skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: SU-F-T-398: Improving Radiotherapy Treatment Planning Using Dual Energy Computed Tomography Based Tissue Characterization

Abstract

Purpose: Both kVp settings and geometric distribution of various materials lead to significant change of the HU values, showing the largest discrepancy for high-Z materials and for the lowest CT scanning kVp setting. On the other hand, the dose distributions around low-energy brachytherapy sources are highly dependent on the architecture and composition of tissue heterogeneities in and around the implant. Both measurements and Monte Carlo calculations show that improper tissue characterization may lead to calculated dose errors of 90% for low energy and around 10% for higher energy photons. We investigated the ability of dual-energy CT (DECT) to characterize more accurately tissue equivalent materials. Methods: We used the RMI-467 heterogeneity phantom scanned in DECT mode with 3 different set-ups: first, we placed high electron density (ED) plugs within the outer ring of the phantom; then we arranged high ED plugs within the inner ring; and finally ED plugs were randomly distributed. All three setups were scanned with the same DECT technique using a single-source DECT scanner with fast kVp switching (Discovery CT750HD; GE Healthcare). Images were transferred to a GE Advantage workstation for DECT analysis. Spectral Hounsfield unit curves (SHUACs) were then generated from 50 to 140-keV, in 10-keV increments,more » for each plug. Results: The dynamic range of Hounsfield units shrinks with increased photon energy as the attenuation coefficients decrease. Our results show that the spread of HUs for the three different geometrical setups is the smallest at 80 keV. Furthermore, among all the energies and all materials presented, the largest difference appears at high Z tissue equivalent plugs. Conclusion: Our results suggest that dose calculations at both megavoltage and low photon energies could benefit in the vicinity of bony structures if the 80 keV reconstructed monochromatic CT image is used with the DECT protocol utilized in this work.« less

Authors:
; ; ; ; ;  [1]
  1. McGill University, Montreal, QC (Canada)
Publication Date:
OSTI Identifier:
22648995
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; ANIMAL TISSUES; COMPUTERIZED TOMOGRAPHY; KEV RANGE 10-100; MONTE CARLO METHOD; PHOTONS; PLANT TISSUES; RADIATION DOSE DISTRIBUTIONS

