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SU-E-J-135: 3-D Fourier-Based Volumetric Registration for Estimating Intra-Fractional Lung Tumor Motion
Medical Physics
|May 19, 2017
Summary
This study introduces a 3D registration algorithm to accurately track lung tumor motion during respiration, enhancing radiotherapy precision. The method improves planning target volume (PTV) expansion for better patient outcomes.
Area of Science:
- Medical Imaging
- Radiotherapy Physics
- Computational Anatomy
Background:
- Accurate estimation of intra-fractional tumor motion is crucial for effective radiotherapy.
- Conventional 2D image registration methods are insufficient for capturing complex 3D respiratory motion.
Purpose of the Study:
- To develop and validate a novel 3D volumetric registration algorithm.
- To precisely estimate lung tumor motion between respiratory phases for improved radiotherapy accuracy.
Main Methods:
- Acquired 3D thoracic CT volumes in cine mode across different respiratory phases.
- Applied bicubic interpolation for volume upsampling and defined tumor sub-volumes.
- Utilized 3D phase correlation with inverse Fourier transformation for displacement estimation.
Main Results:
- The algorithm accurately estimated tumor motion between respiratory phases.
- Experimental results demonstrated high accuracy with mean square error below 1 mm.
- Validated on both artificial and clinical 4D CT datasets.
Conclusions:
- Extended 2D registration techniques to 3D for enhanced tumor motion estimation.
- The 3D motion information provides a reliable basis for PTV expansion.
- Significant potential for improving radiotherapy treatment planning accuracy.
