Dual- and multi-energy CT for particle stopping-power estimation: current state, challenges and potential.

Range uncertainty has been a key factor preventing particle radiotherapy from reaching its full physical potential. One of the main contributing sources is the uncertainty in estimating particle stopping power (ρs) within patients. Currently, theρsdistribution in a patient is derived from a single-energy CT (SECT) scan acquired for treatment planning by converting CT number expressed in Hounsfield units (HU) of each voxel toρsusing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρsshare a linear relationship with electron density but differ in their additional dependence on elemental composition through different physical properties, i.e. effective atomic number and mean excitation energy, respectively. Because of that, the HLUT approach is particularly sensitive to differences in elemental composition between real human tissues and tissue surrogates as well as tissue variations within and among individual patients. The use of dual-energy CT (DECT) forρsprediction has been shown to be effective in reducing the uncertainty inρsestimation compared to SECT. The acquisition of CT data over different x-ray spectra yields additional information on the material elemental composition. Recently, multi-energy CT (MECT) has been explored to deduct material-specific information with higher dimensionality, which has the potential to further improve the accuracy ofρsestimation. Even though various DECT and MECT methods have been proposed and evaluated over the years, these approaches are still only scarcely implemented in routine clinical practice. In this topical review, we aim at accelerating this translation process by providing: (1) a comprehensive review of the existing DECT/MECT methods forρsestimation with their respective strengths and weaknesses; (2) a general review of uncertainties associated with DECT/MECT methods; (3) a general review of different aspects related to clinical implementation of DECT/MECT methods; (4) other potential advanced DECT/MECT applications beyondρsestimation.

Uncertainty-driven determination of target measurement times for indirect tracking validation in adaptive radiotherapy.

Objective. Hybrid indirect tumor tracking strategies combine continuous monitoring of surrogate signals with episodic radiographic imaging of the target to check and update their models during the treatment. This validation process is traditionally performed at predetermined and fixed-rate time intervals. This study investigates a new validation procedure based on the real-time uncertainty associated with the predicted target positions.Approach. An adaptive version of a Bayesian method for indirect tracking is developed to simulate different validation processes within a single framework: no validation, regular validation and uncertainty-based validation. While regular validation involves measuring targets at fixed intervals, uncertainty-based validation takes advantage of a key Bayesian feature, which is the real-time confidence information associated with predictions. The validation processes are applied to ground truth breathing signals consisting of a lung target and two different surrogates (one internal, one external). Their impact on prediction accuracy is evaluated with root-mean-square error (RMSE) and incidence of large errors. The number of validation measurements triggered is also examined.Main results. When using the internal surrogate and compared to regular validation, uncertainty-based validation results in significantly better prediction accuracy while using fewer validation measurements: RMSE and fraction of large errors are reduced on average by 12% and 26% respectively, with 36% fewer validation measurements. With the external surrogate, whose correlation with the target is less stable over time, more validation measurements are automatically triggered, which leads to a substantial reduction of prediction errors: RMSE and fraction of large errors are reduced on average by 17% and 28% respectively compared to regular validation. It is also observed that depending on the initial instant, regular validation can result in worse prediction accuracy compared to no validation.Significance. Uncertainty-based validation has the potential to be more efficient and effective than a validation process performed at prescheduled and fixed-rate time intervals.

One-step iterative reconstruction approach based on eigentissue decomposition for spectral photon-counting computed tomography.

Purpose: We propose a one-step tissue characterization method for spectral photon-counting computed tomography (SPCCT) using eigentissue decomposition (ETD), tailored for highly accurate human tissue characterization in radiotherapy. Methods: The approach combines a Poisson likelihood, a spatial prior, and a quantitative prior constraining eigentissue fractions based on expected values for tabulated tissues. There are two regularization parameters: α for the quantitative prior, and ß for the spatial prior. The approach is validated in a realistic simulation environment for SPCCT. The impact of α and ß is evaluated on a virtual phantom. The framework is tested on a virtual patient and compared with two sinogram-based two-step methods [using respectively filtered backprojection (FBP) and an iterative method for the second step] and a post-reconstruction approach with the same quantitative prior. All methods use ETD. Results: Optimal performance with respect to bias or RMSE is achieved with different combinations of α and ß on the cylindrical phantom. Evaluated in tissues of the virtual patient, the one-step framework outperforms two-step and post-reconstruction approaches to quantify proton-stopping power (SPR). The mean absolute bias on the SPR is 0.6% (two-step FBP), 0.6% (two-step iterative), 0.6% (post-reconstruction), and 0.2% (one-step optimized for low bias). Following the same order, the RMSE on the SPR is 13.3%, 2.5%, 3.2%, and 1.5%. Conclusions: Accurate and precise characterization with ETD can be achieved with noisy SPCCT data without the need to rely on post-reconstruction methods. The one-step framework is more accurate and precise than two-step methods for human tissue characterization.