Citation Formats

Tomic, N, Bekerat, H, Seuntjens, J, Forghani, R, DeBlois, F, and Devic, S. SU-F-T-398: Improving Radiotherapy Treatment Planning Using Dual Energy Computed Tomography Based Tissue Characterization. United States: N. p., 2016. Web. doi:10.1118/1.4956583.
Tomic, N, Bekerat, H, Seuntjens, J, Forghani, R, DeBlois, F, & Devic, S. SU-F-T-398: Improving Radiotherapy Treatment Planning Using Dual Energy Computed Tomography Based Tissue Characterization. United States. doi:10.1118/1.4956583.
Tomic, N, Bekerat, H, Seuntjens, J, Forghani, R, DeBlois, F, and Devic, S. 2016. "SU-F-T-398: Improving Radiotherapy Treatment Planning Using Dual Energy Computed Tomography Based Tissue Characterization". United States. doi:10.1118/1.4956583.
@article{osti_22648995,
title = {SU-F-T-398: Improving Radiotherapy Treatment Planning Using Dual Energy Computed Tomography Based Tissue Characterization},
author = {Tomic, N and Bekerat, H and Seuntjens, J and Forghani, R and DeBlois, F and Devic, S},
abstractNote = {Purpose: Both kVp settings and geometric distribution of various materials lead to significant change of the HU values, showing the largest discrepancy for high-Z materials and for the lowest CT scanning kVp setting. On the other hand, the dose distributions around low-energy brachytherapy sources are highly dependent on the architecture and composition of tissue heterogeneities in and around the implant. Both measurements and Monte Carlo calculations show that improper tissue characterization may lead to calculated dose errors of 90% for low energy and around 10% for higher energy photons. We investigated the ability of dual-energy CT (DECT) to characterize more accurately tissue equivalent materials. Methods: We used the RMI-467 heterogeneity phantom scanned in DECT mode with 3 different set-ups: first, we placed high electron density (ED) plugs within the outer ring of the phantom; then we arranged high ED plugs within the inner ring; and finally ED plugs were randomly distributed. All three setups were scanned with the same DECT technique using a single-source DECT scanner with fast kVp switching (Discovery CT750HD; GE Healthcare). Images were transferred to a GE Advantage workstation for DECT analysis. Spectral Hounsfield unit curves (SHUACs) were then generated from 50 to 140-keV, in 10-keV increments, for each plug. Results: The dynamic range of Hounsfield units shrinks with increased photon energy as the attenuation coefficients decrease. Our results show that the spread of HUs for the three different geometrical setups is the smallest at 80 keV. Furthermore, among all the energies and all materials presented, the largest difference appears at high Z tissue equivalent plugs. Conclusion: Our results suggest that dose calculations at both megavoltage and low photon energies could benefit in the vicinity of bony structures if the 80 keV reconstructed monochromatic CT image is used with the DECT protocol utilized in this work.},
doi = {10.1118/1.4956583},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = 2016,
month = 6
}
  • Purpose: Dual energy computed tomography (DECT) pre-reconstruction methods require the prior knowledge of the X-ray source spectrum to allow extracting physical parameters needed for radiation therapy dose calculation, such as electron density (ED) and the effective atomic number (EAN). While DECT stoichiometric calibration may provide reliable performance for typical radiation therapy clinical conditions, it is yet to be adapted to prereconstruction methods. The presence of noise and inaccurate spectrum description may lead to systematic errors and artifacts which compromise the accuracy of treatment planning. Methods: A new technique is investigated which consists in applying a DECT stoichiometric calibration method tomore » a set of monoenergetic images obtained with a DECT prereconstruction method. To evaluate the performance of this extended method, a simulation environment is developed to generate DECT scans under well controlled conditions, to reconstruct monoenergetic images of a tissue-equivalent phantom from transformed sinograms and to extract ED and EAN maps using a DECT formalism. Result: Under simulated clinical conditions, the accuracy in determining ED with the extended method versus a pre-reconstruction method alone is shown to be better than 0.35% versus 0.5%, respectively. In the presence of a realistic noise level, EAN determination presents a relative mean error that drops from 2.5% to 0.5% once the calibration is applied. Considering a spectrum alteration by a 1 mm Cu layer, EAN errors are up to 30% for the pre-reconstruction method alone versus less than 3% for the extended method. Conclusion: This study shows that combining pre-reconstruction DECT methods with a stoichiometric calibration considerably improves the accuracy and reliability of tissue characterization for radiation therapy in a clinical context. The presented method could potentially be adapted as gold standard for dose calculation methods based on DECT.« less
  • A set of tannin-based Rhizophora spp. particleboard phantoms with dimension of 30 cm x 30 cm was fabricated at target density of 1.0 g/cm{sup 3}. The mass attenuation coefficient of the phantom was measured using {sup 60}Co gamma source. The phantoms were scanned using Computed Tomography (CT) scanner and the percentage depth dose (PDD) of the phantom was calculated using treatment planning system (TPS) at 6 MV and 10 MV x-ray and compared to that in solid water phantoms. The result showed that the mass attenuation coefficient of tannin-based Rhizohora spp. phantoms was near to the value of water with χ{sup 2} valuemore » of 1.2. The measured PDD also showed good agreement with solid water phantom at both 6 MV and 10 MV x-ray with percentage deviation below 8% at depth beyond the maximum dose, Z{sub max}.« less
