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Validation of a CT-based motion model with in-situ fluoroscopy for lung surface deformation estimation
M Ranjbar1,2,3, P Sabouri4,5,2, S Mossahebi4
1Department of Mechanical Engineering, University of Maryland, Baltimore County, Baltimore, MD, United States of America.
Physics in Medicine and Biology
|November 18, 2020
Summary
This study validates a new method for radiotherapy motion management using fluoroscopic images to improve surrogate-based motion models (SMMs). The updated SMMs significantly reduce target position errors compared to traditional 4DCT methods.
Area of Science:
- Medical Physics
- Radiotherapy Technology
- Image-Guided Therapy
Background:
- Surrogate-based motion models (SMMs) in radiotherapy are crucial for motion management but can break down due to changing correlations between surrogates and internal anatomy.
- Current SMMs are typically built using CT-simulation data, which may not reflect real-time treatment conditions.
Purpose of the Study:
- To validate a novel methodology for constructing and updating SMMs using fluoroscopic (FL) images acquired during actual radiotherapy treatment.
- To assess the performance of the FL-enhanced SMMs in improving the accuracy of internal target motion estimation compared to conventional 4DCT-based models.
Main Methods:
- A prospective study collected 4DCT scans, VisionRT (VRT) surfaces, and orthogonal FLs from five lung cancer patients.
- A simulated annealing optimization scheme maximized mutual information (MI) between digitally reconstructed radiographs (DRRs) and FLs to estimate lung deformations.
- The SMM, utilizing partial-least-regression, was trained on optimal deformations and VRT surfaces, with performance evaluated using MI scores and Hausdorff distances.
Main Results:
- The proposed SMM, incorporating FL data, demonstrated superior similarity between FLs and DRRs compared to 4DCT-based models.
- Patient-averaged reductions in mean and 95th percentile Hausdorff distances were significant for both right (3.6 mm, 7 mm) and left lung (3.1 mm, 4 mm) targets.
- The methodology proved feasible for model update using post-treatment FL, maintaining model fidelity and outperforming 4DCT for position estimation.
Conclusions:
- Incorporating intra-treatment fluoroscopic imaging into SMM construction and updating significantly enhances the accuracy of internal target motion management in radiotherapy.
- This validated methodology offers a more robust and precise approach to motion management, reducing positional errors and improving treatment efficacy.
- The use of FL data for SMM refinement holds promise for real-time adaptive radiotherapy strategies.
