Effect of extended field-of-view approaches on the accuracy of stopping power ratio estimation for single-energy computed tomography simulators

BACKGROUND

Extended field-of-view (eFOV) methods have been proposed to generate larger demonstration FOVs for computed tomography (CT) simulators with a limited scanning FOV (sFOV) size in order to ensure accurate dose calculation and patient collision avoidance. Although the efficacy of these strategies has been evaluated for photon applications, the effect of stopping power ratio (SPR) estimation on proton therapy has not been studied. This study investigated the effect of an eFOV approach on the accuracy of SPR to water estimation in homogeneous and heterogeneous phantoms.

MATERIALS AND METHODS

To simulate patient geometries, tissue-equivalent material (TEM) and customized extension phantoms were used. The TEM phantom supported various rod arrangements through predefined holes. Images were reconstructed to three FOV sizes using a commercial eFOV technique. A single-energy CT stoichiometric method was used to generate Hounsfield unit (HU) to SPR (HU-to-SPR) conversion curves for each FOV. To investigate the effect of rod location in the sFOV and eFOV regions, eight TEM rods were placed at off-center distances in the homogeneous phantom and scanned individually. Similarly, 16 TEM rods were placed in the heterogeneous TEM phantom and scanned simultaneously.

RESULTS

The conversion curves derived from the sFOV and eFOV data were identical. The average SPR differences of soft-tissue, bone, and lung materials for rods placed at various off-center locations were 3.3%, 4.8%, and 39.6%, respectively. In the heterogeneous phantom, the difference was within 1.0% in the absence of extension. However, in the presence of extension, the difference increased to 2.8% for all rods, except for lung materials, whose difference was 4.8%.

CONCLUSIONS

When an eFOV method is used, the SPR variation in phantoms considerably increases for all TEM rods, especially for lung TEM rods. This phenomenon may substantially increase the uncertainty of HU-to-SPR conversion. Therefore, image reconstruction with a standard FOV size is recommended.

Validation of an MR-based multimodal method for molecular composition and proton stopping power ratio determination using ex vivo animal tissues and tissue-mimicking phantoms

Objective. Range uncertainty in proton therapy is an important factor limiting clinical effectiveness. Magnetic resonance imaging (MRI) can measure voxel-wise molecular composition and, when combined with kilovoltage CT (kVCT), accurately determine mean ionization potential (Im), electron density, and stopping power ratio (SPR). We aimed to develop a novel MR-based multimodal method to accurately determine SPR and molecular compositions. This method was evaluated in tissue-mimicking andex vivoporcine phantoms, and in a brain radiotherapy patient.Approach. Four tissue-mimicking phantoms with known compositions, two porcine tissue phantoms, and a brain cancer patient were imaged with kVCT and MRI. Three imaging-based values were determined: SPRCM(CT-based Multimodal), SPRMM(MR-based Multimodal), and SPRstoich(stoichiometric calibration). MRI was used to determine two tissue-specific quantities of the Bethe Bloch equation (Im, electron density) to compute SPRCMand SPRMM. Imaging-based SPRs were compared to measurements for phantoms in a proton beam using a multilayer ionization chamber (SPRMLIC).Main results. Root mean square errors relative to SPRMLICwere 0.0104(0.86%), 0.0046(0.45%), and 0.0142(1.31%) for SPRCM, SPRMM, and SPRstoich, respectively. The largest errors were in bony phantoms, while soft tissue and porcine tissue phantoms had <1% errors across all SPR values. Relative to known physical molecular compositions, imaging-determined compositions differed by approximately ≤10%. In the brain case, the largest differences between SPRstoichand SPRMMwere in bone and high lipids/fat tissue. The magnitudes and trends of these differences matched phantom results.Significance. Our MR-based multimodal method determined molecular compositions and SPR in various tissue-mimicking phantoms with high accuracy, as confirmed with proton beam measurements. This method also revealed significant SPR differences compared to stoichiometric kVCT-only calculation in a clinical case, with the largest differences in bone. These findings support that including MRI in proton therapy treatment planning can improve the accuracy of calculated SPR values and reduce range uncertainties.

