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

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.

[1]  Daniel W. Miller,et al.  Ion stopping powers and CT numbers. , 2010, Medical dosimetry : official journal of the American Association of Medical Dosimetrists.

[2]  Takashi Akagi,et al.  Determination of the mean excitation energy of water from proton beam ranges , 2007 .

[3]  A J Lomax,et al.  Intensity modulated proton therapy and its sensitivity to treatment uncertainties 2: the potential effects of inter-fraction and inter-field motions , 2008, Physics in medicine and biology.

[4]  Harald Paganetti,et al.  Relative biological effectiveness (RBE) values for proton beam therapy. , 2002, International journal of radiation oncology, biology, physics.

[5]  D. R. White,et al.  Average soft-tissue and bone models for use in radiation dosimetry. , 1987, The British journal of radiology.

[6]  R. Mohan,et al.  Theoretical variance analysis of single- and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues , 2010, Physics in medicine and biology.

[7]  H. Woodard The Composition of Human Cortical Bone Effect of Age and of Some Abnormalities , 1964, Clinical orthopaedics and related research.

[8]  D R White,et al.  Bone models for use in radiotherapy dosimetry. , 1982, The British journal of radiology.

[9]  WE‐A‐BRA‐03: Considerations of Inter‐Observer and Inter‐Fractional Anatomical Variability in Estimating the Beam Range Uncertainty in Proton Therapy of Prostate Cancer , 2010 .

[10]  D. R. White,et al.  The composition of body tissues (II). Fetus to young adult. , 1991, The British journal of radiology.

[11]  Cinzia Talamonti,et al.  Towards a proton imaging system , 2010 .

[12]  H. Sadrozinski,et al.  Design of a proton computed tomography system for applications in proton radiation therapy , 2004, 2003 IEEE Nuclear Science Symposium. Conference Record (IEEE Cat. No.03CH37515).

[13]  M Goitein,et al.  Compensating for heterogeneities in proton radiation therapy. , 1984, Physics in medicine and biology.

[14]  Cinzia Talamonti,et al.  Proton radiography for clinical applications , 2010 .

[15]  Pedro Andreo,et al.  On the clinical spatial resolution achievable with protons and heavier charged particle radiotherapy beams , 2009, Physics in medicine and biology.

[16]  I Kyriakou,et al.  A dielectric response study of the electronic stopping power of liquid water for energetic protons and a new I-value for water , 2009, Physics in medicine and biology.

[17]  Thomas Bortfeld,et al.  Reducing the sensitivity of IMPT treatment plans to setup errors and range uncertainties via probabilistic treatment planning. , 2008, Medical physics.

[18]  E Pedroni,et al.  The precision of proton range calculations in proton radiotherapy treatment planning: experimental verification of the relation between CT-HU and proton stopping power. , 1998, Physics in medicine and biology.

[19]  Wolfgang A Tomé,et al.  Bragg peak prediction from quantitative proton computed tomography using different path estimates , 2011, Physics in medicine and biology.

[20]  J F Ziegler,et al.  Comments on ICRU report no. 49: stopping powers and ranges for protons and alpha particles. , 1999, Radiation research.

[21]  J. Valentin Basic anatomical and physiological data for use in radiological protection: reference values , 2002, Annals of the ICRP.

[22]  Lei Dong,et al.  A beam-specific planning target volume (PTV) design for proton therapy to account for setup and range uncertainties. , 2012, International journal of radiation oncology, biology, physics.

[23]  E. Pedroni,et al.  The calibration of CT Hounsfield units for radiotherapy treatment planning. , 1996, Physics in medicine and biology.

[24]  Daniel W. Miller,et al.  Methodologies and tools for proton beam design for lung tumors. , 2001, International journal of radiation oncology, biology, physics.

[25]  V. Sipala,et al.  A proton imaging device: Design and status of realization , 2010 .

[26]  R Mohan,et al.  Does kV–MV dual-energy computed tomography have an advantage in determining proton stopping power ratios in patients? , 2011, Physics in medicine and biology.

[27]  C. Civinini,et al.  Characterization of a Silicon Strip Detector and a YAG:Ce Calorimeter for a Proton Computed Radiography Apparatus , 2010, IEEE Transactions on Nuclear Science.

[28]  Martin J. Berger,et al.  Evaluation of the collision stopping power of elements and compounds for electrons and positrons , 1982 .

[29]  R. Cloutier Tissue Substitutes in Radiation Dosimetry and Measurement. , 1989 .

[30]  A. Lomax,et al.  Intensity modulated proton therapy and its sensitivity to treatment uncertainties 1: the potential effects of calculational uncertainties , 2008, Physics in medicine and biology.

[31]  Zhengrong Liang,et al.  Reconstruction for proton computed tomography by tracing proton trajectories: a Monte Carlo study. , 2006, Medical physics.

[32]  D. R. White,et al.  The composition of body tissues. , 1986, The British journal of radiology.

[33]  O. Jäkel,et al.  The Influence of Stopping Powers upon Dosimetry for Radiation Therapy with Energetic Ions , 2007 .

[34]  Takeshi Hiraoka,et al.  Energy loss of 70 MeV protons in elements , 1992 .