MR IMAGE-GUIDED PORTAL VERIFICATION FOR BRAIN TREATMENT FIELD

Purpose: To investigate a method for the generation of digitally recon structed radiographs directly from MR images (DRR-MRI) to guide a comp uterized portal verification procedure. Methods and Materials: Several major steps were developed to perform an MR image-guided portal verif ication procedure. Initially, a wavelet-based multiresolution adaptive thresholding method was used to segment the skin slice-by-slice in MR brain axial images. Some selected anatomical structures, such as targ et volume and critical organs, were then manually identified and were reassigned to relatively higher intensities. Interslice information wa s interpolated with a directional method to achieve comparable display resolution in three dimensions. Next, a ray-tracing method was used t o generate a DRR-MRI image at the planned treatment position, and the ray tracing was simply performed on summation of voxels along the ray. The skin and its relative positions were also projected to the DRR-MR I and were used to guide the search of similar features in the portal image. A Canny edge detector was used to enhance the brain contour in both portal and simulation images. The skin in the brain portal image was then extracted using a knowledge-based searching technique. Finall y, a Chamfer matching technique was used to correlate features between DRR-MRI and portal image. Results: The MR image-guided portal verific ation method was evaluated using a brain phantom case and a clinical p atient case. Both DRR-CT and DRR-MRI were generated using CT and MR ph antom images with the same beam orientation and then compared. The mat ching result indicated that the maximum deviation of internal structur es was less than 1 mm. The segmented results for brain MR slice images indicated that a wavelet-based image segmentation technique provided a reasonable estimation for the brain skin. For the clinical patient c ase with a given portal field, the MR image-guided verification method provided an excellent match between features in both DRR-MRI and port al image. Moreover, target volume could be accurately visualized in th e DRR-MRI and mapped over to the corresponding portal image for treatm ent verification. The accuracy of DRR-MRI was also examined by compari ng it to the corresponding simulation image. The matching results indi cated that the maximum deviation of anatomical features was less than 2.5 mm. Conclusion: A method for MR image-guided portal verification o f brain treatment field was developed. Although the radiographic appea rance in the DRR-MRI is different from that in the portal image, DRR-M RI provides essential anatomical features (landmarks and target volume ) as well as their relative locations to be used as references for com puterized portal verification. (C) 1998 Elsevier Science Inc.