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Title: SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy

Abstract

Purpose: The aim of this study is to develop radiation treatment planning using magnetic susceptibility obtained from quantitative susceptibility mapping (QSM) via MR imaging. This study demonstrates the feasibility of a method for generating a substitute for a CT image from an MRI. Methods: The head of a healthy volunteer was scanned using a CT scanner and a 3.0 T MRI scanner. The CT imaging was performed with a slice thickness of 2.5 mm at 80 and 120 kV (dual-energy scan). These CT images were converted to relative electron density (rED) using the CT-rED conversion table generated by a previous dual-energy CT scan. The CT-rED conversion table was generated using the conversion of the energy-subtracted CT number to rED via a single linear relationship. One T2 star-weighted 3D gradient echo-based sequence with four different echo times images was acquired using the MRI scanner. These T2 star-weighted images were used to estimate the phase data. To estimate the local field map, a Laplacian unwrapping of the phase and background field removal algorithm were implemented to process phase data. To generate a magnetic susceptibility map from the local field map, we used morphology enabled dipole inversion method. The rED map was resampledmore » to the same resolution as magnetic susceptibility, and the magnetic susceptibility-rED conversion table was obtained via voxel-by-voxel mapping between the magnetic susceptibility and rED maps. Results: A correlation between magnetic susceptibility and rED is not observed through our method. Conclusion: Our results show that the correlation between magnetic susceptibility and rED is not observed. As the next step, we assume that the voxel of the magnetic susceptibility map comprises two materials, such as water (0 ppm) and bone (-2.2 ppm) or water and marrow (0.81ppm). The elements of each voxel were estimated from the ratio of the two materials.« less

Authors:
; ; ; ;  [1]; ; ;  [2]; ;  [3]
  1. Tohoku University Graduate School of Medicine, Sendai, Miyagi (Japan)
  2. Tohoku University Hospital, Sendai, Miyagi (Japan)
  3. Tohoku University, Sendai, Miyagi (Japan)
Publication Date:
OSTI Identifier:
22626790
Resource Type:
Journal Article
Resource Relation:
Journal Name: Medical Physics; Journal Volume: 43; Journal Issue: 6; Other Information: (c) 2016 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA)
Country of Publication:
United States
Language:
English
Subject:
60 APPLIED LIFE SCIENCES; 61 RADIATION PROTECTION AND DOSIMETRY; ALGORITHMS; BIOMEDICAL RADIOGRAPHY; COMPUTERIZED TOMOGRAPHY; CORRELATIONS; IMAGE PROCESSING; IMAGES; LAPLACIAN; MORPHOLOGY; NMR IMAGING; RADIOTHERAPY; SKELETON; THICKNESS

