MRI-based treatment planning with electron density information mapped from CT images: a preliminary study.
Nowadays magnetic resonance imaging (MRI) has been profoundly used in radiotherapy (RT) planning to aid the contouring of targets and critical organs in brain and intracranial cases, which is attributable to its excellent soft tissue contrast and multi-planar imaging capability. However, the lack of electron density information in MRI, together with the image distortion issues, precludes its use as the sole image set for RT planning and dose calculation. The purpose of this preliminary study is to probe the feasibility and evaluate an MRI-based radiation dose calculation process by providing MR images the necessary electron density (ED) information from a patient's readily available diagnostic/staging computed tomography (CT) images using an image registration model. To evaluate the dosimetric accuracy of the proposed approach, three brain and three intracranial cases were selected retrospectively for this study. For each patient, the MR images were registered to the CT images, and the ED information was then mapped onto the MR images by in-house developed software generating a modified set of MR images. Another set of MR images with voxel values assigned with the density of water was also generated. The original intensity modulated radiation treatment (IMRT) plan was then applied to the two sets of MR images and the doses were calculated. The dose distributions from the MRI-based calculations were compared to that of the original CT-based calculation. In all cases, the MRI-based calculations with mapped ED yielded dose values very close (within 2%) to that of the CT-based calculations. The MRI-based calculations with voxel values assigned with water density indicated a dosimetric error of 3-5%, depending on the treatment site. The present approach offers a means of utilizing MR images for accurate dose calculation and affords a potential to eliminate the redundant simulation CT by planning a patient's treatment with only simulation MRI and any available diagnostic/staging CT data.
Wang
C
C
Department of Radiation Oncology, Stanford University School of Medicine, Stanford, CA 94305, USA.
Chao
M
M
Lee
L
L
Xing
L
L
D001921:Brain / Q000473:pathology; D001932:Brain Neoplasms / Q000473:pathology / Q000532:radiotherapy*; D003952:Diagnostic Imaging / Q000379:methods; D004583:Electrons; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D008279:Magnetic Resonance Imaging / Q000379:methods*; D011874:Radiometry; D011880:Radiotherapy Planning, Computer-Assisted / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014057:Tomography, X-Ray Computed / Q000379:methods*
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