Dual-energy CT-based stopping power prediction for dental materials in particle therapy

Radiotherapy with protons or light ions can offer accurate and precise treatment delivery. Accurate knowledge of the stopping power ratio (SPR) distribution of the tissues in the patient is crucial for improving dose prediction in patients during planning. However, materials of uncertain stoichiometric composition such as dental implant and restoration materials can substantially impair particle therapy treatment planning due to related SPR prediction uncertainties. This study investigated the impact of using dual-energy computed tomography (DECT) imaging for characterizing and compensating for commonly used dental implant and restoration materials during particle therapy treatment planning. Radiological material parameters of ten common dental materials were determined using two different DECT techniques: sequential acquisition CT (SACT) and dual-layer spectral CT (DLCT). DECT-based direct SPR predictions of dental materials via spectral image data were compared to conventional single-energy CT (SECT)-based SPR predictions obtained via indirect CT-number-to-SPR conversion. DECT techniques were found overall to reduce uncertainty in SPR predictions in dental implant and restoration materials compared to SECT, although DECT methods showed limitations for materials containing elements of a high atomic number. To assess the influence on treatment planning, an anthropomorphic head phantom with a removable tooth containing lithium disilicate as a dental material was used. The results indicated that both DECT techniques predicted similar ranges for beams unobstructed by dental material in the head phantom. When ion beams passed through the lithium disilicate restoration, DLCT-based SPR predictions using a projection-based method showed better agreement with measured reference SPR values (range deviation: 0.2 mm) compared to SECT-based predictions. DECT-based SPR prediction may improve the management of certain non-tissue dental implant and restoration materials and subsequently increase dose prediction accuracy.

Error on the stopping power ratio of ERKODENT's mouthpiece for head and neck carbon ion radiotherapy treatment

The errors on the stopping power ratio (SPR) of mouthpiece samples from ERKODENT were evaluated. Erkoflex and Erkoloc-pro from ERKODENT and samples that combined Erkoflex and Erkoloc-pro were computed tomography (CT)-scanned using head and neck (HN) protocol at the East Japan Heavy Ion Center (EJHIC), and the values were averaged to obtain the CT number. The integral depth dose of the Bragg curve with and without these samples was measured for 292.1, 180.9, and 118.8 MeV/u of the carbon-ion pencil beam using an ionization chamber with concentric electrodes at the horizontal port of the EJHIC. The average value of the water equivalent length (WEL) of each sample was obtained from the difference between the range of the Bragg curve and the thickness of the sample. To calculate the difference between the theoretical and measured values, the theoretical CT number and SPR value of the sample were calculated using the stoichiometric calibration method. Compared with the Hounsfield unit (HU)-SPR calibration curve used at the EJHIC, the SPR error on each measured and theoretical value was calculated. The WEL value of the mouthpiece sample had an error of approximately 3.5% in the HU-SPR calibration curve. From this error, it was evaluated that for a mouthpiece with a thickness of 10 mm, a beam range error of approximately 0.4 mm can occur, and for a mouthpiece with a thickness of 30 mm, a beam range error of approximately 1 mm can occur. For a beam passing through the mouthpiece in HN treatment, it would be practical to consider a mouthpiece margin of 1 mm to avoid beam range errors if ions pass through the mouthpiece.

An evaluation of the use of DirectSPR images for proton planning in the RayStation treatment planning software

