Seyed Mehdi Bagherimofidi1, Claus Chunli Yang2, Roberto Rey-Dios3, Madhava R Kanakamedala2, Ali Fatemi2,4. 1. Department of Biomedical Engineering, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran. 2. Department of Radiation Oncology, University of Mississippi Medical Center, Jackson, MS 39216, United States. 3. Department of Neurosurgery, University of Mississippi Medical Center, Jackson, MS 39216, United States. 4. Department of Radiology, University of Mississippi Medical Center, Jackson, MS 39216, United States.
Abstract
AIM: Determine the 1) effectiveness of correction for gradient-non-linearity and susceptibility effects on both QUASAR GRID3D and CIRS phantoms; and 2) the magnitude and location of regions of residual distortion before and after correction. BACKGROUND: Using magnetic resonance imaging (MRI) as a primary dataset for radiotherapy planning requires correction for geometrical distortion and non-uniform intensity. MATERIALS AND METHODS: Phantom Study: MRI, computed tomography (CT) and cone beam CT images of QUASAR GRID3D and CIRS head phantoms were acquired. Patient Study: Ten patients were MRI-scanned for stereotactic radiosurgery treatment. Correction algorithm: Two magnitude and one phase difference image were acquired to create a field map. A MATLAB program was used to calculate geometrical distortion in the frequency encoding direction, and 3D interpolation was applied to resize it to match 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images. MPRAGE images were warped according to the interpolated field map in the frequency encoding direction. The corrected and uncorrected MRI images were fused, deformable registered, and a difference distortion map generated. RESULTS: Maximum deviation improvements: GRID3D , 0.27 mm y-direction, 0.07 mm z-direction, 0.23 mm x-direction. CIRS, 0.34 mm, 0.1 mm and 0.09 mm at 20-, 40- and 60-mm diameters from the isocenter. Patient data show corrections from 0.2 to 1.2 mm, based on location. The most-distorted areas are around air cavities, e.g. sinuses. CONCLUSIONS: The phantom data show the validity of our fast distortion correction algorithm. Patient-specific data are acquired in <2 min and analyzed and available for planning in less than a minute.
AIM: Determine the 1) effectiveness of correction for gradient-non-linearity and susceptibility effects on both QUASAR GRID3D and CIRS phantoms; and 2) the magnitude and location of regions of residual distortion before and after correction. BACKGROUND: Using magnetic resonance imaging (MRI) as a primary dataset for radiotherapy planning requires correction for geometrical distortion and non-uniform intensity. MATERIALS AND METHODS: Phantom Study: MRI, computed tomography (CT) and cone beam CT images of QUASAR GRID3D and CIRS head phantoms were acquired. Patient Study: Ten patients were MRI-scanned for stereotactic radiosurgery treatment. Correction algorithm: Two magnitude and one phase difference image were acquired to create a field map. A MATLAB program was used to calculate geometrical distortion in the frequency encoding direction, and 3D interpolation was applied to resize it to match 3D T1-weighted magnetization-prepared rapid gradient-echo (MPRAGE) images. MPRAGE images were warped according to the interpolated field map in the frequency encoding direction. The corrected and uncorrected MRI images were fused, deformable registered, and a difference distortion map generated. RESULTS: Maximum deviation improvements: GRID3D , 0.27 mm y-direction, 0.07 mm z-direction, 0.23 mm x-direction. CIRS, 0.34 mm, 0.1 mm and 0.09 mm at 20-, 40- and 60-mm diameters from the isocenter. Patient data show corrections from 0.2 to 1.2 mm, based on location. The most-distorted areas are around air cavities, e.g. sinuses. CONCLUSIONS: The phantom data show the validity of our fast distortion correction algorithm. Patient-specific data are acquired in <2 min and analyzed and available for planning in less than a minute.
Authors: Joseph Weygand; Clifton David Fuller; Geoffrey S Ibbott; Abdallah S R Mohamed; Yao Ding; Jinzhong Yang; Ken-Pin Hwang; Jihong Wang Journal: Int J Radiat Oncol Biol Phys Date: 2016-03-02 Impact factor: 7.038
Authors: Patricia Tai; Jake Van Dyk; Jerry Battista; Edward Yu; Larry Stitt; Jon Tonita; Olusegun Agboola; James Brierley; Rashid Dar; Christopher Leighton; Shawn Malone; Barbara Strang; Pauline Truong; Gregory Videtic; C Shun Wong; Rebecca Wong; Youssef Youssef Journal: Int J Radiat Oncol Biol Phys Date: 2002-07-01 Impact factor: 7.038