The clinical impact of uncertainties in the mean excitation energy of human tissues during proton therapy

Besemer, Abigail E; Paganetti, Harald; Bednarz, Bryan

doi:10.1088/0031-9155/58/4/887

Cited by 39 publications

(34 citation statements)

References 36 publications

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“…Our discussion of WET measurement methods is very brief, mainly because they are relatively simple and obvious. In practice, however, WET measurements remain very important (Andreo, 2009; Gottschalk, 2010a; Newhauser and Zhang, 2010; Zhang et al , 2010b; Besemer et al , 2013). …”

Section: Proton Transport Calculationsmentioning

confidence: 99%

The physics of proton therapy

2015

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The physics of proton therapy has advanced considerably since it was proposed in 1946. Today analytical equations and numerical simulation methods are available to predict and characterize many aspects of proton therapy. This article reviews the basic aspects of the physics of proton therapy, including proton interaction mechanisms, proton transport calculations, the determination of dose from therapeutic and stray radiations, and shielding design. The article discusses underlying processes as well as selected practical experimental and theoretical methods. We conclude by briefly speculating on possible future areas of research of relevance to the physics of proton therapy.

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Section: Proton Transport Calculationsmentioning

confidence: 99%

The physics of proton therapy

2015

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“…However, the I value of HAp we obtain by applying Bragg's rule [25] from each HAp component is 140.2 eV. Since the indetermination in the I value of HAp will influence the energy deposition profile of ion beams as a function of the penetration depth in the material [41], we use the SEICS (simulation of energetic ions and clusters through solids) code [44,70] projectile inside the target by solving its equation of motion [44,70]. The following physical processes are considered: (i) electronic interactions with the target electrons (ionization and excitation), which are the main channel of energy transfer to the target (with statistical fluctuations around the mean value taken into account); (ii) elastic collisions with the target nuclei, which are responsible of the projectile trajectory deviations and the elastic energy loss; and (iii) dynamical chargechanging processes of the projectile.…”

Section: Resultsmentioning

confidence: 99%

“…In particular, knowing the precise value of the mean excitation energy I of HAp (and bone) is strongly desirable, since this magnitude is the main target-dependent ingredient in the Bethe formula [40], which is extensively used for range determinations with submillimeter precision [41].…”

Section: Introductionmentioning

confidence: 99%

Energy deposition of H and He ion beams in hydroxyapatite films: A study with implications for ion-beam cancer therapy

et al. 2014

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Ion-beam cancer therapy is a promising technique to treat deep-seated tumors; however, for an accurate treatment planning, the energy deposition by the ions must be well known both in soft and hard human tissues. Although the energy loss of ions in water and other organic and biological materials is fairly well known, scarce information is available for the hard tissues (i.e., bone), for which the current stopping power information relies on the application of simple additivity rules to atomic data. Especially, more knowledge is needed for the main constituent of human bone, calcium hydroxyapatite (HAp), which constitutes 58% of its mass composition. In this work the energy loss of H and He ion beams in HAp films has been obtained experimentally. The experiments have been performed using the Rutherford backscattering technique in an energy range of 450-2000 keV for H and 400-5000 keV for He ions. These measurements are used as a benchmark for theoretical calculations (stopping power and mean excitation energy) based on the dielectric formalism together with the MELF-GOS (Mermin energy loss function-generalized oscillator strength) method to describe the electronic excitation spectrum of HAp. The stopping power calculations are in good agreement with the experiments. Even though these experimental data are obtained for low projectile energies compared with the ones used in hadron therapy, they validate the mean excitation energy obtained theoretically, which is the fundamental quantity to accurately assess energy deposition and depth-dose curves of ion beams at clinically relevant high energies. The effect of the mean excitation energy choice on the depth-dose profile is discussed on the basis of detailed simulations. Finally, implications of the present work on the energy loss of charged particles in human cortical bone are remarked.

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“…On the other hand, if I-values of actual patient tissues and physical phantom substitute deviate from their assumed ICRU values, the DECT stopping power images predicted by any two-parameter model will deviate from physical reality. Besemer et al 36 noted that liquid water I-value measurements span a range of approximately ±12% which corresponds to stopping power uncertainties of approximately ±0.8%. The accuracies achieved by the two-parameter models in this study were evaluated at the energy pair 90 and 140 kVp.…”

Section: Discussionmentioning

confidence: 99%

A linear, separable two-parameter model for dual energy CT imaging of proton stopping power computation

2016

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Purpose: To evaluate the accuracy and robustness of a simple, linear, separable, two-parameter model (basis vector model, BVM) in mapping proton stopping powers via dual energy computed tomography (DECT) imaging. Methods: The BVM assumes that photon cross sections (attenuation coefficients) of unknown materials are linear combinations of the corresponding radiological quantities of dissimilar basis substances (i.e., polystyrene, CaCl 2 aqueous solution, and water). The authors have extended this approach to the estimation of electron density and mean excitation energy, which are required parameters for computing proton stopping powers via the Bethe-Bloch equation. The authors compared the stopping power estimation accuracy of the BVM with that of a nonlinear, nonseparable photon cross section Torikoshi parametric fit model (VCU tPFM) as implemented by the authors and by Yang et al.["Theoretical variance analysis of single-and dual-energy computed tomography methods for calculating proton stopping power ratios of biological tissues," Phys. Med. Biol. 55, 1343-1362]. Using an idealized monoenergetic DECT imaging model, proton ranges estimated by the BVM, VCU tPFM, and Yang tPFM were compared to International Commission on Radiation Units and Measurements (ICRU) published reference values. The robustness of the stopping power prediction accuracy of tissue composition variations was assessed for both of the BVM and VCU tPFM. The sensitivity of accuracy to CT image uncertainty was also evaluated. Results: Based on the authors' idealized, error-free DECT imaging model, the root-mean-square error of BVM proton stopping power estimation for 175 MeV protons relative to ICRU reference values for 34 ICRU standard tissues is 0.20%, compared to 0.23% and 0.68% for the Yang and VCU tPFM models, respectively. The range estimation errors were less than 1 mm for the BVM and Yang tPFM models, respectively. The BVM estimation accuracy is not dependent on tissue type and proton energy range. The BVM is slightly more vulnerable to CT image intensity uncertainties than the tPFM models. Both the BVM and tPFM prediction accuracies were robust to uncertainties of tissue composition and independent of the choice of reference values. This reported accuracy does not include the impacts of I-value uncertainties and imaging artifacts and may not be achievable on current clinical CT scanners. Conclusions: The proton stopping power estimation accuracy of the proposed linear, separable BVM model is comparable to or better than that of the nonseparable tPFM models proposed by other groups. In contrast to the tPFM, the BVM does not require an iterative solving for effective atomic number and electron density at every voxel; this improves the computational efficiency of DECT imaging when iterative, model-based image reconstruction algorithms are used to minimize noise and systematic imaging artifacts of CT images. C

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The clinical impact of uncertainties in the mean excitation energy of human tissues during proton therapy

Cited by 39 publications

References 36 publications

The physics of proton therapy

The physics of proton therapy

Energy deposition of H and He ion beams in hydroxyapatite films: A study with implications for ion-beam cancer therapy

A linear, separable two-parameter model for dual energy CT imaging of proton stopping power computation

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