An important source of uncertainty in proton therapy treatment planning is the assignment of stopping-power ratio (SPR) from CT data. A commercial product is now available that creates an SPR map directly from dual-energy CT (DECT). This paper investigates the use of this new product in proton treatment planning and compares the results to the current method of assigning SPR based on a single-energy CT (SECT). Two tissue surrogate phantoms were CT scanned using both techniques. The SPRs derived from single-energy CT and by DirectSPR™ were compared to measured values. SECT-based values agreed with measurements within 4% except for low density lung and high density bone, which differed by 13% and 8%, respectively. DirectSPR™ values were within 2% of measured values for all tissues studied. Both methods were also applied to scanned containers of three types of animal tissue, and the expected range of protons of two different energies was calculated in the treatment planning system and compared to the range measured using a multi-layer ion chamber. The average difference between range measurements and calculations based on SPR maps from dual- and single-energy CT, respectively, was 0.1 mm (0.07%) versus 2.2 mm (1.5%). Finally, a phantom was created using a layer of various tissue surrogate plugs on top of a 2D ion chamber array. Dose measurements on this array were compared to predictions using both single- and dual-energy CTs and SPR maps. While standard gamma pass rates for predictions based on DECT-derived SPR maps were slightly higher than those based on single-energy CT, the differences were generally modest for this measurement setup. This study showed that SPR maps created by the commercial product from dual-energy CT can successfully be used in RayStation to generate proton dose distributions and that these predictions agree well with measurements.

Evaluation of treatment planning system accuracy in estimating the stopping-power ratio of immobilization devices for proton therapy

PURPOSE

To assess treatment planning system (TPS) accuracy in estimating the stopping-power ratio (SPR) of immobilization devices commonly used in proton therapy and to evaluate the dosimetric effect of SPR estimation error for a set of clinical treatment plans.

METHODS

Computed tomography scans of selected clinical immobilization devices were acquired. Then, the water-equivalent thickness (WET) and SPR values of these devices based on the scans were estimated in a commercial TPS. The reference SPR of each device was measured using a multilayer ion chamber (MLIC), and the differences between measured and TPS-estimated SPRs were calculated. These findings were utilized to calculate corrected dose distributions of 15 clinical proton plans for three treatment sites: extremity, abdomen, and head-and-neck. The original and corrected dose distributions were compared using a set of target and organs-at-risk (OARs) dose-volume histogram (DVH) parameters.

RESULTS

On average, the TPS-estimated SPR was 19.5% lower (range, -35.1% to 0.2%) than the MLIC-measured SPR. Due to the relatively low density of most immobilization devices used, the WET error was typically <1 mm, but up to 2.2 mm in certain devices. Overriding the SPR of the immobilization devices to the measured values did not result in significant changes in the DVH metrics of targets and most OARs. However, some critical OARs showed noticeable changes of up to 6.7% in maximum dose.

CONCLUSIONS

The TPS tends to underestimate the SPR of selected proton immobilization devices by an average of about 20%, but this does not induce major WET errors because of the low density of the devices. The dosimetric effect of this SPR error was negligible for most treatment sites, although the maximum dose of a few OARs exhibited noticeable variations.

Experimental validation of proton physics models of Geant4 for calculating stopping power ratio

In this work, we conducted experiments to validate the proton physics models of Geant4 (version 10.6). The stopping power ratios (SPRs) of 11 inserts, such as acrylic, delrin, high density polyethylene, and polytetrafluoroethylene, etc, were measured using a superconducting synchrocyclotron that produces a scattering proton beam. The SPRs of the inserts were also calculated based on Geant4 simulation with six physics lists, i.e. QGSP_ FTFP_ BERT, QGSP_BIC_HP, QGSP_BIC, QGSP_FTFP_BERT, QSGP_BERT, and QBBC. The calculated SPRs were compared to the experimental SPRs, and relative per cent error was used to quantify the accuracy of the simulated SPRs of inserts. The comparison showed that the five physics lists generally agree well with the experimental SPRs with a relative difference of less than 1%. The lowest overall percentage error was observed for QGSP_FTFP_BERT and the highest overall percentage error was observed for QGSP_BIC_HP. The 0.1 mm range cut value consistently led to higher percentage error for all physics lists except for QGSP_BIC_HP and QBBC. Based on the validation, we recommend QGSP_BERT_HP physics list for proton dose calculation.