Adaptive confidence regions for indirect tracking of moving tumors in radiotherapy.

BACKGROUND: Target motion in the course of radiotherapy is one of the largest factors affecting the treatment quality of highly dynamic sites such as lung. A critical component of real-time motion management is not only the prediction of tumor location at a future point in time but assessment of positional uncertainty for the purposes of margin adjustment and optimization of validation schemes. PURPOSE: In this study, we propose to investigate the ability of a confidence estimator to accurately reflect the reliability of individual target position predictions and prospectively detect large prediction errors by relying exclusively on a surrogate signal. METHODS: This work uses a Bayesian framework for indirect tracking. While constant covariance estimates are commonly used to express the uncertainty of the models involved, in this study new adaptive estimates are derived from the surrogate behavior to reflect increasing uncertainty when the breathing conditions differ from the reference conditions observed during the training step. The accuracy of the resulting 95% predicted confidence regions (CRs) is evaluated on nine breathing sequences involving changes of respiratory types (free, thoracic, abdominal, deep). The breathing motions are collected simultaneously from a lung target and two different surrogate signals (an external marker and an anatomical location within the liver). Receiver operating characteristic (ROC) analysis is performed to evaluate the ability of the predicted uncertainty to prospectively detect large prediction errors. RESULTS: Higher CR accuracy is obtained when using the proposed adaptive estimates over using constant estimations: on average over the cohort, the proportion of actual target positions lying within the 95% CR is increased by 40 and 35 p.p. with the internal and external surrogates. The time-dependent inflation of the CR width tends to match the magnitude variation of the prediction errors: the adaptive CR effectively enlarges when the target position cannot be predicted reliably, which corresponds to potentially high prediction errors. More precisely, the ROC analysis indicates that the proposed uncertainty estimate can detect if prediction errors are greater than 5 mm with on average high sensitivity (90%) and modest specificity (54% and 47% from internal and external surrogates, respectively). CONCLUSIONS: While relying exclusively on the surrogate motion characteristics being continuously monitored, the Bayesian framework coupled to adaptive uncertainty estimations can provide reliable CR able to detect large prediction errors. The findings of this study could be further used to automatically trigger risk management mechanisms prospectively.

Efficient dose-rate correction of silicon diode relative dose measurements.

PURPOSE: Silicon diodes are often the detector of choice for relative dose measurements, particularly in the context of radiotherapy involving small photon beams. However, a major drawback lies in their dose-rate dependency. Although ionization chambers are often too large for small field output factor (OF) measurements, they are valuable instruments to provide reliable percent-depth dose (PDD) curves in reference beams. The aim of this work is to propose a practical and accurate method for the characterization of silicon diode dose-rate dependence correction factors using ionization chamber measurements as a reference. METHODS: The robustness of ionization chambers for PDD measurements is used to quantify the dose-rate dependency of a diode detector. A mathematical formalism, which exploits the error induced in percent-depth ionization (PDI) curves for diodes by their dose-rate dependency, is developed to derive a dose-rate correction factor applicable to diode relative measurements. The method is based on the definition of the recombination correction factor given in the addendum to TG 51 and is applied to experimental measurements performed on a CyberKnife M6 radiotherapy unit using a PTW 60012 diode detector. A measurement-based validation is provided by comparing corrected PDI curves to measurements performed with a PTW 60019 diamond detector, which does not exhibit dose-rate dependence. RESULTS: Results of dose-rate correction factors for PDI curves, off-axis ratios (OARs), tissue-phantom ratios, and small field OFs are coherent with the expected behavior of silicon diode detectors. For all considered setups and field sizes, the maximum correction and the maximum impact of the uncertainties induced by the correction are obtained for OARs for the 60 mm collimator, with a correction of 2.5% and an uncertainty of 0.34%. For OFs, corrections range from 0.33% to 0.82% for all field sizes considered, and increase with the reduction of the field size. Comparison of PDI curves corrected for dose-rate and for in-depth beam quality variations illustrates excellent agreement with measurements performed using the diamond detector. CONCLUSION: The proposed method allows the efficient and precise correction of the dose-rate dependence of silicon diode detectors in the context of clinical relative dosimetry.

