One of the most popular diagnostics for oncology imaging is computed tomography (CT). Worldwide, the CT market accounts for 17.0 per cent of the total diagnostic medical imaging industry. As CT technology improves, physicians are able to use these tools for better approaches to patient treatment.
Radiation therapy is a commonly used treatment for many types of cancers, especially in the head and neck. Treatment outcomes have been enhanced with the use of advanced radiotherapy techniques such as intensity-modulated radiation therapy (IMRT) by delivering conformal radiation dose to tumors while sparing healthy surrounding tissue. In-room tomographic imaging has allowed the support of adaptive radiation therapy (ART) which aims to adapt treatment planning in response to patient variations. ART includes the delineating contours of tumors and normal tissue in order to adjust the treatment plan in response to the variations in the contours. However, it is extremely time consuming for physicians to manually delineate contours of tumor and normal organs at every treatment scan. It is not clinically feasible to re-optimize beam intensity maps in response to patient variations.
Deformable image registration computes a transformation map from a reference image to a target image in order to help automate the procedures in ART such as contouring and dose accumulation. The contours delineated by physicians at the initial planning can be propagated to target images from in-treatment scans using deformation maps from deformable image registration. However, deformable image registration utilizes correlations of image intensities between reference and target images, which result in physically impossible deformation maps.
To prevent physically implausible deformation maps, mathematical or biomechanical penalties or constraints have been applied with varying success. Rigidity penalties are imposed on parts of an image volume which are anatomically rigid. While there has been some success, the rigidity penalties often fail to separately preserve rigidity of multiple objects in a close proximity.
Distance-preserving penalty function for imposing local rigidity in deformable image registration
The proposed technology is a method for improving the accuracy of the deformable registration of tightly located skeletal components in the head and neck in planning CT scans and daily cone-beam CT (CBCT) scans of patients undergoing radiation therapy. The proposed rigidity penalty is designed to preserve intervoxel distances within each rigid component. Intervoxel distances are only calculated for the voxel pairs that belong to the same rigid object. By allowing the rigidity of each bony object to be independently preserved while not penalizing relative orientation of disconnect objects, the proposed penalty decreases the possibility of local misalignments, which cannot otherwise be corrected by the existing rigidity penalty in regions containing multiples rigid bodes in close proximity. Furthermore, this penalty will not impact the intensity-driven deformation of soft tissue away from the bony voxels.
- The adaptive radiation therapy of cancers in regions with multiple bony elements located close in proximity
- Industrial CT metrology for flaw detection in rigid objects
- Increased accuracy of aligning multiple bony elements in CT scans over current methods