Potential of a Second-Generation Dual-Layer Spectral CT for Dose Calculation in Particle Therapy Treatment Planning

In particle therapy treatment planning, dose calculation is conducted using patient-specific maps of tissue ion stopping power ratio (SPR) to predict beam ranges. Improving patient-specific SPR prediction is therefore essential for accurate dose calculation. In this study, we investigated the use of the Spectral CT 7500, a second-generation dual-layer spectral computed tomography (DLCT) system, as an alternative to conventional single-energy CT (SECT) for patient-specific SPR prediction. This dual-energy CT (DECT)-based method allows for the direct prediction of SPR from quantitative measurements of relative electron density and effective atomic number using the Bethe equation, whereas the conventional SECT-based method consists of indirect image data-based prediction through the conversion of calibrated CT numbers to SPR. The performance of the Spectral CT 7500 in particle therapy treatment planning was characterized by conducting a thorough analysis of its SPR prediction accuracy for both tissue-equivalent materials and common non-tissue implant materials. In both instances, DLCT was found to reduce uncertainty in SPR predictions compared to SECT. Mean deviations of 0.7% and 1.6% from measured SPR values were found for DLCT- and SECT-based predictions, respectively, in tissue-equivalent materials. Furthermore, end-to-end analyses of DLCT-based treatment planning were performed for proton, helium, and carbon ion therapies with anthropomorphic head and pelvic phantoms. 3D gamma analysis was performed with ionization chamber array measurements as the reference. DLCT-predicted dose distributions revealed higher passing rates compared to SECT-predicted dose distributions. In the DLCT-based treatment plans, measured distal-edge evaluation layers were within 1 mm of their predicted positions, demonstrating the accuracy of DLCT-based particle range prediction. This study demonstrated that the use of the Spectral CT 7500 in particle therapy treatment planning may lead to better agreement between planned and delivered dose compared to current clinical SECT systems.

A reconstruction approach for proton computed tomography by modeling the integral depth dose of the scanning proton pencil beam

PURPOSE

To present a proton computed tomography (pCT) reconstruction approach that models the integral depth dose (IDD) of the clinical scanning proton beam into beamlets. Using a multi-layer ionization chamber (MLIC) as the imager, the proposed pCT system and the reconstruction approach can minimize the extra ambient neutron dose and simplify the beamline design by eliminating an additional collimator to confine the proton beam.

METHODS

Monte Carlo simulation was applied to digitally simulate the IDDs of the exiting proton beams detected by the MLIC. A forward model was developed to model each IDD into the weighted sum of percentage depth doses (PDDs) of the constituent beamlets separated laterally by 1mm. The water equivalent path lengths (WEPLs) of the beamlets were determined by iteratively minimizing the squared L2-norm of the forward projected and simulated IDDs. The final WEPL values were reconstructed to pCT images, i.e., proton Stopping Power Ratio (SPR) maps, through simultaneous algebraic reconstruction technique with total variation regularization (SART-TV). The reconstruction process was tested with a digital cylindrical water-based phantom and an ICRP adult reference computational phantom. The mean of SPR within regions of interest (ROIs) and the WEPLs along 4 mm-wide beams (WEPL_4mm ) were compared to the reference values. The spatial resolution was analyzed at the edge of a cortical insert of the cylindrical phantom.

RESULTS

The percentage deviations from reference SPR were within ±1% in all selected ROIs. The mean absolute error of the reconstructed SPR was 0.33%, 0.19%, and 0.27% for the cylindrical phantom, the adult phantom at the head and lung region, respectively. The corresponding percentage deviations from reference WEPL_4mm were 0.48%±0.64%, 0.28% ± 0.48%, and 0.22% ± 0.49%. The full width at half maximum (FWHM) of the line spread function (LSF) derived from the radial edge spread function (ESF) of a cortical insert was 0.13 cm. The frequency at 10% of the modulation transfer function (MTF) was 6.38 cm^-1 . The mean signal-to-noise ratio (SNR) of all the inserts was 2.45. The mean imaging dose was 0.29 cGy and 0.25 cGy at the head and lung region of the adult phantom, respectively.

CONCLUSION

A new pCT reconstruction approach was developed by modeling the IDDs of the uncollimated scanning proton beams in the pencil beam geometry. SPR accuracy within ±1%, spatial resolution of better than 2mm at 10% MTF, and imaging dose at the magnitude of mGy were achieved. Potential side effects caused by neutron dose were eliminated by removing the extra beam collimator. This article is protected by copyright. All rights reserved.