Monte Carlo investigation of electron fluence perturbation in MRI-guided radiotherapy beams using six commercial radiation detectors.

With the integration of treatments with MRI-linacs to the clinical workflow, the understanding and characterization of detector response in reference dosimetry in magnetic fields are required. The external magnetic field perturbs the electron fluence. The degree of perturbation depends on the irradiation conditions and on the detector type. The purpose of this study is to evaluate the magnetic field impact on the electron fluence spectra in several detectors to provide a deeper understanding of detector response in these conditions. Monte Carlo calculations of the electron fluence are performed in six detectors (solid-state: PTW60012 and PTW60019, ionization chambers: PTW30013, PTW31010, PTW31021, and PTW31022) in water and irradiated by a 7 MV FFF photon beam with a small and a reference field, at 0 and 1.5 T. Three chamber axis orientations are investigated: parallel or perpendicular (either the Lorentz force pointing towards the stem or the tip) to the magnetic field and always perpendicular to the photon beam. One orientation for the solid-state detector is studied: parallel to the photon beam and perpendicular to the magnetic field. Additionally, electron fluence spectra are calculated in modified detector geometries to identify the underlying physical mechanisms behind the fluence perturbations. The total electron fluence in the Farmer chamber varies up to 1.24% and 5.12% at 1.5 T, in the parallel and perpendicular orientation, respectively. The interplay between the gyration radius and the Farmer chamber cavity length significantly affects the electron fluence in the perpendicular orientation. For the small-cavity chambers, the maximal variation in total electron fluence is 0.19% in the parallel orientation for the reference field. Significant small-field effects occur in these chambers; the magnetic field reduces the total electron fluence (with respect to the no field case) between 9.86% and 14.50%, depending on the orientation. The magnetic field strongly impacted the solid-state detectors in both field sizes, probably due to the high-Z components and cavity density. The maximal reductions of total electron fluence are 15.06 ± 0.09% (silicon) and 16.00 ± 0.07% (microDiamond). This work provides insights into detector response in magnetic fields by illustrating the interplay between several factors causing dosimetric perturbation effects: (1) chamber and magnetic field orientation, (2) cavity size and shape, (3) extracameral components, (4) air gaps and their asymmetry, (5) electron energy. Low-energy electron trajectories are more susceptible to change in magnetic fields, and are associated with detector response perturbation. Detectors with higher density and high-Z extracameral components exhibit more significant perturbations in the presence of a magnetic field, regardless of field size.

A probabilistic approach for determining Monte Carlo beam source parameters: I. Modeling of a CyberKnife M6 unit.

Objective.During Monte Carlo modeling of external radiotherapy beams, models must be adjusted to reproduce the experimental measurements of the linear accelerator being considered. The aim of this work is to propose a new method for the determination of the energy and spot size of the electron beam incident on the target of a linear accelerator using a maximum likelihood estimation.Approach.For that purpose, the method introduced by Francesconet al(2008Med. Phys.35504-13) is expanded upon in this work. Simulated tissue-phantom ratios and uncorrected output factors using a set of different detector models are compared to experimental measurements. A probabilistic formalism is developed and a complete uncertainty budget, which includes a detailed simulation of positioning errors, is evaluated. The method is applied to a CyberKnife M6 unit using four detectors (PTW 60012, PTW 60019, Exradin A1SL and IBA CC04), with simulations being performed using the EGSnrc suite.Main results.The likelihood distributions of the electron beam energy and spot size are evaluated, leading toEˆ=7.42±0.17MeVandFˆ=2.15±0.06mm. Using these results and a 95% confidence region, simulations reproduce measurements in 13 out of the 14 considered setups.Significance.The proposed method allows an accurate beam parameter optimization and uncertainty evaluation during the Monte Carlo modeling of a radiotherapy unit.

A probabilistic approach for determining Monte Carlo beam source parameters: II. Impact of beam modeling uncertainties on dosimetric functions and treatment plans.

