Purpose: Deformable image registration (DIR) is increasingly used for target volume definition in radiotherapy. However, this kind of method is challenged by the situation of postoperative breast cancer patients due to the large deformations and non-correspondence caused by tumor resection and clip insertion. To deal with this situation, fiducials, region of interests (ROIs) and voxel intensities were jointly used for higher registration accuracy.
Methods: Three metrics were combined to form the objective function of DIR algorithm. Fiducial-based metric minimizes the distance between 2 point sets with known correspondence. ROI-based metric utilized Kappa Statistic (KS) to maximize the overlap of corresponding ROIs. Intensity-based metric maximized mutual information (MI) between image intensities. Two sets of CT images before and after breast surgery were used for image registration. One set was the diagnostic CT image acquired before surgery, and another set was the planning CT image acquired after surgery for breast cancer radiotherapy. A total of 26 sets of CT images from 13 patients were collected retrospectively for the test. The registration accuracy of the proposed method was evaluated in terms of target registration error (TRE) and through visual assessment by the physician.
Results: The difference of mean TRE between the proposed joint-metric method and the conventional intensity-based method was statistically significant for soft tissue (2.06 vs. 7.82, P < 0.05), rigid structure (3.02 vs. 3.34, P < 0.05) and boundary (3.70 vs. 6.93, P < 0.05). For visual assessment, the proposed method achieved better matching for soft tissue and boundary.
Conclusion: The registration accuracy of the proposed method was higher than the conventional method based on the preliminary results. This method provides a feasible way for target volume definition in postoperative radiotherapy of breast cancer patients.