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Title: Characterization of tissue magnetic susceptibility-induced distortions for MRIgRT

Journal Article · · Medical Physics
DOI:https://doi.org/10.1118/1.4764481· OSTI ID:22096993
; ;  [1]
  1. Radiation Medicine Program, Princess Margaret Hospital, 610 University Avenue, Toronto, Ontario M5G 2M9 (Canada) and Department of Radiation Oncology, University of Toronto, 610 University Avenue, Toronto, Ontario M5G 2M9 (Canada)

Purpose: MR image geometric integrity is one of the building blocks of MRI-guided radiotherapy. In particular, tissue magnetic susceptibility-induced effects are patient-dependent and their behavior is difficult to assess and predict. In this study, the authors investigated in detail the characteristics of susceptibility ({chi}) distortions in the context of MRIgRT, including the case of two common MR-linac system configurations. Methods: The magnetic field distortions were numerically simulated for several imaging parameters and anatomical sites, i.e., brain, lung, pelvis (with air pockets), and prostate. The simulation process consisted of (a) segmentation of patient CT data into susceptibility relevant anatomical volumes (i.e., soft-tissue, bone and air/lung), (b) conversion of CT data into susceptibility masks by assigning bulk {chi} values to the structures defined at (a), (c) numerical computations of the local magnetic fields by using a finite difference algorithm, and (d) generation of the geometric distortion maps from the magnetic field distributions. For each patient anatomy, the distortions were quantified at the interfaces of anatomical structures with significantly different {chi} values. The analysis was performed for two specific orientations of the external main magnetic field (B{sub 0}) characteristic to the MR-linac systems, specifically along the z-axis for a bore MR scanner and in the (x,y)-plane for a biplanner magnet. The magnetic field local perturbations were reported in ppm. The metrics used to quantify the geometric distortions were the maximum, mean, and range of distortions. The numerical simulation algorithm was validated using phantom data measurements. Results: Susceptibility-induced distortions were determined for both quadratic and patient specific geometries. The numerical simulations showed a good agreement with the experimental data. The measurements were acquired at 1.5 and 3 T and with an encoding gradient varying between 3 and 20 mT/m by using an annular phantom mimicking the water-air and water-oil {chi} interfaces. For quadratic geometries, the magnitude of field distortion increased rapidly with the size of the inhomogeneity up to about 10 mm and then tended to plateau. This trend became more evident for materials with a larger {Delta}{chi} relative to water. The simulations showed only a slight increase in the maximum distortion values when the B{sub 0} orientation was varied with regard to the shape of the {chi} inhomogeneity. In the case of patient anatomy, the largest distortion values arose at the air-soft-tissue interface. Considering the two MR-linac system configurations and comparing the field distortion values corresponding to all organ structures, the distortions tended to be larger for the biplanar magnet. The authors provide a reference table with ppm values which can be used to easily evaluate the geometric distortions for patient data as a function of B{sub 0} and the strength of the encoding gradient. Conclusions: The susceptibility distortions were quantified as a function of multiple parameters such as the {chi} inhomogeneity size and shape, the magnitude of B{sub 0} and the readout gradient, and the orientation of B{sub 0} with respect to the sample geometry. The analysis was performed for several anatomical sites and corresponding to two B{sub 0} orientations as featured by MR-linac systems.

OSTI ID:
22096993
Journal Information:
Medical Physics, Vol. 39, Issue 12; Other Information: (c) 2012 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-2405
Country of Publication:
United States
Language:
English