Related Experiment Video
Updated: May 13, 2026

Dynamic Lung Tumor Tracking for Stereotactic Ablative Body Radiation Therapy
Published on: June 7, 2015
Robust organ mapped dose: using multiple image registrations to identify deformation uncertainty in radiation dose
Christopher Thompson1, Stina Svensson2, Robin Prestwich3
1Department of Medical Physics, Leeds Cancer Centre, Leeds Teaching Hospitals NHS Trust, Leeds, United Kingdom.
A new Robust Organ-Mapped Dose (ROAD) method improves cumulative dose estimation for reirradiation (reRT) by accounting for deformable image registration (DIR) uncertainty, enhancing treatment planning accuracy.
Area of Science:
- Radiation Oncology
- Medical Physics
- Image-guided Therapy
Background:
- Accurate cumulative dose estimation is crucial for safe and effective reirradiation (reRT) treatment planning.
- Deformable image registration (DIR) uncertainty poses a challenge in reRT dose accumulation.
- Existing methods may not fully capture spatial uncertainties in critical organs-at-risk (OARs).
Purpose of the Study:
- To introduce a Robust Organ-Mapped Dose (ROAD) method for estimating cumulative dose in OARs during reRT.
- To incorporate voxel-level DIR uncertainty into dose estimation using a novel resampling kernel.
- To improve the reliability of OAR dose assessment in reRT, especially in areas with significant anatomical changes.
Main Methods:
- Developed a dose resampling kernel based on the discordance among three independent DIR algorithms to estimate spatial uncertainty.
- Incorporated additional kernel expansions to account for uncertainties not captured by inter-DIR discordance, ensuring dose origin and sampling within OARs.
- Applied the ROAD method to pelvic, head-and-neck, and thoracic reRT cases, comparing results with baseline mapped doses and a fixed-kernel method.
Main Results:
- The ROAD framework successfully detected residual errors beyond DIR discordance using additional kernel expansions.
- ROAD demonstrated comparable dose distributions to fixed-kernel methods under low deformation uncertainty.
- ROAD showed superior robustness in regions with large anatomical variations (e.g., pelvis), reducing underestimation of mapped near-maximum doses without increasing overall dose.
Conclusions:
- The proposed ROAD framework provides a more reliable OAR dose estimate by explicitly incorporating voxel-level DIR uncertainty.
- ROAD enhances confidence in reirradiation dose assessment, particularly in cases with substantial anatomical changes.
- The ROAD method offers a practical and robust tool for clinical evaluation of cumulative organ doses in reRT.
More Related Videos
07:57Positron Emission Tomography-based Dose Painting Radiation Therapy in a Glioblastoma Rat Model using the Small Animal Radiation Research Platform
Published on: March 24, 2022
07:13Author Spotlight: An Efficient and Robust Software for Automated Fusion of Multiple Preclinical Imaging Modalities
Published on: October 27, 2023