Inter-comparison of relative stopping power estimation models for proton therapy

Assessment of quantitative information for radiation therapy at a first-generation clinical photon-counting computed tomography scanner

As one of the latest developments in X-ray computed tomography (CT), photon-counting technology allows spectral detection, demonstrating considerable advantages as compared to conventional CT. In this study, we investigated the use of a first-generation clinical photon-counting computed tomography (PCCT) scanner and estimated proton relative (to water) stopping power (RSP) of tissue-equivalent materials from virtual monoenergetic reconstructions provided by the scanner. A set of calibration and evaluation tissue-equivalent inserts were scanned at 120 kVp. Maps of relative electron density (RED) and effective atomic number (EAN) were estimated from the reconstructed virtual monoenergetic images (VMI) using an approach previously applied to a spectral CT scanner with dual-layer detector technology, which allows direct calculation of RSP using the Bethe-Bloch formula. The accuracy of RED, EAN, and RSP was evaluated by root-mean-square errors (RMSE) averaged over the phantom inserts. The reference RSP values were obtained experimentally using a water column in an ion beam. For RED and EAN, the reference values were calculated based on the mass density and the chemical composition of the inserts. Different combinations of low- and high-energy VMIs were investigated in this study, ranging from 40 to 190 keV. The overall lowest error was achieved using VMIs at 60 and 180 keV, with an RSP accuracy of 1.27% and 0.71% for the calibration and the evaluation phantom, respectively.

Towards sub-percentage uncertainty proton stopping-power mapping via dual-energy CT: direct experimental validation and uncertainty analysis of a statistical iterative image reconstruction method

PURPOSE

To assess the potential of a joint dual-energy CT reconstruction process (Statistical Image Reconstruction method built on a Basis Vector Model (JSIR-BVM)) implemented on a 16-slice commercial CT scanner to measure high spatial-resolution stopping-power ratio (SPR) maps with uncertainties of less than 1%.

METHODS

JSIR-BVM was used to reconstruct images of effective electron density and mean excitation energy from dual-energy CT (DECT) sinograms for ten high-purity samples of known density and atomic composition inserted into head and body phantoms. The measured DECT data consisted of 90 kVp and 140 kVp axial sinograms serially acquired on a Philips Brilliance Big Bore CT scanner without beam-hardening corrections. The corresponding SPRs were subsequently measured directly via ion chamber measurements on a MEVION S250 superconducting synchrocyclotron and evaluated theoretically from the known sample compositions and densities. Deviations of JSIR-BVM SPR values from their theoretically calculated and directly measured ground-truth values were evaluated for our JSIR-BVM method and for our implementation of the Hünemohr-Saito (H-S) DECT image-domain decomposition technique for SPR imaging. A thorough uncertainty analysis was then performed for 5 different scenarios (comparison of JSIR-BVM SPR/SP to International Commission on Radiation Measurements and Units (ICRU) benchmarks; comparison of JSIR-BVM SPR to measured benchmarks; and uncertainties in JSIR-BVM SPR/SP maps for patients of unknown composition) per the Joint Committee for Guides in Metrology (JCGM) and the Guide to expression of Uncertainty in Measurement (GUM), including the impact of uncertainties in measured photon spectra, sample composition and density, photon cross-section and I-value models, and random measurement uncertainty. Estimated SPR uncertainty for three main tissue groups in patients of unknown composition and the weighted proportion of each tissue type for three proton treatment sites were then used to derive a composite range uncertainty for our method.

RESULTS

Mean JSIR-BVM SPR estimates deviated by less than 1% from their theoretical and directly measured ground-truth values for most inserts and phantom geometries except for high density Delrin and Teflon samples with SPR error relative to proton measurements of 1.1% and -1.0% (Head Phantom) and 1.1% and -1.1% (Body Phantom). The overall RMS deviations over all samples were 0.39% and 0.52% (head phantom) and 0.43% and 0.57% (body phantom) relative to theoretical and directly measured ground-truth SPRs, respectively. The corresponding RMS (maximum) errors for the image-domain decomposition method were 2.68% and 2.73% (4.68% and 4.99%) for the head phantom and 0.71% and 0.87% (1.37% and 1.66%) for the body phantom. Compared to H-S SPR maps, JSIR-BVM yielded 30% sharper and two-fold sharper images for soft tissues and bone-like surrogates, respectively, while reducing noise by factors of 6 and 3, respectively. The uncertainty (coverage factor k = 1) of the DECT-to-benchmark values comparison ranged from 0.5% to 1.5% and is dominated by scanning-beam photon-spectra uncertainties. An analysis of the SPR uncertainty for patients of unknown composition showed a JSIR-BVM uncertainty of 0.65%, 1.21%, and 0.77% for soft-, lung-, and bony-tissue groups which led to a composite range uncertainty of 0.6%-0.9%.

