A local contrast based approach to threshold segmentation for PET target volume delineation
Laura Drever1, Don M Robinson, Alexander McEwan
1Department of Physics, University of Alberta, Edmonton, Alberta, Canada T6G 1Z2.
Medical Physics
|July 29, 2006
Summary
Positron emission tomography (PET) can improve radiation therapy planning by better distinguishing tumors. This study explored using PET imaging contrast for accurate tumor volume delineation, finding it depends on target size and activity ratios.
Area of Science:
- Medical imaging
- Radiation oncology
- Image segmentation
Background:
- Current radiation therapy relies on precise high-dose delivery to defined volumes.
- Computed tomography (CT) struggles to differentiate cancerous from normal tissue.
- Positron emission tomography (PET) shows promise for differentiating malignant from healthy tissues.
Purpose of the Study:
- To investigate the use of a local contrast-based threshold segmentation approach for delineating PET target volumes.
- To assess the accuracy of PET-based tumor volume quantification in radiation treatment planning.
- To explore the clinical implementation and limitations of PET segmentation.
Main Methods:
- Utilized well-defined cylindrical and spherical volumes for segmentation analysis.
- Investigated a local contrast-based thresholding method on PET images.
- Analyzed the impact of contrast levels on volumetric quantification.
Main Results:
- Accurate volumetric quantification using PET segmentation is dependent on the activity concentration ratio between target and background.
- Target size and slice location significantly influence segmentation accuracy.
- Identified specific contrast levels yielding correct volumetric quantification.
Conclusions:
- PET imaging offers potential for improved tumor delineation in radiation therapy planning.
- Contrast-based threshold segmentation accuracy is influenced by several factors, including target characteristics and imaging parameters.
- Further exploration is needed for robust clinical implementation of PET-guided radiation therapy segmentation.
