Beam commissioning of the first compact proton therapy system with spot scanning and dynamic field collimation.

OBJECTIVES: To describe the measurements and to present the results of the beam commissioning and the beam model validation of a compact, gantry-mounted, spot scanning proton accelerator system with dynamic layer-by-layer field collimation. METHODS: We performed measurements of depth dose distributions in water, spot and scanned field size in air at different positions from the isocenter plane, spot position over the 20 × 20 cm2 scanned area, beam monitor calibration in terms of absorbed dose to water and specific field collimation measurements at different gantry angles to commission the system. To validate the beam model in the treatment planning system (TPS), we measured spot profiles in water at different depths, absolute dose in water of single energy layers of different field sizes and inversely optimised spread-out Bragg peaks (SOBP) under normal and oblique beam incidence, field size and penumbra in water of SOBPs, and patient treatment specific quality assurance in homogeneous and heterogeneous phantoms. RESULTS: Energy range, spot size, spot position and dose output were consistent at all gantry angles with 0.3 mm, 0.4 mm, 0.6 mm and 0.5% maximum deviations, respectively. Uncollimated spot size (one sigma) in air with an air-gap of 10 cm ranged from 4.1 to 16.4 mm covering a range from 32.2 to 1.9 cm in water, respectively. Absolute dose measurements were within 3% when comparing TPS and experimental data. Gamma pass rates >98% and >96% at 3%/3 mm were obtained when performing 2D dose measurements in homogeneous and in heterogeneous media, respectively. Leaf position was within ±1 mm at all gantry angles and nozzle positions. CONCLUSIONS: Beam characterisation and machine commissioning results, and the exhaustive end-to-end tests performed to assess the proper functionality of the system, confirm that it is safe and accurate to treat patients. ADVANCES IN KNOWLEDGE: This is the first paper addressing the beam commissioning and the beam validation of a compact, gantry-mounted, pencil beam scanning proton accelerator system with dynamic layer-by-layer multileaf collimation.

Technical Note: Relative proton stopping power estimation from virtual monoenergetic images reconstructed from dual-layer computed tomography.

PURPOSE: The objective of this technical note was to investigate the accuracy of proton stopping power relative to water (RSP) estimation using a novel dual-layer, dual-energy computed tomography (DL-DECT) scanner for potential use in proton therapy planning. DL-DECT allows dual-energy reconstruction from scans acquired at a single x-ray tube voltage V by using two-layered detectors. METHODS: Sets of calibration and evaluation inserts were scanned at a DL-DECT scanner in a custom phantom with variable diameter D (0 to 150 mm) at V of 120 and 140 kV. Inserts were additionally scanned at a synchrotron computed tomography facility to obtain comparative linear attenuation coefficients for energies from 50 to 100 keV, and reference RSP was obtained using a carbon ion beam and variable water column. DL-DECT monoenergetic (mono-E) reconstructions were employed to obtain RSP by adapting the Yang-Saito-Landry (YSL) method. The method was compared to reference RSP via the root mean square error (RMSE) over insert mean values obtained from volumetric regions of interest. The accuracy of intermediate quantities such as the relative electron density (RED), effective atomic number (EAN), and the mono-E was additionally evaluated. RESULTS: The lung inserts showed higher errors for all quantities and we report RMSE excluding them. RMSE for µ from DL-DECT mono-E was below 1.9%. For the evaluation inserts at D = 150 mm and V = 140 kV, RED RMSE was 1.0%, while for EAN it was 2.9%. RSP RMSE was below 0.8% for all D and V, which did not strongly affect the results. CONCLUSIONS: In this investigation of RSP accuracy from DL-DECT, we have shown that RMSE below 1% can be achieved. It was possible to adapt the YSL method for DL-DECT and intermediate quantities RED and EAN had comparable accuracy to previous publications.

On the determination of planning target margins due to motion for mice lung tumours using a four-dimensional MOBY phantom.

OBJECTIVE:: This work aims to analyse the effect of respiratory motion on optimal irradiation margins for murine lung tumour models. METHODS:: Four-dimensional mathematical phantoms with different lung tumour locations affected by respiratory motion were created. Two extreme breathing curves were adopted and divided into time-points. Each time-point was loaded in a treatment planning system and Monte Carlo (MC) dose calculations were performed for a 360° arc plan. A time-resolved dose was derived, considering the gantry rotation and the breathing motion. Radiotherapy metrics were derived to assess the final treatment plans. An interpolation function was investigated to reduce calculation cost. RESULTS:: The effect of respiratory motion on the treatment plan quality is strongly dependent on the breathing pattern and the tumour position. Tumours located closer to the diaphragm required a compromise between tumour conformity and healthy tissue damage. A recipe, which considers collimator size, was proposed to derive tumour margins and spare the organs at risk (OARs) by respecting constraints on user-defined metrics. CONCLUSION:: It is recommended to add a target margin, especially on sites where movement is substantial. A simple recipe to derive tumour margins was developed. ADVANCES IN KNOWLEDGE:: This work is a first step towards a standard planning target volume concept in pre-clinical radiotherapy.