Citation Formats

Ito, K, Kadoya, N, Chiba, M, Matsushita, H, Jingu, K, Sato, K, Nagasaka, T, Yamanaka, K, Dobashi, S, and Takeda, K. SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy. United States: N. p., 2016. Web. doi:10.1118/1.4955852.
Ito, K, Kadoya, N, Chiba, M, Matsushita, H, Jingu, K, Sato, K, Nagasaka, T, Yamanaka, K, Dobashi, S, & Takeda, K. SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy. United States. doi:10.1118/1.4955852.
Ito, K, Kadoya, N, Chiba, M, Matsushita, H, Jingu, K, Sato, K, Nagasaka, T, Yamanaka, K, Dobashi, S, and Takeda, K. 2016. "SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy". United States. doi:10.1118/1.4955852.
@article{osti_22626790,
title = {SU-F-I-24: Feasibility of Magnetic Susceptibility to Relative Electron Density Conversion Method for Radiation Therapy},
author = {Ito, K and Kadoya, N and Chiba, M and Matsushita, H and Jingu, K and Sato, K and Nagasaka, T and Yamanaka, K and Dobashi, S and Takeda, K},
abstractNote = {Purpose: The aim of this study is to develop radiation treatment planning using magnetic susceptibility obtained from quantitative susceptibility mapping (QSM) via MR imaging. This study demonstrates the feasibility of a method for generating a substitute for a CT image from an MRI. Methods: The head of a healthy volunteer was scanned using a CT scanner and a 3.0 T MRI scanner. The CT imaging was performed with a slice thickness of 2.5 mm at 80 and 120 kV (dual-energy scan). These CT images were converted to relative electron density (rED) using the CT-rED conversion table generated by a previous dual-energy CT scan. The CT-rED conversion table was generated using the conversion of the energy-subtracted CT number to rED via a single linear relationship. One T2 star-weighted 3D gradient echo-based sequence with four different echo times images was acquired using the MRI scanner. These T2 star-weighted images were used to estimate the phase data. To estimate the local field map, a Laplacian unwrapping of the phase and background field removal algorithm were implemented to process phase data. To generate a magnetic susceptibility map from the local field map, we used morphology enabled dipole inversion method. The rED map was resampled to the same resolution as magnetic susceptibility, and the magnetic susceptibility-rED conversion table was obtained via voxel-by-voxel mapping between the magnetic susceptibility and rED maps. Results: A correlation between magnetic susceptibility and rED is not observed through our method. Conclusion: Our results show that the correlation between magnetic susceptibility and rED is not observed. As the next step, we assume that the voxel of the magnetic susceptibility map comprises two materials, such as water (0 ppm) and bone (-2.2 ppm) or water and marrow (0.81ppm). The elements of each voxel were estimated from the ratio of the two materials.},
doi = {10.1118/1.4955852},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: Prostate radiation therapy dose planning directly on magnetic resonance imaging (MRI) scans would reduce costs and uncertainties due to multimodality image registration. Adaptive planning using a combined MRI-linear accelerator approach will also require dose calculations to be performed using MRI data. The aim of this work was to develop an atlas-based method to map realistic electron densities to MRI scans for dose calculations and digitally reconstructed radiograph (DRR) generation. Methods and Materials: Whole-pelvis MRI and CT scan data were collected from 39 prostate patients. Scans from 2 patients showed significantly different anatomy from that of the remaining patient population,more » and these patients were excluded. A whole-pelvis MRI atlas was generated based on the manually delineated MRI scans. In addition, a conjugate electron-density atlas was generated from the coregistered computed tomography (CT)-MRI scans. Pseudo-CT scans for each patient were automatically generated by global and nonrigid registration of the MRI atlas to the patient MRI scan, followed by application of the same transformations to the electron-density atlas. Comparisons were made between organ segmentations by using the Dice similarity coefficient (DSC) and point dose calculations for 26 patients on planning CT and pseudo-CT scans. Results: The agreement between pseudo-CT and planning CT was quantified by differences in the point dose at isocenter and distance to agreement in corresponding voxels. Dose differences were found to be less than 2%. Chi-squared values indicated that the planning CT and pseudo-CT dose distributions were equivalent. No significant differences (p > 0.9) were found between CT and pseudo-CT Hounsfield units for organs of interest. Mean {+-} standard deviation DSC scores for the atlas-based segmentation of the pelvic bones were 0.79 {+-} 0.12, 0.70 {+-} 0.14 for the prostate, 0.64 {+-} 0.16 for the bladder, and 0.63 {+-} 0.16 for the rectum. Conclusions: The electron-density atlas method provides the ability to automatically define organs and map realistic electron densities to MRI scans for radiotherapy dose planning and DRR generation. This method provides the necessary tools for MRI-alone treatment planning and adaptive MRI-based prostate radiation therapy.« less
  • Purpose: To develop a CBCT HU correction method using a patient specific HU to mass density conversion curve based on a novel image registration and organ mapping method for head-and-neck radiation therapy. Methods: There are three steps to generate a patient specific CBCT HU to mass density conversion curve. First, we developed a novel robust image registration method based on sparseness analysis to register the planning CT (PCT) and the CBCT. Second, a novel organ mapping method was developed to transfer the organs at risk (OAR) contours from the PCT to the CBCT and corresponding mean HU values of eachmore » OAR were measured in both the PCT and CBCT volumes. Third, a set of PCT and CBCT HU to mass density conversion curves were created based on the mean HU values of OARs and the corresponding mass density of the OAR in the PCT. Then, we compared our proposed conversion curve with the traditional Catphan phantom based CBCT HU to mass density calibration curve. Both curves were input into the treatment planning system (TPS) for dose calculation. Last, the PTV and OAR doses, DVH and dose distributions of CBCT plans are compared to the original treatment plan. Results: One head-and-neck cases which contained a pair of PCT and CBCT was used. The dose differences between the PCT and CBCT plans using the proposed method are −1.33% for the mean PTV, 0.06% for PTV D95%, and −0.56% for the left neck. The dose differences between plans of PCT and CBCT corrected using the CATPhan based method are −4.39% for mean PTV, 4.07% for PTV D95%, and −2.01% for the left neck. Conclusion: The proposed CBCT HU correction method achieves better agreement with the original treatment plan compared to the traditional CATPhan based calibration method.« less
  • Purpose: To determine the suitability of dual-energy CT (DECT) to calculate relative electron density (RED) of tissues for accurate proton therapy dose calculation. Methods: DECT images of RED tissue surrogates were acquired at 80 and 140 kVp. Samples (RED=0.19−2.41) were imaged in a water-equivalent phantom in a variety of configurations. REDs were calculated using the DECT numbers and inputs of the high and low energy spectral weightings. DECT-derived RED was compared between geometric configurations and for variations in the spectral inputs to assess the sensitivity of RED accuracy versus expected values. Results: RED accuracy was dependent on accurate spectral inputmore » influenced by phantom thickness and radius from the phantom center. Material samples located at the center of the phantom generally showed the best agreement to reference RED values, but only when attenuation of the surrounding phantom thickness was accounted for in the calculation spectra. Calculated RED changed by up to 10% for some materials when the sample was located at an 11 cm radius from the phantom center. Calculated REDs under the best conditions still differed from reference values by up to 5% in bone and 14% in lung. Conclusion: DECT has previously been used to differentiate tissue types based on RED and Z for binary tissue-type segmentation. To improve upon the current standard of empirical conversion of CT number to RED for treatment planning dose calculation, DECT methods must be able to calculate RED to better than 3% accuracy throughout the image. The DECT method is sensitive to the accuracy of spectral inputs used for calculation, as well as to spatial position in the anatomy. Effort to address adjustments to the spectral calculation inputs based on position and phantom attenuation will be required before DECT-determined RED can achieve a consistent level of accuracy for application in dose calculation.« less