The NMIJ air kerma primary standard for high energy x-ray beams in 300-450 kV

Accurate radiation dosimetry is required for radiation protection in various environments. Therefore, dosemeters and dose-rate meters must be calibrated in standard radiation fields. The National Metrology Institute of Japan (NMIJ) expands the energy range of x-ray reference field measurement up to 450 kV using a cylindrical graphite-walled cavity ionization chamber. Departure from the condition of the Spencer-Attix cavity theory was evaluated by comparing the measurement results obtained using the cavity ionization and the free-air ionization chambers, which are used as the primary standard up to a tube voltage of 250 kV. The calibration coefficients found using the spherical ionization chamber were in good agreement with those obtained by the free-air ionization chamber within relative standard uncertainties (k = 1) for N-200 and N-250 x-ray fields. Consistent calibration coefficients were obtained in the energy range 300-450 kV.

Monte Carlo computation of 3D distributions of stopping power ratios in light ion beam therapy using GATE-RTion

PURPOSE

This paper presents a novel method for the calculation of three-dimensional (3D) Bragg-Gray water-to-detector stopping power ratio (s_w,det ) distributions for proton and carbon ion beams.

METHODS

Contrary to previously published fluence-based calculations of the stopping power ratio, the s_w,det calculation method used in this work is based on the specific way GATE/Geant4 scores the energy deposition. It only requires the use of the so-called DoseActor, as available in GATE, for the calculation of the s_w,det at any point of a 3D dose distribution. The simulations are performed using GATE-RTion v1.0, a dedicated GATE release that was validated for the clinical use in light ion beam therapy.

RESULTS

The Bragg-Gray water-to-air stopping power ratio (s_w,air ) was calculated for monoenergetic proton and carbon ion beams with the default stopping power data in GATE-RTion v1.0 and the new ICRU90 recommendation. The s_w,air differences between the use of the default and the ICRU90 configuration were 0.6% and 5.4% at the physical range (R₈₀ - 80% dose level in the distal dose fall-off) for a 70 MeV proton beam and a 120 MeV/u carbon ion beam, respectively. For protons, the s_w,det results for lithium fluoride, silicon, gadolinium oxysulfide, and the active layer material of EBT2 (radiochromic film) were compared with the literature and a reasonable agreement was found. For a real patient treatment plan, the 3D distributions of s_w,det in proton beams were calculated.

CONCLUSIONS

Our method was validated by comparison with available literature data. Its equivalence with Bragg-Gray cavity theory was demonstrated mathematically. The capability of GATE-RTion v1.0 for the s_w,det calculation at any point of a 3D dose distribution for simple and complex proton and carbon ion plans was presented.

Initial Validation of Proton Dose Calculations on SPR Images from DECT in Treatment Planning System

PURPOSE

To investigate and quantify the potential benefits associated with the use of stopping-power-ratio (SPR) images created from dual-energy computed tomography (DECT) images for proton dose calculation in a clinical proton treatment planning system (TPS).

MATERIALS AND METHODS

The DECT and single-energy computed tomography (SECT) scans obtained for 26 plastic tissue surrogate plugs were placed individually in a tissue-equivalent plastic phantom. Relative-electron density (ρe) and effective atomic number (Z eff) images were reconstructed from the DECT scans and used to create an SPR image set for each plug. Next, the SPR for each plug was measured in a clinical proton beam for comparison of the calculated values in the SPR images. The SPR images and SECTs were then imported into a clinical TPS, and treatment plans were developed consisting of a single field delivering a 10 × 10 × 10-cm3 spread-out Bragg peak to a clinical target volume that contained the plugs. To verify the accuracy of the TPS dose calculated from the SPR images and SECTs, treatment plans were delivered to the phantom containing each plug, and comparisons of point-dose measurements and 2-dimensional γ-analysis were performed.