Murine vs human tissue compositions: implications of using human tissue compositions for photon energy absorption in mice.

METHODS:: Dual energy CT (DECT) images of 9 female mice were used to extract the effective atomic number Zeff and the relative electron density ρe for each voxel in the images. To investigate the influence of the tissue compositions on the absorbed radiation dose for a typical kilovoltage photon beam, mass energy-absorption coefficients µen/ρ were calculated for 10 different tissues in each mouse. RESULTS: Differences between human and murine tissue compositions can lead to errors around 7.5 % for soft tissues and 20.1 % for bone tissues in µen/ρ values for kilovoltage photon beams. When considering the spread within tissues, these errors can increase up to 17.5 % for soft tissues and 53.9 % for bone tissues within only a single standard deviation away from the mean tissue value. CONCLUSION:: This study illustrates the need for murine reference tissue data. However, assigning only a single mean reference value to an entire tissue can still lead to large errors in dose calculations given the large spread within tissues of µen/ρ values found in this study. Therefore, new methods such as DECT and spectral CT imaging need to be explored, which can be important next steps in improving tissue assignment for dose calculations in small animal radiotherapy. ADVANCES IN KNOWLEDGE:: This is the first study that investigates the implications of using human tissue compositions for dose calculations in mice for kilovoltage photon beams.

The effect of different image reconstruction techniques on pre-clinical quantitative imaging and dual-energy CT.

OBJECTIVE:: To analyse the effect of different image reconstruction techniques on image quality and dual energy CT (DECT) imaging metrics. METHODS:: A software platform for pre-clinical cone beam CT X-ray image reconstruction was built using the open-source reconstruction toolkit. Pre-processed projections were reconstructed with filtered back-projection and iterative algorithms, namely Feldkamp, Davis, and Kress (FDK), Iterative FDK, simultaneous algebraic reconstruction technique (SART), simultaneous iterative reconstruction technique and conjugate gradient. Imaging metrics were quantitatively assessed, using a quality assurance phantom, and DECT analysis was performed to determine the influence of each reconstruction technique on the relative electron density (ρe) and effective atomic number (Zeff) values. RESULTS:: Iterative reconstruction had favourable results for the DECT analysis: a significantly smaller spread for each material in the ρe-Zeff space and lower Zeff and ρe residuals (on average 24 and 25% lower, respectively). In terms of image quality assurance, the techniques FDK, Iterative FDK and SART provided acceptable results. The three reconstruction methods showed similar geometric accuracy, uniformity and CT number results. The technique SART had a contrast-to-noise ratio up to 76% higher for solid water and twice as high for Teflon, but resolution was up to 28% lower when compared to the other two techniques. CONCLUSIONS:: Advanced image reconstruction can be beneficial, but the benefit is small, and calculation times may be unacceptable with current technology. The use of targeted and downscaled reconstruction grids, larger, yet practicable, pixel sizes and GPU are recommended. ADVANCES IN KNOWLEDGE:: An iterative CBCT reconstruction platform was build using RTK.

Exploring the feasibility of a clinical proton beam with an adaptive aperture for pre-clinical research.

OBJECTIVE:: To investigate whether the Mevion S250i with HYPERSCAN clinical proton system could be used for pre-clinical research with millimetric beams. METHODS:: The nozzle of the proton beam line, consisting of an energy modulation system (EMS) and an adaptive aperture (AA), was modelled with the TOPAS Monte Carlo Simulation Toolkit. With the EMS, the 230 MeV beam nominal range can be decreased in multiples of 2.1 mm. Monte Carlo dose calculations were performed in a mouse lung tumour CT image. The AA allows fields as small as 5 × 1 mm2 to be used for irradiation. The best plans to give 2 Gy to the tumour were derived from a set of discrete energies allowed by the EMS, different field sizes and beam directions. The final proton plans were compared to a precision photon irradiation plan. Treatment times were also assessed. RESULTS:: Seven different proton beam plans were investigated, with a good coverage to the tumour (D95 > 1.95 Gy, D5 < 2.3 Gy) and with potentially less damage to the organs at risk than the photon plan. For very small fields and low energies, the number of protons arriving to the target drops to 1-3%, nevertheless the treatment times would be below 5 s. CONCLUSION:: The proton plans made in this study, collimated by an AA, could be used for animal irradiation. ADVANCES IN KNOWLEDGE:: This is one of the first study to demonstrate the feasibility of pre-clinical research with a clinical proton beam with an adaptive aperture used to create small fields.