Objective.The Monte Carlo method is recognized as a valid approach for the evaluation of dosimetric functions for clinical use. This procedure requires the accurate modeling of the considered linear accelerator. In Part I, we propose a new method to extract the probability density function of the beam model physical parameters. The aim of this work is to evaluate the impact of beam modeling uncertainties on Monte Carlo evaluated dosimetric functions and treatment plans in the context of small fields.Approach.Simulations of output factors, output correction factors, dose profiles, percent-depth doses and treatment plans are performed using the CyberKnife M6 model developed in Part I. The optimized pair of electron beam energy and spot size, and eight additional pairs of beam parameters representing a 95% confidence region are used to propagate the uncertainties associated to the source parameters to the dosimetric functions.Main results.For output factors, the impact of beam modeling uncertainties increases with the reduction of the field size and confidence interval half widths reach 1.8% for the 5 mm collimator. The impact on output correction factors cancels in part, leading to a maximum confidence interval half width of 0.44%. The impact is less significant for percent-depth doses in comparison to dose profiles. For these types of measurement, in absolute terms and in comparison to the reference dose, confidence interval half widths less than or equal to 1.4% are observed. For simulated treatment plans, the impact is more significant for the treatment delivered with a smaller field size with confidence interval half widths reaching 2.5% and 1.4% for the 5 and 20 mm collimators, respectively.Significance.Results confirm that AAPM TG-157's tolerances cannot apply to the field sizes studied. This study provides an insight on the reachable dose calculation accuracy in a clinical setup.

Monte Carlo calculation of detector perturbation and quality correction factors in a 1.5 T magnetic resonance guided radiation therapy small photon beams.

Objective.With future advances in magnetic resonance imaging-guided radiation therapy, small photon beams are expected to be included regularly in clinical treatments. This study provides physical insights on detector dose-response to multiple megavoltage photon beam sizes coupled to magnetic fields and determines optimal orientations for measurements.Approach.Monte Carlo simulations determine small-cavity detector (solid-state: PTW60012 and PTW60019, ionization chambers: PTW31010, PTW31021, and PTW31022) dose-responses in water to an Elekta Unity 7 MV FFF photon beam. Investigations are performed for field widths between 0.25 and 10 cm in four detector axis orientations with respect to the 1.5 T magnetic field and the photon beam. The magnetic field effect on the overall perturbation factor (PMC) accounting for the extracameral components, atomic composition, and density is quantified in each orientation. The density (Pρ) and volume averaging (Pvol) perturbation factors and quality correction factors (kQB,QfB,f) accounting for the magnetic field are also calculated in each orientation.Main results.Results show thatPvolremains the most significant perturbation both with and without magnetic fields. In most cases, the magnetic field effect onPvolis 1% or less. The magnetic field effect onPρis more significant on ionization chambers than on solid-state detectors. This effect increases up to 1.564 ± 0.001 with decreasing field size for chambers. On the contrary, the magnetic field effect on the extracameral perturbation factor is higher on solid-state detectors than on ionization chambers. For chambers, the magnetic field effect onPMCis only significant for field widths <1 cm, while, for solid-state detectors, this effect exhibits different trends with orientation, indicating that the beam incident angle and geometry play a crucial role.Significance.Solid-state detectors' dose-response is strongly affected by the magnetic field in all orientations. The magnetic field impact on ionization chamber response increases with decreasing field size. In general, ionization chambers yieldkQB,QfB,fcloser to unity, especially in orientations where the chamber axis is parallel to the magnetic field.

Traceable reference dosimetry in MRI guided radiotherapy using alanine: calibration and magnetic field correction factors of ionisation chambers.

Magnetic resonance imaging (MRI)-guided radiotherapy (RT) (MRIgRT) falls outside the scope of existing high energy photon therapy dosimetry protocols, because those protocols do not consider the effects of the magnetic field on detector response and on absorbed dose to water. The aim of this study is to evaluate and demonstrate the traceable measurement of absorbed dose in MRIgRT systems using alanine, made possible by the characterisation of alanine sensitivity to magnetic fields reported previously by Billaset al(2020Phys. Med. Biol.65115001), in a way which is compatible with existing standards and calibrations available for conventional RT. In this study, alanine is used to transfer absorbed dose to water to MRIgRT systems from a conventional linac. This offers an alternative route for the traceable measurement of absorbed dose to water, one which is independent of the transfer using ionisation chambers. The alanine dosimetry is analysed in combination with measurements with several Farmer-type chambers, PTW 30013 and IBA FC65-G, at six different centres and two different MRIgRT systems (Elekta Unity™ and ViewRay MRIdian™). The results are analysed in terms of the magnetic field correction factors, and in terms of the absorbed dose calibration coefficients for the chambers, determined at each centre. This approach to reference dosimetry in MRIgRT produces good consistency in the results, across the centres visited, at the level of 0.4% (standard deviation). Farmer-type ionisation chamber magnetic field correction factors were determined directly, by comparing calibrations in some MRIgRT systems with and without the magnetic field ramped up, and indirectly, by comparing calibrations in all the MRIgRT systems with calibrations in a conventional linac. Calibration coefficients in the MRIgRT systems were obtained with a standard uncertainty of 1.1% (Elekta Unity™) and 0.9% (ViewRay MRIdian™), for three different chamber orientations with respect to the magnetic field. The values obtained for the magnetic field correction factor in this investigation are consistent with those presented in the summary by de Pooteret al(2021Phys. Med. Biol.6605TR02), and would tend to support the adoption of a magnetic field correction factor which depends on the chamber type, PTW 30013 or IBA FC65-G.

