A comparison of relative proton stopping power measurements across patient size using dual- and single-energy CT

Prediction of proton stopping power ratios using dual-energy CT basis material decomposition

BACKGROUND

Proton radiotherapy treatment plans are currently restricted by the range uncertainties originating from the stopping power ratio (SPR) prediction based on single-energy computed tomography (SECT). Various studies have shown that multi-energy CT (MECT) can reduce the range uncertainties due to medical implant materials and age-related variations in tissue composition. None of these has directly applied the basis material density (MD) images produced by projection-based MECT systems for SPR prediction.

PURPOSE

To present and evaluate a novel proton SPR prediction method based on MD images from dual-energy CT (DECT), which could reduce the range uncertainties currently associated with proton radiotherapy.

METHODS

A theoretical basis material decomposition into water and iodine material densities was performed for various pediatric and adult human reference tissues, as well as other non-tissue materials, by minimizing the root-mean-square relative attenuation error in the energy interval from 40 to 140 keV. A model (here called MD-SPR) mapping predicted MDs to theoretically calculated reference SPRs was created with locally weighted scatterplot smoothing (LOWESS) data-fitting. The goodness of fit of the MD-SPR model was evaluated for the included reference tissues. MD images of two electron density phantoms, combined to form a head- and an abdomen-sized phantom setup, were acquired with a clinical projection-based fast-kV switching DECT scanner. The MD images were compared to the theoretically predicted MDs of the tissue surrogates and other non-tissue materials in the phantoms, as well as used for input to the MD-SPR model for generation of SPR images. The SPR images were subsequently compared to theoretical reference SPRs of the materials in the phantoms, as well as to SPR images from a commercial algorithm (DirectSPR, Siemens Healthineers, Forchheim, Germany) using image-based consecutive scan DECT for the same phantom setups.

RESULTS

The predicted SPRs of the tissue surrogates were similar for MD-SPR and DirectSPR, where the adipose and bone tissue surrogates were within 1% difference to the reference SPRs, while other non-adipose soft tissue surrogates (breast, brain, liver, muscle) were all underestimated by between -0.7% and -1.8%. The SPRs of the non-tissue materials (polymethyl methacrylate (PMMA), polyether ether ketone (PEEK), graphite and Teflon) were within 2.8% for MD-SPR images, compared to 6.8% for DirectSPR.

CONCLUSIONS

The MD-SPR model performed similar compared to other published methods for the human reference tissues. The SPR prediction for tissue surrogates was similar to DirectSPR and showed potential to improve SPR prediction for non-tissue materials.

Extension of the open-source TIGRE toolbox for proton imaging

Proton irradiation is a well-established method to treat deep-seated tumors in radio oncology. Usually, an X-ray computed tomography (CT) scan is used for treatment planning. Since proton therapy is based on the precise knowledge of the stopping power describing the energy loss of protons in the patient tissues, the Hounsfield units of the planning CT have to be converted. This conversion introduces range errors in the treatment plan, which could be reduced, if the stopping power values were extracted directly from an image obtained using protons instead of X-rays. Since protons are affected by multiple Coulomb scattering, reconstruction of the 3D stopping power map results in limited image quality if the curved proton path is not considered. This work presents a substantial code extension of the open-source toolbox TIGRE for proton CT (pCT) image reconstruction based on proton radiographs including a curved proton path estimate. The code extension and the reconstruction algorithms are GPU-based, allowing to achieve reconstruction results within minutes. The performance of the pCT code extension was tested with Monte Carlo simulated data using three phantoms (Catphan® high resolution and sensitometry modules and a CIRS patient phantom). In the simulations, ideal and non-ideal conditions for a pCT setup were assumed. The obtained mean absolute percentage error was found to be below 1% and up to 8 lp/cm could be resolved using an idealized setup. These findings demonstrate that the presented code extension to the TIGRE toolbox offers the possibility for other research groups to use a fast and accurate open-source pCT reconstruction.

