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Registration of magnetic resonance spectroscopic imaging to computed tomography for radiotherapy treatment planning
Author(s) -
Graves Edward E.,
Pirzkall Andrea,
Nelson Sarah J.,
Larson David,
Verhey Lynn
Publication year - 2001
Publication title -
medical physics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.473
H-Index - 180
eISSN - 2473-4209
pISSN - 0094-2405
DOI - 10.1118/1.1420400
Subject(s) - radiation treatment planning , magnetic resonance imaging , dicom , image registration , voxel , computer science , medical imaging , radiation therapy , fiducial marker , nuclear medicine , radiology , artificial intelligence , medical physics , computer vision , medicine , image (mathematics)
The incorporation of multiple imaging modalities into radiotherapy treatment planning offers the potential to improve identification of regions of pathology. This work outlines and evaluates a methodology for registration of magnetic resonance images (MRI) and spectroscopic images (MRSI) to computed tomography (CT) images, and visualization of the multimodality data on the treatment planning workstation. Volumetric magnetic resonance images were acquired during an examination prior to the initiation of radiotherapy. Registration between these images and the treatment planning computed tomography images was performed using an automated alignment routine, and was improved manually using an interactive registration tool. The parameters of the alignment were then used to transform the spectroscopic images into the same reference frame. The spectroscopy data were represented in terms of a statistical measure of abnormality, and embedded within the MRI data as overlaid contours. These images were sent via DICOM transfer to the treatment planning workstation. An analysis of the reproducibility of the MRSI contours for varying acquisition grid positions was also performed. The technique was applied to ten patients with malignant gliomas. In each case the quality of the final CT/MR registration was demonstrated by at least a 97% volume overlap. All data were reliably transmitted across the PACS network to the treatment planning workstation, and were able to be evaluated by a radiation oncologist prior to treatment planning. The median variation in contour location for a half‐voxel shift of the MRSI acquisition grid was found to be 1.4 mm. In this study, we demonstrate the feasibility of including functional magnetic resonance spectroscopic imaging information in the treatment planning process for radiation therapy. This technique has facilitated research into uses of MRSI in radiation therapy, and we are currently investigating methods of implementing our procedure into commercial treatment planning systems.