T Stanescu1, S H Mousavi2, M Cole3, E Barberi3, K Wachowicz4. 1. Princess Margaret Cancer Centre, University Health Network, Department of Radiation Oncology, University of Toronto, 610 University Avenue, Toronto, Ontario M5G 2M9, Canada. Electronic address: Teodor.Stanescu@rmp.uhn.ca. 2. Princess Margaret Cancer Centre, University Health Network, Department of Radiation Oncology, University of Toronto, 610 University Avenue, Toronto, Ontario M5G 2M9, Canada. 3. Modus QA, London, Ontario N6H 5L6, Canada. 4. Cross Cancer Institute, Alberta Health Services, Department of Radiation Oncology, University of Alberta, 11560 University Avenue, Edmonton, AB T6G 1Z2, Canada.
Abstract
PURPOSE: The study investigates the numerical modelling as well as experimental validation of magnetic susceptibility effects with respect to a 3D linearity phantom used for the quantification of MR image distortions. METHODS: Magnetic field numerical simulations based on finite difference methods were conducted to generate the susceptibility (χ) model of the MRID3D phantom. Experimental data was acquired and analyzed for eight different MR scanners to include a wide range of scanning parameters. Distortion vector fields were generated by applying a harmonic analysis based on finite elements methods. Phantom scans for the same setup but with opposite polarities of the frequency encoding gradient were processed in conjunction with the susceptibility modelling to separately quantify three field components due to gradient non-linearities (GNL), B0 inhomogeneities and χ perturbations. RESULTS: The numerical modelling showed a significant range of χ value of up to 8.23 ppm, with a mean value of 2.9 ppm. The χ perturbations were found to be mostly present at the end plates of the cylindrical phantom design. The simulations also showed that setup rotations of up to 10° introduced only negligible variations in the χ model of less than 0.1 ppm. This allows for a straightforward practical implementation of the modelling as a single lookup table. After correcting for the χ perturbations, the B0 inhomogeneities were derived and found to be in good agreement with either the MR system manufacturer specifications or experimental data available in the literature. CONCLUSIONS: It is possible to accurately model the magnetic susceptibility signature of a 3D linearity device and remove it as a post-processing correction step. This is important as the procedure unlocks the ability of determining both the GNL field and B0 map of the scanner without the need of extra acquisitions or phantoms.
PURPOSE: The study investigates the numerical modelling as well as experimental validation of magnetic susceptibility effects with respect to a 3D linearity phantom used for the quantification of MR image distortions. METHODS: Magnetic field numerical simulations based on finite difference methods were conducted to generate the susceptibility (χ) model of the MRID3D phantom. Experimental data was acquired and analyzed for eight different MR scanners to include a wide range of scanning parameters. Distortion vector fields were generated by applying a harmonic analysis based on finite elements methods. Phantom scans for the same setup but with opposite polarities of the frequency encoding gradient were processed in conjunction with the susceptibility modelling to separately quantify three field components due to gradient non-linearities (GNL), B0 inhomogeneities and χ perturbations. RESULTS: The numerical modelling showed a significant range of χ value of up to 8.23 ppm, with a mean value of 2.9 ppm. The χ perturbations were found to be mostly present at the end plates of the cylindrical phantom design. The simulations also showed that setup rotations of up to 10° introduced only negligible variations in the χ model of less than 0.1 ppm. This allows for a straightforward practical implementation of the modelling as a single lookup table. After correcting for the χ perturbations, the B0 inhomogeneities were derived and found to be in good agreement with either the MR system manufacturer specifications or experimental data available in the literature. CONCLUSIONS: It is possible to accurately model the magnetic susceptibility signature of a 3D linearity device and remove it as a post-processing correction step. This is important as the procedure unlocks the ability of determining both the GNL field and B0 map of the scanner without the need of extra acquisitions or phantoms.