Potential of a probabilistic framework for target prediction from surrogate respiratory motion during lung radiotherapy.

Purpose.Respiration-induced motion introduces significant positioning uncertainties in radiotherapy treatments for thoracic sites. Accounting for this motion is a non-trivial task commonly addressed with surrogate-based strategies and latency compensating techniques. This study investigates the potential of a new unified probabilistic framework to predict both future target motion in real-time from a surrogate signal and associated uncertainty.Method.A Bayesian approach is developed, based on a Kalman filter theory adapted specifically for surrogate measurements. Breathing motions are collected simultaneously from a lung target, two external surrogates (abdominal and thoracic markers) and an internal surrogate (liver structure) for 9 volunteers during 4 min, in which severe breathing changes occur to assess the robustness of the method. A comparison with an artificial non-linear neural network (NN) is performed, although no confidence interval prediction is provided. A static worst-case scenario and a simple static design are investigated.Results.Although the NN can reduce the prediction errors from thoracic surrogate in some cases, the Bayesian framework outperforms in most cases the NN when using the other surrogates: bias on predictions is reduced by 38% and 16% on average when using respectively the liver and the abdomen for the simple scenario, and by respectively 40% and 31% for the worst-case scenario. The standard deviation of residuals is reduced on average by up to 42%. The Bayesian method is also found to be more robust to increasing latencies. The thoracic marker appears to be less reliable to predict the target position, while the liver shows to be a better surrogate. A statistical test confirms the significance of both observations.Conclusion.The proposed framework predicts both the future target position and the associated uncertainty, which can be valuably used to further assist motion management decisions. Further investigation is required to improve the predictions by using an adaptive version of the proposed framework.

Reference dosimetry of modulated and dynamic photon beams.

In the late 1980s, a new technique was proposed that would revolutionize radiotherapy. Now referred to as intensity-modulated radiotherapy, it is at the core of state-of-the-art photon beam delivery techniques, such as helical tomotherapy and volumetric modulated arc therapy. Despite over two decades of clinical application, there are still no established guidelines on the calibration of dynamic modulated photon beams. In 2008, the IAEA-AAPM work group on nonstandard photon beam dosimetry published a formalism to support the development of a new generation of protocols applicable to nonstandard beam reference dosimetry (Alfonso et al 2008 Med. Phys. 35 5179-86). The recent IAEA Code of Practice TRS-483 was published as a result of this initiative and addresses exclusively small static beams. But the plan-class specific reference calibration route proposed by Alfonso et al (2008 Med. Phys. 35 5179-86) is a change of paradigm that is yet to be implemented in radiotherapy clinics. The main goals of this paper are to provide a literature review on the dosimetry of nonstandard photon beams, including dynamic deliveries, and to discuss anticipated benefits and challenges in a future implementation of the IAEA-AAPM formalism on dynamic photon beams.

Electron density and effective atomic number estimation in a maximum a posteriori framework for dual-energy computed tomography.

PURPOSE: The stoichiometric calibration method for dual-energy CT (DECT) proposed by Bourque et al. (Phys Med Biol. 59:2059; 2014), which provides estimators of the electron density and the effective atomic number, is adapted to a maximum a posteriori (MAP) framework to increase the model's robustness to noise and biases in CT data, specifically for human tissues. Robust physical parameter estimation from noisy DECT scans is required to maximize the precision of quantities used for radiotherapy treatment planning such as the proton stopping power (SPR). METHODS: Estimation of electron density and effective atomic number is performed by constraining their variation to the natural range of values expected for human tissues, while maximizing attenuation data fidelity. The MAP framework is first compared against the original method using theoretical CT numbers with Gaussian noise. The quantitative accuracy of the MAP framework is then validated experimentally on the Gammex 467 phantom. Then, using two clinical datasets, the advantages of the approach are experimentally evaluated, qualitatively, and quantitatively. RESULTS: The theoretical study shows that the root-mean-square error on the electron density, the effective atomic number and the SPR are, respectively, reduced from 2.3 to 1.5, 5.7 to 3.2 and 2.8 to 1.7% with the adapted framework, when analyzing soft tissues and bone together. The experimental validation study shows that the standard deviation in Gammex inserts can be reduced, on average, by factors of 1.4 (electron density), 2.7 (effective atomic number), and 1.9 (SPR), while the quantitative accuracy of the three physical parameters is preserved, on average. Evaluation on clinical datasets show apparent noise reduction in maps of all estimated physical quantities, and suggests that the MAP framework has increased robustness to beam hardening and photon starvation artifacts. Mean values for the electron density, the effective atomic number, and the SPR averaged in four uniform regions of interest (brain, muscle, adipose, and cranium), respectively, differ by 0.7, 1.8, and 0.9% between both frameworks. The standard deviation in the same regions of interest is also reduced, on average, by factors of 1.8, 6.6, and 3.2 with the MAP framework. Differences in mean value and standard deviations are statistically significant. CONCLUSION: Theoretical and experimental results suggest that the MAP framework produces more accurate and precise estimates of the electron density and SPR. Thus, the present approach limits the propagation of noise in DECT attenuation data to radiotherapy-related parameters maps such as the SPR and the electron density. Using a MAP framework with DECT for radiotherapy treatment planning can help maximizing the precision of dose calculation. The method also provides more precise estimates of the effective atomic number. The MAP methodology is presented in a general way such that it can be adapted to any DECT image-based tissue characterization method.

