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Enhancing liver tumor localization accuracy by prior-knowledge-guided motion modeling and a biomechanical model
You Zhang1, Michael R Folkert1, Xiaokun Huang1
1Department of Radiation Oncology, University of Texas Southwestern Medical Center, Dallas, TX, USA.
Quantitative Imaging in Medicine and Surgery
|August 27, 2019
Summary
Motion modeling and biomechanical modeling-guided CBCT (MM-Bio-CBCT) improves liver tumor localization accuracy. This technique enhances pre-treatment planning and intra-treatment verification, potentially reducing radiotherapy margins.
Area of Science:
- Medical Imaging
- Radiation Oncology
- Biomechanical Modeling
Background:
- Liver tumor localization for radiation therapy is challenging due to low contrast and respiratory motion.
- Previous biomechanical modeling (Bio-CBCT) improved accuracy but was limited by caudal liver boundary contrast.
- A novel motion modeling and biomechanical modeling-guided CBCT (MM-Bio-CBCT) technique was developed to further enhance accuracy.
Purpose of the Study:
- To develop and evaluate the MM-Bio-CBCT technique for improved liver tumor localization.
- To incorporate motion and biomechanical modeling to overcome limitations of previous methods.
- To assess the potential for reducing radiotherapy margins through enhanced localization accuracy.
Main Methods:
- MM-Bio-CBCT estimates new CBCT images by deforming a prior volume, solving the deformation vector field (DVF) via digitally-reconstructed radiographs (DRRs) matching.
- DVF accuracy is optimized using prior-knowledge-guided liver boundary motion modeling and finite-element-analysis-based biomechanical modeling.
- Accuracy was evaluated on XCAT phantom and real patient data, comparing MM-Bio-CBCT against 2D-3D deformation techniques and Bio-CBCT.
Main Results:
- MM-Bio-CBCT achieved higher DICE coefficients (0.89±0.11 in XCAT, 0.83±0.09 in patients) compared to Bio-CBCT (0.83±0.21, 0.78±0.12) and other methods.
- The technique localized liver tumors with an average center-of-mass-error (COME) of approximately 2 mm in both phantom and patient studies.
- Significant improvements in Dice coefficients were observed across all tested techniques when incorporating motion modeling.
Conclusions:
- MM-Bio-CBCT demonstrates superior liver tumor localization accuracy compared to Bio-CBCT.
- The technique shows promise for accurate pre-treatment liver tumor localization and intra-treatment verification.
- MM-Bio-CBCT may enable substantial reductions in radiotherapy margins.
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