Consensus guide on CT-based prediction of stopping-power ratio using a Hounsfield look-up table for proton therapy

BACKGROUND AND PURPOSE

Studies have shown large variations in stopping-power ratio (SPR) prediction from computed tomography (CT) across European proton centres. To standardise this process, a step-by-step guide on specifying a Hounsfield look-up table (HLUT) is presented here.

MATERIALS AND METHODS

The HLUT specification process is divided into six steps: Phantom setup, CT acquisition, CT number extraction, SPR determination, HLUT specification, and HLUT validation. Appropriate CT phantoms have a head- and body-sized part, with tissue-equivalent inserts in regard to X-ray and proton interactions. CT numbers are extracted from a region-of-interest covering the inner 70% of each insert in-plane and several axial CT slices in scan direction. For optimal HLUT specification, the SPR of phantom inserts is measured in a proton beam and the SPR of tabulated human tissues is computed stoichiometrically at 100 MeV. Including both phantom inserts and tabulated human tissues increases HLUT stability. Piecewise linear regressions are performed between CT numbers and SPRs for four tissue groups (lung, adipose, soft tissue, and bone) and then connected with straight lines. Finally, a thorough but simple validation is performed.

RESULTS

The best practices and individual challenges are explained comprehensively for each step. A well-defined strategy for specifying the connection points between the individual line segments of the HLUT is presented. The guide was tested exemplarily on three CT scanners from different vendors, proving its feasibility.

CONCLUSION

The presented step-by-step guide for CT-based HLUT specification with recommendations and examples can contribute to reduce inter-centre variations in SPR prediction.

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 (ρ_s) within patients. Currently, theρ_sdistribution 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 toρ_susing a Hounsfield look-up table (HLUT), also known as the CT calibration curve. HU andρ_sshare 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) forρ_sprediction has been shown to be effective in reducing the uncertainty inρ_sestimation 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 ofρ_sestimation. 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 forρ_sestimation 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 beyondρ_sestimation.

Impact of beam-hardening corrections on proton relative stopping power estimates from single- and dual-energy CT

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield units (HU) to proton relative stopping power (RSP). This uncertainty is heightened in the presence of X-ray beam-hardening artifact (BHA), which has two manifestations: cupping and streaking, especially in and near bone tissue. This uncertainty can affect the accuracy of proton RSP calculation for treatment planning in proton radiotherapy. Dual-energy CT (DECT) and iterative beam-hardening correction (iBHC) both show promise in mitigating CT BHA. This present work attempts to analyze the relative robustness of iBHC and DECT techniques on both manifestations of BHA. The stoichiometric method for HU to RSP conversion was used for single-energy CT (SECT) and DECT-based monochromatic techniques using a tissue substitute phantom. Cupping BHA was simulated by measuring the HU of a bone substitute plug in wax/3D-printed phantoms of increasing size. Streaking BHA was simulated by placing a solid water plug between two bone plugs in a wax phantom. Finally, the effect of varying calibration phantom size on RSP was calculated in an anthropomorphic head phantom. The RSP decreased -0.002 cm^-1 as phantom size increased for SECT but remained largely constant when iBHC applied or with DECT techniques. The RSP varied a maximum of 2.60% in the presence of streaking BHA in SECT but was reduced to 1.40% with iBHC. For DECT techniques, the maximum difference was 2.40%, reduced to 0.6% with iBHC. Comparing calibration phantoms of 20- and 33-cm diameter, maximum voxel differences of 5 mm in the water-equivalent thickness were observed in the skull but reduced to 1.3 mm with iBHC. The DECT techniques excelled in mitigating cupping BHA, but streaking BHA still could be observed. The use of iBHC reduced RSP variation with BHA in both SECT and DECT techniques.

Dosimetric Advantages of Silicone-Filled Vaginal Spacers in Pediatric Proton Therapy

We introduce a custom-made silicone-filled vaginal spacer for use during treatment of female patients receiving pelvic proton radiation therapy. Commercially available vaginal dilators can be purchased as hollow objects; when filled with a media, they can act as a beam stopper and/or tissue spacer while pushing uninvolved vaginal wall away from a high-dose region. Dosimetric advantages of these specifically constructed silicone-filled vaginal spacers were investigated when compared to the unaltered commercially available product or no vaginal spacer in pediatric proton therapy.