  • Purpose: Four-dimensional computed tomography (4D-CT) is commonly used to account for respiratory motion of target volumes in radiotherapy to the thorax. From the 4D-CT acquisition, a maximum-intensity projection (MIP) image set can be created and used to help define the tumor motion envelope or the internal gross tumor volume (iGTV). The purpose of this study was to quantify the differences in automatically contoured target volumes for usage in the delivery of stereotactic body radiation therapy using MIP data sets generated from one of the four methods: (1) 4D-CT phase-binned (PB) based on retrospective phase calculations, (2) 4D-CT phase-corrected phase-binned (PC-PB)more » based on motion extrema, (3) 4D-CT amplitude-binned (AB), and (4) cine CT built from all available images. Methods: MIP image data sets using each of the four methods were generated for a cohort of 28 patients who had prior thoracic 4D-CT scans that exhibited lung tumor motion of at least 1 cm. Each MIP image set was automatically contoured on commercial radiation treatment planning system. Margins were added to the iGTV to observe differences in the final simulated planning target volumes (PTVs). Results: For all patients, the iGTV measured on the MIP generated from the entire cine CT data set (iGTV{sub cine}) was the largest. Expressed as a percentage of iGTV{sub cine}, 4D-CT iGTV (all sorting methods) ranged from 83.8% to 99.1%, representing differences in the absolute volume ranging from 0.02 to 4.20 cm{sup 3}; the largest average and range of 4D-CT iGTV measurements was from the PC-PB data set. Expressed as a percentage of PTV{sub cine} (expansions applied to iGTV{sub cine}), the 4D-CT PTV ranged from 87.6% to 99.6%, representing differences in the absolute volume ranging from 0.08 to 7.42 cm{sup 3}. Regions of the measured respiratory waveform corresponding to a rapid change of phase or amplitude showed an increased susceptibility to the selection of identical images for adjacent bins. Duplicate image selection was most common in the AB implementation, followed by the PC-PB method. The authors also found that the image associated with the minimum amplitude measurement did not always correlate with the image that showed maximum tumor motion extent. Conclusions: The authors identified cases in which the MIP generated from a 4D-CT sorting process under-represented the iGTV by more than 10% or up to 4.2 cm{sup 3} when compared to the iGTV{sub cine}. They suggest utilization of a MIP generated from the full cine CT data set to ensure maximum inclusive tumor extent.« less
  • Purpose: To evaluate the implications of differences between contours drawn manually and contours generated automatically by deformable image registration for four-dimensional (4D) treatment planning. Methods and Materials: In 12 lung cancer patients intensity-modulated radiotherapy (IMRT) planning was performed for both manual contours and automatically generated ('auto') contours in mid and peak expiration of 4D computed tomography scans, with the manual contours in peak inspiration serving as the reference for the displacement vector fields. Manual and auto plans were analyzed with respect to their coverage of the manual contours, which were assumed to represent the anatomically correct volumes. Results: Auto contoursmore » were on average larger than manual contours by up to 9%. Objective scores, D{sub 2%} and D{sub 98%} of the planning target volume, homogeneity and conformity indices, and coverage of normal tissue structures (lungs, heart, esophagus, spinal cord) at defined dose levels were not significantly different between plans (p = 0.22-0.94). Differences were statistically insignificant for the generalized equivalent uniform dose of the planning target volume (p = 0.19-0.94) and normal tissue complication probabilities for lung and esophagus (p = 0.13-0.47). Dosimetric differences >2% or >1 Gy were more frequent in patients with auto/manual volume differences {>=}10% (p = 0.04). Conclusions: The applied deformable image registration algorithm produces clinically plausible auto contours in the majority of structures. At this stage clinical supervision of the auto contouring process is required, and manual interventions may become necessary. Before routine use, further investigations are required, particularly to reduce imaging artifacts.« less
  • Purpose: An improvement in tissue assignment for low-dose rate brachytherapy (LDRB) patients using more accurate Monte Carlo (MC) dose calculation was accomplished with a metallic artifact reduction (MAR) method specific to dual-energy computed tomography (DECT). Methods: The proposed MAR algorithm followed a four-step procedure. The first step involved applying a weighted blend of both DECT scans (I {sub H/L}) to generate a new image (I {sub Mix}). This action minimized Hounsfield unit (HU) variations surrounding the brachytherapy seeds. In the second step, the mean HU of the prostate in I {sub Mix} was calculated and shifted toward the mean HUmore » of the two original DECT images (I {sub H/L}). The third step involved smoothing the newly shifted I {sub Mix} and the two original I {sub H/L}, followed by a subtraction of both, generating an image that represented the metallic artifact (I {sub A,(H/L)}) of reduced noise levels. The final step consisted of subtracting the original I {sub H/L} from the newly generated I {sub A,(H/L)} and obtaining a final image corrected for metallic artifacts. Following the completion of the algorithm, a DECT stoichiometric method was used to extract the relative electronic density (ρ{sub e}) and effective atomic number (Z {sub eff}) at each voxel of the corrected scans. Tissue assignment could then be determined with these two newly acquired physical parameters. Each voxel was assigned the tissue bearing the closest resemblance in terms of ρ{sub e} and Z {sub eff}, comparing with values from the ICRU 42 database. A MC study was then performed to compare the dosimetric impacts of alternative MAR algorithms. Results: An improvement in tissue assignment was observed with the DECT MAR algorithm, compared to the single-energy computed tomography (SECT) approach. In a phantom study, tissue misassignment was found to reach 0.05% of voxels using the DECT approach, compared with 0.40% using the SECT method. Comparison of the DECT and SECT D {sub 90} dose parameter (volume receiving 90% of the dose) indicated that D {sub 90} could be underestimated by up to 2.3% using the SECT method. Conclusions: The DECT MAR approach is a simple alternative to reduce metallic artifacts found in LDRB patient scans. Images can be processed quickly and do not require the determination of x-ray spectra. Substantial information on density and atomic number can also be obtained. Furthermore, calcifications within the prostate are detected by the tissue assignment algorithm. This enables more accurate, patient-specific MC dose calculations.« less