Literature DB >> 22678123

Comprehensive analysis of proton range uncertainties related to patient stopping-power-ratio estimation using the stoichiometric calibration.

Ming Yang1, X Ronald Zhu, Peter C Park, Uwe Titt, Radhe Mohan, Gary Virshup, James E Clayton, Lei Dong.   

Abstract

The purpose of this study was to analyze factors affecting proton stopping-power-ratio (SPR) estimations and range uncertainties in proton therapy planning using the standard stoichiometric calibration. The SPR uncertainties were grouped into five categories according to their origins and then estimated based on previously published reports or measurements. For the first time, the impact of tissue composition variations on SPR estimation was assessed and the uncertainty estimates of each category were determined for low-density (lung), soft, and high-density (bone) tissues. A composite, 95th percentile water-equivalent-thickness uncertainty was calculated from multiple beam directions in 15 patients with various types of cancer undergoing proton therapy. The SPR uncertainties (1σ) were quite different (ranging from 1.6% to 5.0%) in different tissue groups, although the final combined uncertainty (95th percentile) for different treatment sites was fairly consistent at 3.0-3.4%, primarily because soft tissue is the dominant tissue type in the human body. The dominant contributing factor for uncertainties in soft tissues was the degeneracy of Hounsfield numbers in the presence of tissue composition variations. To reduce the overall uncertainties in SPR estimation, the use of dual-energy computed tomography is suggested. The values recommended in this study based on typical treatment sites and a small group of patients roughly agree with the commonly referenced value (3.5%) used for margin design. By using tissue-specific range uncertainties, one could estimate the beam-specific range margin by accounting for different types and amounts of tissues along a beam, which may allow for customization of range uncertainty for each beam direction.

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Year:  2012        PMID: 22678123      PMCID: PMC3396587          DOI: 10.1088/0031-9155/57/13/4095

Source DB:  PubMed          Journal:  Phys Med Biol        ISSN: 0031-9155            Impact factor:   3.609


  21 in total

1.  Methodologies and tools for proton beam design for lung tumors.

Authors:  M F Moyers; D W Miller; D A Bush; J D Slater
Journal:  Int J Radiat Oncol Biol Phys       Date:  2001-04-01       Impact factor: 7.038

2.  The composition of body tissues (II). Fetus to young adult.

Authors:  D R White; E M Widdowson; H Q Woodard; J W Dickerson
Journal:  Br J Radiol       Date:  1991-02       Impact factor: 3.039

3.  Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning.

Authors:  Jan Unkelbach; Thomas Bortfeld; Benjamin C Martin; Martin Soukup
Journal:  Med Phys       Date:  2009-01       Impact factor: 4.071

4.  Does kV-MV dual-energy computed tomography have an advantage in determining proton stopping power ratios in patients?

Authors:  M Yang; G Virshup; J Clayton; X R Zhu; R Mohan; L Dong
Journal:  Phys Med Biol       Date:  2011-06-30       Impact factor: 3.609

5.  A beam-specific planning target volume (PTV) design for proton therapy to account for setup and range uncertainties.

Authors:  Peter C Park; X Ronald Zhu; Andrew K Lee; Narayan Sahoo; Adam D Melancon; Lifei Zhang; Lei Dong
Journal:  Int J Radiat Oncol Biol Phys       Date:  2011-06-22       Impact factor: 7.038

6.  Bone models for use in radiotherapy dosimetry.

Authors:  H Q Woodard; D R White
Journal:  Br J Radiol       Date:  1982-04       Impact factor: 3.039

7.  Bragg peak prediction from quantitative proton computed tomography using different path estimates.

Authors:  Dongxu Wang; T Rockwell Mackie; Wolfgang A Tomé
Journal:  Phys Med Biol       Date:  2011-01-06       Impact factor: 3.609

8.  The composition of body tissues.

Authors:  H Q Woodard; D R White
Journal:  Br J Radiol       Date:  1986-12       Impact factor: 3.039

9.  The precision of proton range calculations in proton radiotherapy treatment planning: experimental verification of the relation between CT-HU and proton stopping power.

Authors:  B Schaffner; E Pedroni
Journal:  Phys Med Biol       Date:  1998-06       Impact factor: 3.609

10.  Compensating for heterogeneities in proton radiation therapy.

Authors:  M Urie; M Goitein; M Wagner
Journal:  Phys Med Biol       Date:  1984-05       Impact factor: 3.609

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  69 in total

1.  Material elemental decomposition in dual and multi-energy CT via a sparsity-dictionary approach for proton stopping power ratio calculation.

Authors:  Chenyang Shen; Bin Li; Liyuan Chen; Ming Yang; Yifei Lou; Xun Jia
Journal:  Med Phys       Date:  2018-02-23       Impact factor: 4.071

2.  Validation of an in-vivo proton beam range check method in an anthropomorphic pelvic phantom using dose measurements.

Authors:  El H Bentefour; Shikui Tang; Ethan W Cascio; Mauro Testa; Deepak Samuel; Damien Prieels; Bernard Gottschalk; Hsiao-Ming Lu
Journal:  Med Phys       Date:  2015-04       Impact factor: 4.071

Review 3.  Image guidance in proton therapy for lung cancer.

Authors:  Miao Zhang; Wei Zou; Boon-Keng Kevin Teo
Journal:  Transl Lung Cancer Res       Date:  2018-04

4.  Systematic analysis of the impact of imaging noise on dual-energy CT-based proton stopping power ratio estimation.

Authors:  Hugh H C Lee; Bin Li; Xinhui Duan; Linghong Zhou; Xun Jia; Ming Yang
Journal:  Med Phys       Date:  2019-04-01       Impact factor: 4.071

5.  The effect of beam purity and scanner complexity on proton CT accuracy.

Authors:  P Piersimoni; J Ramos-Méndez; T Geoghegan; V A Bashkirov; R W Schulte; B A Faddegon
Journal:  Med Phys       Date:  2017-01-09       Impact factor: 4.071

6.  Tissue decomposition from dual energy CT data for MC based dose calculation in particle therapy.

Authors:  Nora Hünemohr; Harald Paganetti; Steffen Greilich; Oliver Jäkel; Joao Seco
Journal:  Med Phys       Date:  2014-06       Impact factor: 4.071

7.  Comparison of x ray computed tomography number to proton relative linear stopping power conversion functions using a standard phantom.

Authors:  M F Moyers
Journal:  Med Phys       Date:  2014-06       Impact factor: 4.071

8.  Helium CT: Monte Carlo simulation results for an ideal source and detector with comparison to proton CT.

Authors:  Pierluigi Piersimoni; Bruce A Faddegon; José Ramos Méndez; Reinhard W Schulte; Lennart Volz; Joao Seco
Journal:  Med Phys       Date:  2018-05-20       Impact factor: 4.071

9.  Impact of Spot Size and Spacing on the Quality of Robustly Optimized Intensity Modulated Proton Therapy Plans for Lung Cancer.

Authors:  Chenbin Liu; Steven E Schild; Joe Y Chang; Zhongxing Liao; Shawn Korte; Jiajian Shen; Xiaoning Ding; Yanle Hu; Yixiu Kang; Sameer R Keole; Terence T Sio; William W Wong; Narayan Sahoo; Martin Bues; Wei Liu
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-02-14       Impact factor: 7.038

10.  Site-specific range uncertainties caused by dose calculation algorithms for proton therapy.

Authors:  J Schuemann; S Dowdell; C Grassberger; C H Min; H Paganetti
Journal:  Phys Med Biol       Date:  2014-07-03       Impact factor: 3.609

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