Dental management in head and neck cancers: from intensity-modulated radiotherapy with photons to proton therapy

INTRODUCTION

Despite reduction of xerostomia with intensity-modulated compared to conformal X-ray radiotherapy, radiation-induced dental complications continue to occur. Proton therapy is promising in head and neck cancers to further reduce radiation-induced side-effects, but the optimal dental management has not been defined.

MATERIAL AND METHODS

Dental management before proton therapy was assessed compared to intensity-modulated radiotherapy based on a bicentric experience, a literature review and illustrative cases.

RESULTS

Preserved teeth frequently contain metallic dental restorations (amalgams, crowns, implants). Metals blur CT images, introducing errors in tumour and organ contour during radiotherapy planning. Due to their physical interactions with matter, protons are more sensitive than photons to tissue composition. The composition of restorative materials is rarely documented during radiotherapy planning, introducing dose errors. Manual artefact recontouring, metal artefact-reduction CT algorithms, dual or multi-energy CT and appropriate dose calculation algorithms insufficiently compensate for contour and dose errors during proton therapy. Physical uncertainties may be associated with lower tumour control probability and more side-effects after proton therapy. Metal-induced errors should be quantified and removal of metal restorations discussed on a case by case basis between dental care specialists, radiation oncologists and physicists. Metallic amalgams can be replaced with water-equivalent materials and crowns temporarily removed depending on rehabilitation potential, dental condition and cost. Implants might contraindicate proton therapy if they are in the proton beam path.

CONCLUSION

Metallic restorations may more severely affect proton than photon radiotherapy quality. Personalized dental care prior to proton therapy requires multidisciplinary assessment of metal-induced errors before choice of conservation/removal of dental metals and optimal radiotherapy.

Physical density estimations of single- and dual-energy CT using material-based forward projection algorithm: a simulation study

OBJECTIVES

This study aims to evaluate the accuracy of physical density prediction in single-energy CT (SECT) and dual-energy CT (DECT) by adapting a fully simulation-based method using a material-based forward projection algorithm (MBFPA).

METHODS

We used biological tissues referenced in ICRU Report 44 and tissue substitutes to prepare three different types of phantoms for calibrating the Hounsfield unit (HU)-to-density curves. Sinograms were first virtually generated by the MBFPA with four representative energy spectra (i.e. 80 kVp, 100 kVp, 120 kVp, and 6 MVp) and then reconstructed to form realistic CT images by adding statistical noise. The HU-to-density curves in each spectrum and their pairwise combinations were derived from the CT images. The accuracy of these curves was validated using the ICRP110 human phantoms.

RESULTS

The relative mean square errors (RMSEs) of the physical density by the HU-to-density curves calibrated with kV SECT nearly presented no phantom size dependence. The kV-kV DECT calibrated curves were also comparable with those from the kV SECT. The phantom size effect became notable when the MV X-ray beams were employed for both SECT and DECT due to beam-hardening effects. The RMSEs were decreased using the biological tissue phantom.

CONCLUSION

Simulation-based density prediction can be useful in the theoretical analysis of SECT and DECT calibrations. The results of this study indicated that the accuracy of SECT calibration is comparable with that of DECT using biological tissues. The size and shape of the calibration phantom could affect the accuracy, especially for MV CT calibrations.

ADVANCES IN KNOWLEDGE

The present study is based on a full simulation environment, which accommodates various situations such as SECT, kV-kV DECT, and even kV-MV DECT. In this paper, we presented the advances pertaining to the accuracy of the physical density prediction when applied to SECT and DECT in the MV X-ray energy range. To the best of our knowledge, this study is the first to validate the physical density estimation both in SECT and DECT using human-type phantoms.