Quantitative imaging performance of MARS spectral photon-counting CT for radiotherapy.

PURPOSE: To evaluate the quantitative imaging performance of a spectral photon-counting computed tomography (SPCCT) scanner for radiotherapy applications. An experimental comparison of the quantitative performance of a Siemens dual-energy CT (DECT) and a MARS SPCCT scanner is performed to estimate physical properties relevant to radiotherapy of human substitute materials and contrast agent solutions. In human substitute materials, the accuracy of quantities relevant to photon therapy, proton therapy, and Monte-Carlo simulations, such as the electron density, proton stopping power, and elemental composition is evaluated. For contrast agent solutions, the accuracy of the contrast agent concentrations and the virtual non-contrast (VNC) electron density is evaluated. METHODS: Human tissue substitute phantoms (Gammex 467 and 472) as well as diluted solutions of contrast agents (iodine and gadolinium based) are scanned with two commercial systems: a Siemens dual-source CT (SOMATOM Definition Flash, Siemens Healthineers, Forchheim, Germany) and a MARS spectral photon-counting micro-CT (MARS V5.2, MARS Bioimaging Ltd., Christchurch, New Zealand). Material decomposition is performed in a maximum a posteriori framework with an optimized material basis tailored to characterize either human substitute materials or contrast agents in the context of experimental multi-energy CT data. RESULTS: The root-mean-square error (RMSE) of the electron density calculated over all Gammex inserts is reduced from 1.09 to 0.89% when going from DECT to SPCCT. For the proton stopping power, the RMSE is reduced from 1.92 to 0.89%. Elemental mass fractions of hydrogen, carbon, nitrogen, oxygen, and calcium are more accurately estimated with the MARS scanner. The RMSE on the iodine-based contrast agents concentration is reduced from 0.27 to 0.12 mg/mL with SPCCT, and the VNC electron density from 0.40 to 0.22%. CONCLUSION: In the present phantom study, a MARS photon-counting scanner provides superior accuracy compared to a Siemens SOMATOM Definition Flash DECT scanner to quantify physical parameters relevant to radiotherapy. This work experimentally demonstrates the benefits of using more energies to characterize human tissue equivalent materials. This highlights the potential of SPCCT for particle therapy, where more accurate tissue characterization is needed, as well as for Monte-Carlo based planning, which requires accurate elemental mass fractions.

Parametrization of multi-energy CT projection data with eigentissue decomposition.

The purpose of this work is, firstly, to propose an optimized parametrization of the attenuation coefficient to describe human tissues in the context of projection-based material characterization with multi-energy CT. The approach is based on eigentissue decomposition (ETD). Secondly, to evaluate its benefits in terms of accuracy and precision of radiotherapy-related parameters against established parametrizations. The attenuation coefficient is parametrized as a linear combination of virtual materials, eigentissues, obtained by performing principal component analysis on a set of reference tissues in order to optimally represent human tissue composition. Two implementations of ETD are compared with other pre-reconstruction formalisms established for dual-energy and photon-counting CT in a simulation framework. The first implementation uses a single set of eigentissues to describe all human tissues, while the second uses different sets of eigentissues to characterize soft tissues and bones, and includes a post-reconstruction classification step. The simulation framework evaluates the reconstruction accuracy of various radiotherapy-related quantities over a range of 71 human tissues for various noise levels. Compared to conventional parametrizations, the first implementation of ETD reduces the mean error and root-mean-square error (RMSE) in two radiotherapy-related quantities (the proton stopping power and the mass energy absorption coefficient of 21 keV photons from 103Pd seeds used in brachytherapy) for all noise levels and modalities investigated. This illustrates that a decomposition basis selected with principal component analysis is superior to an arbitrary pair of materials to describe human tissues. The mean error on radiotherapy-related parameters can be further reduced with the classification-based approach. In the context of pre-reconstruction material characterization with multi-energy CT, parametrizing the attenuation coefficient with eigentissues provides a more accurate and precise evaluation of human tissues properties for radiotherapy. Accurate quantification can thus be achieved without the need to parametrize tissues using unphysical parameters, such as the energy-dependent effective atomic number.

