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Title: SU-E-J-37: Combining Proton Radiography and X-Ray CT Information to Better Estimate Relative Proton Stopping Power in a Clinical Environment

Abstract

Purpose: In standard proton therapy clinical practice, proton stopping power uncertainties are in the order of 3.5%, which affects the ability of placing the proton Bragg peak at the edge of the tumor. The innovating idea of this project is to approach the uncertainty problem in RSP by using combined information from X-ray CT and proton radiography along a few beam angles. In addition, this project aims to quantify the systematic error introduced by the theoretical models (Janni, ICRU49, Bischel) for proton stopping power in media. Methods: A 3D phantom of 36 cm3 composed of 9 materials randomly placed is created. Measured RSP values are obtained using a Gammex phantom with a proton beam. Theoretical RSP values are calculated with Beth-Block equation in combination with three databases (Janni, ICRU49 and Bischel). Clinical RSP errors are simulated by introducing a systematic (1.5%, 2.5%, 3.5%) and a random error (+/−0.5%) to the theoretical RSP. A ray-tracing algorithm uses each of these RSP tables to calculate energy loss for proton crossing the phantom through various directions. For each direction, gradient descent (GD) method is done on the clinical RSP table to minimize the residual energy difference between the simulation with clinical RSP andmore » with theoretical RSP. The possibility of a systematic material dependent error is investigated by comparing measured RSP to theoretical RSP as calculated from the three models. Results: Using 10,000 iterations on GD algorithm, RSP differences between theoretical values and clinical RSP have converged (<1%) for each error introduced. Results produced with ICRU49 have the smallest average difference (0.021%) to the measured RSP. Janni (1.168%) and Bischel (−0.372%) database shows larger systematic errors. Conclusion: Based on these results, ray-tracing optimisation using information from proton radiography and X-ray CT demonstrates a potential to improve the proton range accuracy in a clinical environment.« less

Authors:
 [1];  [2];  [2];  [3];  [1];  [2]
  1. Departement de physique, de genie physique et d'optique et Centre de recherche sur le cancer, Universite Laval, Quebec (Canada)
  2. Massachusetts General Hospital, Boston, MA (United States)
  3. Experimental Clinical Oncology, Aarhus University, 8000 Aarhus C (Denmark)
Publication Date:
OSTI Identifier:
22325299
Resource Type:
Journal Article
Journal Name:
Medical Physics
Additional Journal Information:
Journal Volume: 41; Journal Issue: 6; Other Information: (c) 2014 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); Journal ID: ISSN 0094-2405
Country of Publication:
United States
Language:
English
Subject:
07 ISOTOPES AND RADIATION SOURCES; 60 APPLIED LIFE SCIENCES; ACCURACY; ALGORITHMS; BRAGG CURVE; EQUATIONS; ERRORS; NEOPLASMS; PHANTOMS; PROTON BEAMS; PROTON RADIOGRAPHY; RADIOTHERAPY; SIMULATION; STOPPING POWER; X RADIATION

Citation Formats

CollinsFekete, C, Massachusetts General Hospital, Boston, MA, Dias, M, Dipartamento di Elettronica, Informazione e Bioingegneria - DEIB, Politecnico di Milano, Doolan, P, University College London, London, Hansen, David C, Beaulieu, L, and Seco, J. SU-E-J-37: Combining Proton Radiography and X-Ray CT Information to Better Estimate Relative Proton Stopping Power in a Clinical Environment. United States: N. p., 2014. Web. doi:10.1118/1.4888089.
CollinsFekete, C, Massachusetts General Hospital, Boston, MA, Dias, M, Dipartamento di Elettronica, Informazione e Bioingegneria - DEIB, Politecnico di Milano, Doolan, P, University College London, London, Hansen, David C, Beaulieu, L, & Seco, J. SU-E-J-37: Combining Proton Radiography and X-Ray CT Information to Better Estimate Relative Proton Stopping Power in a Clinical Environment. United States. https://doi.org/10.1118/1.4888089
CollinsFekete, C, Massachusetts General Hospital, Boston, MA, Dias, M, Dipartamento di Elettronica, Informazione e Bioingegneria - DEIB, Politecnico di Milano, Doolan, P, University College London, London, Hansen, David C, Beaulieu, L, and Seco, J. 2014. "SU-E-J-37: Combining Proton Radiography and X-Ray CT Information to Better Estimate Relative Proton Stopping Power in a Clinical Environment". United States. https://doi.org/10.1118/1.4888089.
@article{osti_22325299,
title = {SU-E-J-37: Combining Proton Radiography and X-Ray CT Information to Better Estimate Relative Proton Stopping Power in a Clinical Environment},
author = {CollinsFekete, C and Massachusetts General Hospital, Boston, MA and Dias, M and Dipartamento di Elettronica, Informazione e Bioingegneria - DEIB, Politecnico di Milano and Doolan, P and University College London, London and Hansen, David C and Beaulieu, L and Seco, J},
abstractNote = {Purpose: In standard proton therapy clinical practice, proton stopping power uncertainties are in the order of 3.5%, which affects the ability of placing the proton Bragg peak at the edge of the tumor. The innovating idea of this project is to approach the uncertainty problem in RSP by using combined information from X-ray CT and proton radiography along a few beam angles. In addition, this project aims to quantify the systematic error introduced by the theoretical models (Janni, ICRU49, Bischel) for proton stopping power in media. Methods: A 3D phantom of 36 cm3 composed of 9 materials randomly placed is created. Measured RSP values are obtained using a Gammex phantom with a proton beam. Theoretical RSP values are calculated with Beth-Block equation in combination with three databases (Janni, ICRU49 and Bischel). Clinical RSP errors are simulated by introducing a systematic (1.5%, 2.5%, 3.5%) and a random error (+/−0.5%) to the theoretical RSP. A ray-tracing algorithm uses each of these RSP tables to calculate energy loss for proton crossing the phantom through various directions. For each direction, gradient descent (GD) method is done on the clinical RSP table to minimize the residual energy difference between the simulation with clinical RSP and with theoretical RSP. The possibility of a systematic material dependent error is investigated by comparing measured RSP to theoretical RSP as calculated from the three models. Results: Using 10,000 iterations on GD algorithm, RSP differences between theoretical values and clinical RSP have converged (<1%) for each error introduced. Results produced with ICRU49 have the smallest average difference (0.021%) to the measured RSP. Janni (1.168%) and Bischel (−0.372%) database shows larger systematic errors. Conclusion: Based on these results, ray-tracing optimisation using information from proton radiography and X-ray CT demonstrates a potential to improve the proton range accuracy in a clinical environment.},
doi = {10.1118/1.4888089},
url = {https://www.osti.gov/biblio/22325299}, journal = {Medical Physics},
issn = {0094-2405},
number = 6,
volume = 41,
place = {United States},
year = {Sun Jun 01 00:00:00 EDT 2014},
month = {Sun Jun 01 00:00:00 EDT 2014}
}