Accuracy of proton stopping power estimation of silicone breast implants with single and dual-energy CT calibration techniques

A major contributing factor to proton range uncertainty is the conversion of computed tomography (CT) Hounsfield Units (HU) to proton relative stopping power (RSP). This uncertainty is elevated with implanted devices, such as silicone breast implants when computed with single energy CT (SECT). In recent years, manufacturers have introduced implants with variations in gel cohesivity. Deriving the RSP for these implants from dual-energy CT (DECT) can result in a marked reduction of the error associated with SECT. In this study, we investigate the validity of DECT calibration of HU to RSP on silicone breast implants of varying cohesivity levels. A DECT capable scanner was calibrated using the stoichiometric method of Bourque et al for SECT and DECT using a tissue substitute phantom. Three silicone breast implants of increasing gel cohesivity were measured in a proton beam of clinical energy to determine ground-truth RSP and water equivalent thickness (WET). These were compared to SECT-derived RSP at three CT spectrum energies and DECT with two energy pairs (80/140 kVp and 100/140 kVp) as obtained from scans with and without an anthropomorphic phantom. The RSP derived from parameters estimates from CT vendor-specific software (syngo.via) was compared. The WET estimates from SECT deviated from MLIC ground truth approximately +11%-19%, which would result in overpenetration if used clinically. Both the Bourque calibration and syngo.via WET estimates from DECT yielded error ≤0.5% from ground truth; no significant difference was found between models of varying gel cohesivity levels. WET estimates without the anthropomorphic phantom were significantly different than ground truth for the Bourque calibration. From these results, gel cohesivity had no effect on proton RSP. User-generated DECT calibration can yield comparably accurate RSP estimates for silicone breast implants to vendor software methods. However, care must be taken to account for beam hardening effects.

Accuracy and reproducibility of effective atomic number and electron density measurements from sequential dual energy CT

PURPOSE

This study assesses the accuracy of effective atomic number (Z_eff ) and electron density measurements acquired from dual energy CT and characterizes the response to clinically relevant variables representative of challenges in patient imaging, including: phantom size, material position within the phantom, variation over time, off-center positioning, and large cone beam angle.

METHODS

The Gammex Multi-Energy CT head and body phantoms were used to measure Z_eff and electron density from 35 rod inserts that mimic tissues and varying concentrations of iodine and calcium. Scans were performed on a Canon Aquilion ONE Genesis CT scanner over a period of 6 months using default dual energy protocols appropriate for each phantom size. Theoretical Z_eff and electron density values were calculated using data provided by the phantom manufacturer and compared to the measurements. Sources of variance were separated and quantified to identify the influences of random photon statistics, ROI placement, and variation over time. A subset of measurements were repeated with the phantom shifted in the vertical and horizontal directions, and over all slices in the volumetric scan.

RESULTS

All measurements showed strong correlation (r > 0.98) with their corresponding theoretical values; however, the system did demonstrate a bias of -0.58 atomic units in the body phantom and 0.28 atomic units in the head phantom for Z_eff measurements. The mean absolute percent error (MAPE) was 6.3% for the body phantom and 3.2% for the head phantom. Electron density measurements of the body and head phantoms gave MAPE values of 4.6% and 1.0%, respectively. Z_eff and electron density measurements significantly varied within the solid water background, showing a positional dependence within the phantom that dominated the total standard deviation in measurements. Z_eff values dropped by 0.2 atomic units when the phantom was off-center; electron density measurements were less affected by phantom position. Along the z-axis, the accuracy drops off markedly at more than 50-60 mm from the central slice.

CONCLUSION

The Canon dual energy system offers an accurate way of measuring the Z_eff and electron density of clinically relevant materials. Accuracy could be improved further by calibration to remove bias, careful attention to centering within the FOV, and avoiding measurements at the edges of the cone beam.