Alanine dosimetry in strong magnetic fields: use as a transfer standard in MRI-guided radiotherapy.

Reference dosimetry in the presence of a strong magnetic field is challenging. Ionisation chambers have shown to be strongly affected by magnetic fields. There is a need for robust and stable detectors in MRI-guided radiotherapy (MRIgRT). This study investigates the behaviour of the alanine dosimeter in magnetic fields and assesses its suitability to act as a reference detector in MRIgRT. Alanine pellets were loaded in a waterproof holder, placed in an electromagnet and irradiated by 60Co and 6 MV and 8 MV linac beams over a range of magnetic flux densities. Monte Carlo simulations were performed to calculate the absorbed dose, to water and to alanine, with and without magnetic fields. Combining measurements with simulations, the effect of magnetic fields on alanine response was quantified and a correction factor for the presence of magnetic fields on alanine was determined. This study finds that the response of alanine to ionising radiation is modified when the irradiation is in the presence of a magnetic field. The effect is energy independent and may increase the alanine/electron paramagnetic resonance (EPR) signal by 0.2% at 0.35 T and 0.7% at 1.5 T. In alanine dosimetry for MRIgRT, this effect, if left uncorrected, would lead to an overestimate of dose. Accordingly, a correction factor, [Formula: see text], is defined. Values are obtained for this correction as a function of magnetic flux density, with a standard uncertainty which depends on the magnetic field and is 0.6% or less. The strong magnetic field has a measurable effect on alanine dosimetry. For alanine which is used to measure absorbed dose to water in a strong magnetic field, but which has been calibrated in the absence of a magnetic field, a small correction to the reported dose is required. With the inclusion of this correction, alanine/EPR is a suitable reference dosimeter for measurements in MRIgRT.

Influence of intravenous contrast agent on dose calculation in proton therapy using dual energy CT.

The purpose of this study is to evaluate the effect of an intravenous (IV) contrast agent on proton therapy dose calculation using dual-energy computed tomography (DECT). Two DECT methods are considered. The first one, [Formula: see text], attempts to accurately predict the proton stopping powers relative to water (SPR) of contrast enhanced (CE) DECT images, while the second generates a virtual non-contrast (VNC) volume that can be processed as a native non-contrast (NC) one. Both methods are compared against single-energy computed tomography (SECT). The accuracy of SPR predicted for different concentrations of IV contrast diluted in water is first evaluated using simulated data. Results then are validated in an experimental set-up comparing SPR predictions for both NC and CE images to measurements made with a multi-layer ionisation chamber (MLIC). Finally, the impact of IV contrast on dose calculation using both SECT and DECT is evaluated for one liver and one head and neck patient. Using simulated data, DECT is shown to be less sensitive to the presence of IV contrast than SECT, although the performance of the [Formula: see text] method is sensitive to the level of beam hardening considered. For different concentrations of IV contrast diluted in water, experimental MLIC measurement of SPR agrees with DECT predictions within 3% while SECT introduce errors above 20%. This error in the SPR value results in a range error of up to 3.2 mm (2.6%) for proton beams calculated on SECT CE patient images. The error is reduced below 1 mm using DECT with the [Formula: see text] and VNC methods. Globally, it is observed that the influence of IV contrast on proton therapy dose calculation is mitigated using DECT over SECT. In patient anatomies, the VNC approach provides the best agreement with the reference dose distribution.

The potential of photon-counting CT for quantitative contrast-enhanced imaging in radiotherapy.