RESULTS

For all 26 plugs considered in this study, SPR values for each plug from the SPR images were within 2% agreement with measurements. Additionally, treatment plans developed with the SPR images agreed with the measured point dose to within 2%, whereas a 3% agreement was observed for SECT-based plans. γ-Index pass rates were > 90% for all SECT plans and > 97% for all SPR image-based plans.

CONCLUSION

Treatment plans created in a TPS with SPR images obtained from DECT scans are accurate to within guidelines set for validation of clinical treatment plans at our center. The calculated doses from the SPR image-based treatment plans showed better agreement to measured doses than identical plans created with standard SECT scans.

Determination of proton stopping power ratio with dual-energy CT in 3D-printed tissue/air cavity surrogates

PURPOSE

To study the accuracy with which proton stopping power ratio (SPR) can be determined with dual-energy computed tomography (DECT) for small structures and bone-tissue-air interfaces like those found in the head or in the neck.

METHODS

Hollow cylindrical polylactic acid (PLA) plugs (3 cm diameter, 5 cm height) were 3D printed containing either one or three septa with thicknesses t_septa  = 0.8, 1.6, 3.2, and 6.4 mm running along the length of the plug. The cylinders were inserted individually into a tissue-equivalent head phantom (16 cm diameter, 5 cm height). First, DECT scans were obtained using a Siemens SOMATOM Definition Edge CT scanner. Effective atomic number (Z_eff ) and electron density (ρ_e ) images were reconstructed from the DECT to produce SPR-CT images of each plug. Second, independent elemental composition analysis of the PLA plastic was used to determine the Z_eff and ρ_e for calculating the theoretical SPR (SPR-TH) using the Bethe-Bloch equation. Finally, for each plug, a direct measurement of SPR (SPR-DM) was obtained in a clinical proton beam. The values of SPR-CT, SPR-TH, and SPR-DM were compared.

RESULTS

The SPR-CT for PLA agreed with SPR-DM for t_septa  ≥ 3 mm (for CT slice thicknesses of 0.5, 1.0, and 3.0 mm). The density of PLA was found to decrease with thickness when t_septa  < 3 mm. As t_septa (and density) decreased, the SPR-CT values also decreased, in good agreement with SPR-DM and SPR-TH.

CONCLUSION

Overall, the DECT-based SPR-CT was within 3% of SPR-TH and SPR-DM in the high-density gradient regions of the 3D-printed plugs for septa greater than ~ 3mm in thickness.

Material elemental decomposition in dual and multi-energy CT via a sparsity-dictionary approach for proton stopping power ratio calculation

PURPOSE

Accurate calculation of proton stopping power ratio (SPR) relative to water is crucial to proton therapy treatment planning, since SPR affects prediction of beam range. Current standard practice derives SPR using a single CT scan. Recent studies showed that dual-energy CT (DECT) offers advantages to accurately determine SPR. One method to further improve accuracy is to incorporate prior knowledge on human tissue composition through a dictionary approach. In addition, it is also suggested that using CT images with multiple (more than two) energy channels, i.e., multi-energy CT (MECT), can further improve accuracy. In this paper, we proposed a sparse dictionary-based method to convert CT numbers of DECT or MECT to elemental composition (EC) and relative electron density (rED) for SPR computation.

METHOD

A dictionary was constructed to include materials generated based on human tissues of known compositions. For a voxel with CT numbers of different energy channels, its EC and rED are determined subject to a constraint that the resulting EC is a linear non-negative combination of only a few tissues in the dictionary. We formulated this as a non-convex optimization problem. A novel algorithm was designed to solve the problem. The proposed method has a unified structure to handle both DECT and MECT with different number of channels. We tested our method in both simulation and experimental studies.

RESULTS

Average errors of SPR in experimental studies were 0.70% in DECT, 0.53% in MECT with three energy channels, and 0.45% in MECT with four channels. We also studied the impact of parameter values and established appropriate parameter values for our method.

CONCLUSION

The proposed method can accurately calculate SPR using DECT and MECT. The results suggest that using more energy channels may improve the SPR estimation accuracy.