improves the accuracy of dose calculations. Automated OAR contouring using Syngo.via® and MIM® will then be performed, followed by manual tumor delineation. Subsequent treatment planning will again be carried out using RapidPlan®. This process will evaluate the extent to which CBCT or synthetic CT can support adaptive treatment planning. As in the prospective phase, time registration will occur at all workflow stages.

Study Type

Interventional

Enrollment (Estimated)

30

Phase

  • Not Applicable

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Contact

Study Contact Backup

Study Locations

  • Belgium
    • Vlaams-Brabant
      • Leuven, Vlaams-Brabant, Belgium, 3000

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

  • Child
  • Adult
  • Older Adult

Accepts Healthy Volunteers

No

Description

Inclusion Criteria:

  1. Voluntary written informed consent of the participant or their legally authorized representative has been obtained prior to any screening procedures
  2. Patients diagnosed with non-small-cell lung cancer
  3. Locally advanced disease (≥Stage III)
  4. Treated with sequential or concurrent chemoradiotherapy

Exclusion Criteria:

  1. Small-cell lung cancer
  2. Non-small-cell lung cancer of early stage
  3. Mesothelioma

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

  • Primary Purpose: Treatment
  • Allocation: N/A
  • Interventional Model: Single Group Assignment
  • Masking: None (Open Label)

Arms and Interventions

Participant Group / Arm
Intervention / Treatment
Experimental: CT-based Adaptive Radiotherapy applied midtreatment. Retrospective CBCT-based Adaptive comparison
Device: 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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Time required for each step of the prospective adaptive radiotherapy workflow
Time Frame: From initiation of the mid-treatment 4DCT scan until final approval of the adapted treatment plan, assessed for each participant, up to 7 weeks of radiotherapy

The total time required to complete each component of the prospective adaptive radiotherapy workflow will be quantified. Time measurements will be recorded using standardized digital workflow time-logging templates in the department's hospital document management system. The following steps will be assessed:

  • Acquisition of the repeated 4D planning CT
  • Automated organ-at-risk contouring (Syngo.via®)
  • Physician approval of organ-at-risk contouring
  • Manual tumor delineation
  • Knowledge-based treatment planning (RapidPlan®)
  • Medical physics plan review and approval
  • Physician plan review and approval The primary variable will be the total cumulative duration (minutes) and step-specific durations (minutes).
From initiation of the mid-treatment 4DCT scan until final approval of the adapted treatment plan, assessed for each participant, up to 7 weeks of radiotherapy
Time required for each step of the retrospectively tested CBCT-based adaptive radiotherapy workflow
Time Frame: Assessed retrospectively for each participant from the first available mid-treatment CBCT to completion of the simulated treatment plan, up to 6 months

The total time required to complete each component of the retrospective CBCT-based adaptive radiotherapy workflow will be quantified. Time measurements will be recorded using standardized digital workflow time-logging templates in the department's hospital document management system. The following steps will be assessed:

  • CBCT acquisition (retrospective use of routine daily CBCT)
  • Preparation of the CBCT for accurate dose calculation (enhancing image quality, applying correct density to Hounsfield unit curve)
  • Automated organ-at-risk contouring (Syngo.via® and MIM®)
  • Manual tumor delineation
  • Knowledge-based treatment planning (RapidPlan®) The primary variable will be the total cumulative duration (minutes) and step-specific durations (minutes).
Assessed retrospectively for each participant from the first available mid-treatment CBCT to completion of the simulated treatment plan, up to 6 months
Plan quality comparison using dose-volume histogram (DVH) metrics
Time Frame: Assessed retrospectively after completion of radiotherapy, up to 6 months

Quality of CBCT-based or synthetic-CT-based adaptive treatment plans will be compared with reference prospective 4DCT-based plans. Metrics include:

  • Target coverage (i.e. iCTV, PTV) (%)
  • Organ-at-risk doses (i.e. lungs, spinal canal, esophagus, brachial plexi, mediastinal envelope, heart, contralateral lung) (Gy and %)
  • Dose deviations between CBCT-based/synthetic CT-based and 4DCT-based plans Evaluation will be performed using standard treatment planning system DVH tools.
Assessed retrospectively after completion of radiotherapy, up to 6 months
Contour accuracy comparison using similarity metrics (DSC, HD, ASSD)
Time Frame: Assessed retrospectively after completion of radiotherapy, up to 6 months

Contour similarity between CBCT-based (or synthetic-CT-based) contours and reference 4DCT-based contours will be evaluated. Metrics include:

  • Dice Similarity Coefficient (DSC) (unitless)
  • Hausdorff Distance (HD) (millimeters)
  • Average Symmetric Surface Distance (ASSD) (millimeters) Analyses will be performed using MIM®.
Assessed retrospectively after completion of radiotherapy, up to 6 months

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Universitaire Ziekenhuizen KU Leuven

Publications and helpful links

The person responsible for entering information about the study voluntarily provides these publications. These may be about anything related to the study.

General Publications

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (Actual)

June 21, 2024

Primary Completion (Estimated)

August 1, 2026

Study Completion (Estimated)

December 31, 2026

Study Registration Dates

First Submitted

November 14, 2025

First Submitted That Met QC Criteria

November 20, 2025

First Posted (Actual)

December 2, 2025

Study Record Updates

Last Update Posted (Actual)

December 2, 2025

Last Update Submitted That Met QC Criteria

November 20, 2025

Last Verified

November 1, 2025

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • S68182

Plan for Individual participant data (IPD)

Plan to Share Individual Participant Data (IPD)?

NO

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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