First application of the GPU-based software framework TIGRE for proton CT image reconstruction

In proton therapy, the knowledge of the proton stopping power, i.e. the energy deposition per unit length within human tissue, is essential for accurate treatment planning. One suitable method to directly measure the stopping power is proton computed tomography (pCT). Due to the proton interaction mechanisms in matter, pCT image reconstruction faces some challenges: the unique path of each proton has to be considered separately in the reconstruction process adding complexity to the reconstruction problem. This study shows that the GPU-based open-source software toolkit TIGRE, which was initially intended for X-ray CT reconstruction, can be applied to the pCT image reconstruction problem using a straight line approach for the proton path. This simplified approach allows for reconstructions within seconds. To validate the applicability of TIGRE to pCT, several Monte Carlo simulations modeling a pCT setup with two Catphan® modules as phantoms were performed. Ordered-Subset Simultaneous Algebraic Reconstruction Technique (OS-SART) and Adaptive-Steepest-Descent Projection Onto Convex Sets (ASD-POCS) were used for image reconstruction. Since the accuracy of the approach is limited by the straight line approximation of the proton path, requirements for further improvement of TIGRE for pCT are addressed.

Spectral CT quantification stability and accuracy for pediatric patients: A phantom study

BACKGROUND

Spectral computed tomography (spectral CT) provides access to clinically relevant measures of endogenous and exogenous materials in patients. For pediatric patients, current spectral CT applications include lesion characterization, quantitative vascular imaging, assessments of tumor response to treatment, and more.

OBJECTIVE

The aim of this study is a comprehensive investigation of the accuracy and stability of spectral quantifications from a spectral detector-based CT system with respect to different patient sizes and radiation dose levels relevant for the pediatric population.

MATERIALS AND METHODS

A spectral CT phantom with tissue-mimicking materials and iodine concentrations relevant for pediatric imaging was scanned on a spectral detector CT system using a standard pediatric abdominal protocol at 100%, 67%, 33% and 10% of the nominal radiation dose level. Different pediatric patient sizes were simulated using supplemental 3D-printed extension rings. Virtual mono-energetic, iodine density, effective atomic number, and electron density results were analyzed for stability with respect to radiation dose and patient size.

RESULTS

Compared to conventional CT imaging, a pronounced improvement in the stability of attenuation measurements across patient size was observed when using virtual mono-energetic images. Iodine densities were within 0.1 mg/ml, effective atomic numbers were within 0.26 atomic numbers and electron density quantifications were within ±1.0% of their respective nominal values. Relative to the nominal dose clinical protocol, differences in attenuation of all tissue-mimicking materials were maintained below 1.6 HU for a 33% dose reduction, below 2.7 HU for a 67% dose reduction and below 3.7 HU for a 90% dose reduction, for all virtual mono-energetic energies equal to or greater than 50 keV. Iodine, and effective atomic number quantifications were stable to within 0.1 mg/ml and 0.06 atomic numbers, respectively, across all measured dose levels.

CONCLUSION

Spectral CT provides accurate and stable material quantification with respect to radiation dose reduction (up to 90%) and differing pediatric patient size. The observed consistency is an important step towards quantitative pediatric imaging at low radiation exposure levels.

Status and innovations in pre-treatment CT imaging for proton therapy

Pre-treatment CT imaging is a topic of growing importance in particle therapy. Improvements in the accuracy of stopping-power prediction are demanded to allow for a dose conformality that is not inferior to state-of-the-art image-guided photon therapy. Although range uncertainty has been kept practically constant over the last decades, recent technological and methodological developments, like the clinical application of dual-energy CT, have been introduced or arise at least on the horizon to improve the accuracy and precision of range prediction. This review gives an overview of the current status, summarizes the innovations in dual-energy CT and its potential impact on the field as well as potential alternative technologies for stopping-power prediction.

Managing treatment-related uncertainties in proton beam radiotherapy for gastrointestinal cancers

In recent years, there has been rapid adaption of proton beam radiotherapy (RT) for treatment of various malignancies in the gastrointestinal (GI) tract, with increasing number of institutions implementing intensity modulated proton therapy (IMPT). We review the progress and existing literature regarding the technical aspects of RT planning for IMPT, and the existing tools that can help with the management of uncertainties which may impact the daily delivery of proton therapy. We provide an in-depth discussion regarding range uncertainties, dose calculations, image guidance requirements, organ and body cavity filling consideration, implanted devices and hardware, use of fiducials, breathing motion evaluations and both active and passive motion management methods, interplay effect, general IMPT treatment planning considerations including robustness plan evaluation and optimization, and finally plan monitoring and adaptation. These advances have improved confidence in delivery of IMPT for patients with GI malignancies under various scenarios.