The aim of this study is to use a simulation environment to evaluate the potential of using photon-counting CT (PCCT) against dual-energy CT (DECT) in the context of quantitative contrast-enhanced CT for radiotherapy. An adaptation of Bayesian eigentissue decomposition by Lalonde et al (2017 Med. Phys. 44 5293-302) that incorporates the estimation of contrast agent fractions and virtual non-contrast (VNC) parameters is proposed, and its performance is validated against conventional maximum likelihood material decomposition methods for single and multiple contrast agents. PCCT and DECT are compared using two simulation frameworks: one including ideal CT numbers with image-based Gaussian noise and another defined as a virtual patient with projection-based Poisson noise and beam hardening artifacts, with both scenarios considering spectral distortion for PCCT. The modalities are compared for their accuracy in estimating four key physical parameters: (1) the contrast agent fraction, as well as VNC parameters relevant to radiotherapy such as the (2) electron density, (3) proton stopping power and (4) photon linear attenuation coefficient. Considering both simulation frameworks, a reduction of root mean square (RMS) errors with PCCT is noted for all physical parameters evaluated, with the exception of the error on the contrast agent fraction being about constant through modalities in the virtual patient. Notably, for the virtual patient, RMS errors on VNC electron density and stopping power are respectively reduced from 2.0% to 1.4% and 2.7% to 1.4% when going from DECT to PCCT with four energy bins. The increase in accuracy is comparable to the differences between contrast-enhanced and non-contrast DECT. This study suggests that in a realistic simulation environment, the overall accuracy of radiotherapy-related parameters can be increased when using PCCT with four energy bins instead of DECT. This confirms the potential of PCCT to provide robust and quantitative tissue parameters for contrast-enhanced CT required in radiotherapy applications.

The effect of magnetic field strength on the response of Gafchromic EBT-3 film.

With the advent of MRI-guided radiotherapy, the suitability of commercially available radiation dose detectors needs to be assessed. The aim of this study was to investigate the effect of the magnetic field (B-field) on the response of the Gafchromic EBT-3 films. Moreover, as an independent study, we contribute to clarifying the inconsistency of the results of recent published studies, on the effect of B-field on the sensitivity of Gafchromic films. A 60Co beam was used to irradiate film samples in an electromagnet. An in-house PMMA phantom was designed to fit in the 5 cm gap between the two poles of the magnet. The phantom consists of two symmetrical plates where a film can be inserted. The absorbed dose rate of the 60Co beam for zero B-field was measured using alanine pellets in a Farmer-type holder. A 12-point response curve was created, representing [Formula: see text] as a function of dose, for each of five different B-field strengths (0 T to 2 T). This study finds that there is at most a small effect of the magnetic field on the response of EBT-3 film. In terms of netOD (red channel) the change in response varied from ‒0.0011 at 0.5 T to 0.0045 at 2.0 T, with a standard uncertainty of 0.0030. If uncorrected, this would lead to an error in film-measured dose, for the red channel, of 2.4% at 2 T, with a standard uncertainty on dose of 1.4%. Results are also presented for B-field strengths of 0.5 T, 1 T and 1.5 T, which are all zero within the measurement uncertainty. Comparison between other studies is also presented. Considering the small change on dose determined with EBT-3 when irradiated under the presence of B-field and taking into account the overall uncertainty in dosimetry using EBT-3 film achieved in this work, EBT-3 is assessed to be a suitable detector for relative and absolute dosimetry, with appropriate corrections, in MRI-guided radiotherapy. The results of the current work also elucidate the inconsistency on the reports from previous studies and demonstrate the necessity of similar investigations by independent teams, especially if the existing results may be in conflict.

The influence of nuclear interactions on ionization chamber perturbation factors in proton beams: FLUKA simulations supported by a Fano test.

PURPOSE: In all recent protocols for the reference dosimetry of clinical proton beams, ionization chamber perturbation factors are assumed to be unity. In this work, such factors were computed using the FLUKA Monte Carlo code for three ionization chamber types, with particular attention to the influence of nuclear interactions. METHODS: The accuracy of the transport algorithms implemented in FLUKA was first evaluated by performing a Fano cavity test. Ionization chamber perturbation factors were computed for the PTW-34001 Roos® and the PTW-34070 and PTW-34073 Bragg peak® chambers for proton beams of 60-250 MeV using the same transport parameters that were needed to pass the Fano test. RESULTS: FLUKA was found to pass the Fano test within 0.15%. Ionization chamber simulation results show that the presence of the air cavity and the wall results in dose perturbations of the order of 0.6% and 0.8%, respectively. The perturbation factors are shown to be energy dependent and nuclear interactions must be taken into account for accurate calculation of the ionization chamber's response. CONCLUSION: Ionization chamber perturbations can amount to 1% in high-energy proton beams and therefore need to be considered in dosimetry procedures.