CONCLUSIONS

Observed JSIR-BVM SPR estimation errors were all less than 50% of the estimated k = 1 total uncertainty of our benchmarking experiment, demonstrating that JSIR-BVM high spatial-resolution, low-noise SPR mapping is feasible and is robust to variations in the geometry of the scanned object. In contrast, the much larger H-S SPR estimation errors are dominated by imaging noise and residual beam-hardening artifacts. While the uncertainties characteristic of our current JSIR-BVM implementation can be as large as 1.5%, achieving <1% total uncertainty is feasible by improving the accuracy of scanner-specific scatter-profile and photon-spectrum estimates. With its robustness to beam-hardening artifact, image noise and variations in phantom size and geometry, JSIR-BVM has the potential to achieve high spatial-resolution SPR mapping with sub-percentage accuracy and estimated uncertainty in the clinical setting. This article is protected by copyright. All rights reserved.

The impact of secondary fragments on the image quality of helium ion imaging

Single-event ion imaging enables the direct reconstruction of the relative stopping power (RSP) information required for ion-beam therapy. Helium ions were recently hypothesized to be the optimal species for such technique. The purpose of this work is to investigate the effect of secondary fragments on the image quality of helium CT (HeCT) and to assess the performance of a prototype proton CT (pCT) scanner when operated with helium beams in Monte Carlo simulations and experiment. Experiments were conducted installing the U.S. pCT consortium prototype scanner at the Heidelberg Ion-Beam Therapy Center (HIT). Simulations were performed with the scanner using the TOPAS toolkit. HeCT images were reconstructed for a cylindrical water phantom, the CTP404 (sensitometry), and the CTP528 (line-pair) [Formula: see text] ® modules. To identify and remove individual events caused by fragmentation, the multistage energy detector of the scanner was adapted to function as a [Formula: see text] telescope. The use of the developed filter eliminated the otherwise arising ring artifacts in the HeCT reconstructed images. For the HeCT reconstructed images of a water phantom, the maximum RSP error was improved by almost a factor 8 with respect to unfiltered images in the simulation and a factor 10 in the experiment. Similarly, for the CTP404 module, the mean RSP accuracy improved by a factor 6 in both the simulation and the experiment when the filter was applied (mean relative error 0.40% in simulation, 0.45% in experiment). In the evaluation of the spatial resolution through the CTP528 module, the main effect of the filter was noise reduction. For both simulated and experimental images the spatial resolution was  ∼4 lp cm-1. In conclusion, the novel filter developed for secondary fragments proved to be effective in improving the visual quality and RSP accuracy of the reconstructed images. With the filter, the pCT scanner is capable of accurate HeCT imaging.

Optimized I-values for use with the Bragg additivity rule and their impact on proton stopping power and range uncertainty

Novel imaging modalities can improve the estimation of patient elemental compositions for particle treatment planning. The mean excitation energy (I-value) is a main contributor to the proton range uncertainty. To minimize their impact on beam range errors and quantify their uncertainties, the currently used I-values proposed in 1982 are revisited. The study aims at proposing a new set of optimized elemental I-values for use with the Bragg additivity rule (BAR) and establishing uncertainties on the optimized I-values and the BAR. We optimize elemental I-values for the use in compounds based on measured material I-values. We gain a new set of elemental I-values and corresponding uncertainties, based on the experimental uncertainties and our uncertainty model. We evaluate uncertainties on I-values and relative stopping powers (RSP) of 70 human tissues, taking into account statistical correlations between tissues and water. The effect of new I-values on proton beam ranges is quantified using Monte Carlo simulations. Our elemental I-values describe measured material I-values with higher accuracy than ICRU-recommended I-values (RMSE: 6.17% (ICRU), 5.19% (this work)). Our uncertainty model estimates an uncertainty component from the BAR to 4.42%. Using our elemental I-values, we calculate the I-value of water as 78.73  ±  2.89 eV, being consistent with ICRU 90 (78  ±  2 eV). We observe uncertainties on tissue I-values between 1.82-3.38 eV, and RSP uncertainties between 0.002%-0.44%. With transport simulations of a proton beam in human tissues, we observe range uncertainties between 0.31% and 0.47%, as compared to current estimates of 1.5%. We propose a set of elemental I-values well suited for human tissues in combination with the BAR. Our model establishes uncertainties on elemental I-values and the BAR, enabling to quantify uncertainties on tissue I-values, RSP as well as particle range. This work is particularly relevant for Monte Carlo simulations where the interaction probabilities are reconstructed from elemental compositions.

Deriving the mean excitation energy map from dual-energy and proton computed tomography

The mean excitation energy, I, is an essential quantity for proton treatment planning. This work investigated the feasibility of extracting the spatial distribution of I by combining two computed tomography (CT) modalities, dual-energy CT and proton CT, which provided the spatial distribution of the relative electron density and the stopping power relative to water, respectively. We provided the analytical derivation of I as well as its uncertainty. Results were validated on simulated X-ray and proton CT images of a digital anthropomorphic phantom. Accuracy was below 15% with a large uncertainty, which demonstrated the potential and limits of the technique.