Theoretical and experimental analysis of photon counting detector CT for proton stopping power prediction

PURPOSE

Photon counting detectors (PCDs) are being introduced in advanced x-ray computed tomography (CT) scanners. From a single PCD-CT acquisition, multiple images can be reconstructed, each based on only a part of the original x-ray spectrum. In this study, we investigated whether PCD-CT can be used to estimate stopping power ratios (SPRs) for proton therapy treatment planning, both by comparing to other SPR methods proposed for single energy CT (SECT) and dual energy CT (DECT) as well as to experimental measurements.

METHODS

A previously developed DECT-based SPR estimation method was adapted to PCD-CT data, by adjusting the estimation equations to allow for more energy spectra. The method was calibrated directly on noisy data to increase the robustness toward image noise. The new PCD SPR estimation method was tested in theoretical calculations as well as in an experimental setup, using both four and two energy bin PCD-CT images, and through comparison to two other SPR methods proposed for SECT and DECT. These two methods were also evaluated on PCD-CT images, full spectrum (one-bin) or two-bin images, respectively. In a theoretical framework, we evaluated the effect of patient-specific tissue variations (density and elemental composition) and image noise on the SPR accuracy; the latter effect was assessed by applying three different noise levels (low, medium, and high noise). SPR estimates derived using real PCD-CT images were compared to experimentally measured SPRs in nine organic tissue samples, including fat, muscle, and bone tissues.

RESULTS

For the theoretical calculations, the root-mean-square error (RMSE) of the SPR estimation was 0.1% for the new PCD method using both two and four energy bins, compared to 0.2% and 0.7% for the DECT- and SECT-based method, respectively. The PCD method was found to be very robust toward CT image noise, with a RMSE of 2.7% when high noise was added to the CT numbers. Introducing tissue variations, the RMSE only increased to 0.5%; even when adding high image noise to the changed tissues, the RMSE stayed within 3.1%. In the experimental measurements, the RMSE over the nine tissue samples was 0.8% when using two energy bins, and 1.0% for the four-bin images.

CONCLUSIONS

In all tested cases, the new PCD method produced similar or better results than the SECT- and DECT-based methods, showing an overall improvement of the SPR accuracy. This study thus demonstrated that PCD-CT scans will be a qualified candidate for SPR estimations.

Comparison of single and dual energy CT for stopping power determination in proton therapy of head and neck cancer

Background and purpose

Patients with head and neck (HN) cancer may benefit from proton therapy due to the potential for sparing of normal tissue. For planning of proton therapy, dual-energy CT (DECT) has been shown to provide superior stopping power ratio (SPR) determination in phantom materials and organic tissue samples, compared to single-energy CT (SECT). However, the benefit of DECT in HN cancer patients has not yet been investigated. This study therefore compared DECT- and SECT-based SPR estimation for HN cancer patients.

Materials and methods

Fourteen HN cancer patients were DECT scanned. Eight patients were scanned using a dual source DECT scanner and six were scanned with a conventional SECT scanner by acquiring two consecutive scans. SECT image sets were computed as a weighted summation of the low and high energy DECT image sets. DECT- and SECT-based SPR maps were derived. Water-equivalent path lengths (WEPLs) through the SPR maps were compared in the eight cases with dual source DECT scans. Mean SPR estimates over region-of-interests (ROIs) in the cranium, brain and eyes were analyzed for all patients.

Results

A median WEPL difference of 1.9 mm (1.5%) was found across the eight patients. Statistically significant SPR differences were seen for the ROIs in the brain and eyes, with the SPR estimates based on DECT overall lower than for SECT.

Conclusions

Clinically relevant WEPL and SPR differences were found between DECT and SECT, which could imply that the accuracy of treatment planning for proton therapy would benefit from DECT-based SPR estimation.