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Title: TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data

Abstract

Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philips Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantommore » materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.« less

Authors:
; ;  [1]; ; ;  [2];  [3]
  1. Washington University in St. Louis, St. Louis, MO (United States)
  2. Virginia Commonwealth University, Richmond, VA (United States)
  3. University of Pittsburgh, Pittsburgh, PA (United States)
Publication Date:
OSTI Identifier:
22653996
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; COMPUTERIZED TOMOGRAPHY; ELECTRON DENSITY; EXPERIMENTAL DATA; IMAGE PROCESSING; ITERATIVE METHODS; MEV RANGE 100-1000; PHANTOMS; PROTONS; STOPPING POWER

Citation Formats

Zhang, S, Politte, D, O’Sullivan, J, Han, D, Porras-Chaverri, M, Williamson, J, and Whiting, B. TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data. United States: N. p., 2016. Web. doi:10.1118/1.4957543.
Zhang, S, Politte, D, O’Sullivan, J, Han, D, Porras-Chaverri, M, Williamson, J, & Whiting, B. TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data. United States. doi:10.1118/1.4957543.
Zhang, S, Politte, D, O’Sullivan, J, Han, D, Porras-Chaverri, M, Williamson, J, and Whiting, B. Wed . "TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data". United States. doi:10.1118/1.4957543.
@article{osti_22653996,
title = {TU-FG-BRB-03: Basis Vector Model Based Method for Proton Stopping Power Estimation From Experimental Dual Energy CT Data},
author = {Zhang, S and Politte, D and O’Sullivan, J and Han, D and Porras-Chaverri, M and Williamson, J and Whiting, B},
abstractNote = {Purpose: This work aims at reducing the uncertainty in proton stopping power (SP) estimation by a novel combination of a linear, separable basis vector model (BVM) for stopping power calculation (Med Phys 43:600) and a statistical, model-based dual-energy CT (DECT) image reconstruction algorithm (TMI 35:685). The method was applied to experimental data. Methods: BVM assumes the photon attenuation coefficients, electron densities, and mean excitation energies (I-values) of unknown materials can be approximated by a combination of the corresponding quantities of two reference materials. The DECT projection data for a phantom with 5 different known materials was collected on a Philips Brilliance scanner using two scans at 90 kVp and 140 kVp. The line integral alternating minimization (LIAM) algorithm was used to recover the two BVM coefficient images using the measured source spectra. The proton stopping powers are then estimated from the Bethe-Bloch equation using electron densities and I-values derived from the BVM coefficients. The proton stopping powers and proton ranges for the phantom materials estimated via our BVM based DECT method are compared to ICRU reference values and a post-processing DECT analysis (Yang PMB 55:1343) applied to vendorreconstructed images using the Torikoshi parametric fit model (tPFM). Results: For the phantom materials, the average stopping power estimations for 175 MeV protons derived from our method are within 1% of the ICRU reference values (except for Teflon with a 1.48% error), with an average standard deviation of 0.46% over pixels. The resultant proton ranges agree with the reference values within 2 mm. Conclusion: Our principled DECT iterative reconstruction algorithm, incorporating optimal beam hardening and scatter corrections, in conjunction with a simple linear BVM model, achieves more accurate and robust proton stopping power maps than the post-processing, nonlinear tPFM based DECT analysis applied to conventional reconstructions of low and high energy scans. Funding Support: NIH R01CA 75371; NCI grant R01 CA 149305.},
doi = {10.1118/1.4957543},
journal = {Medical Physics},
number = 6,
volume = 43,
place = {United States},
year = {Wed Jun 15 00:00:00 EDT 2016},
month = {Wed Jun 15 00:00:00 EDT 2016}
}