Automatic multiatlas based organ at risk segmentation in mice.

OBJECTIVE:: During the treatment planning of a preclinical small animal irradiation, which has time limitations for reasons of animal wellbeing and workflow efficiency, the time consuming organ at risk (OAR) delineation is performed manually. This work aimed to develop, demonstrate, and quantitatively evaluate an automated contouring method for six OARs in a preclinical irritation treatment workflow. METHODS:: Microcone beam CT images of nine healthy mice were contoured with an in-house developed multiatlas-based image segmentation (MABIS) algorithm for six OARs: kidneys, eyes, heart, and brain. The automatic contouring was compared with the manual delineation using three quantitative metrics: the Dice Similarity Coefficient (DSC), 95th percentile Hausdorff Distance, and the centre of mass displacement. RESULTS:: A good agreement between manual and automatic contouring was found for OARs with sharp organ boundaries. For the brain and the heart, the median DSC was larger than 0.94, the median 95th Hausdorff Distance smaller than 0.44 mm, and the median centre of mass displacement smaller than 0.20 mm. Lower DSC values were obtained for the other OARs, but the median DSC was still larger than 0.74 for the left eye, 0.69 for the right eye, 0.89 for the left kidney and 0.80 for the right kidney. CONCLUSION:: The MABIS algorithm was able to delineate six OARs with a relatively high accuracy. Segmenting OARs with sharp organ boundaries performed better than low contrast OARs. ADVANCES IN KNOWLEDGE:: A MABIS algorithm is developed, evaluated, and demonstrated in a preclinical small animal irradiation research workflow.

Revisiting the single-energy CT calibration for proton therapy treatment planning: a critical look at the stoichiometric method.

Despite extensive research in dual-energy computed tomography (CT), single-energy CT (SECT) is still the standard imaging modality in proton therapy treatment planning and, in this context, the stoichiometric calibration method is considered to be the most accurate to establish a relationship between CT numbers and proton stopping power. This work revisits the SECT calibration for proton therapy treatment planning, with special emphasis on the stoichiometric method. Three different sets of tissue-substitutes of known elemental composition (Gammex, CIRS and Catphan) were scanned with the same scanning protocol. A stoichiometric fit was performed for each set of tissue-substitutes. Based on that, the CT number, relative electron density and relative proton stopping power were calculated for ICRU 46 biological tissues and the different sets of tissue-substitutes. Despite common belief, it was found that the stoichiometric fit depends on the elemental composition of the tissue-substitutes used in the calibration, leading to differences in relative stopping power up to 3.5% for cortical bone. In addition, according to Rutherford et al (1976 Neuroradiology 11 15-21) parametrization of the atomic cross-section, CT numbers of Gammex tissue-substitutes and ICRU 46 biological tissues were found to be similar within the whole energy range relevant to computed tomography. Consequently, it was found that, for Gammex tissue-substitutes, the CT calibration curve resulting from the stoichiometric method agrees with that obtained by simple interpolation of experimental data. In conclusion, the stoichiometric method for SECT calibration seems to depend on the tissue-substitutes used for calibration-which could be regarded as an additional source of uncertainty in proton range for bone tissues. Furthermore, Gammex tissue-substitutes appear to be a good representative of biological tissues within the energy range relevant to computed tomography-making the stoichiometric method unnecessary.

Monte Carlo proton dose calculations using a radiotherapy specific dual-energy CT scanner for tissue segmentation and range assessment.

Proton beam ranges derived from dual-energy computed tomography (DECT) images from a dual-spiral radiotherapy (RT)-specific CT scanner were assessed using Monte Carlo (MC) dose calculations. Images from a dual-source and a twin-beam DECT scanner were also used to establish a comparison to the RT-specific scanner. Proton ranges extracted from conventional single-energy CT (SECT) were additionally performed to benchmark against literature values. Using two phantoms, a DECT methodology was tested as input for Geant4 MC proton dose calculations. Proton ranges were calculated for different mono-energetic proton beams irradiating both phantoms; the results were compared to the ground truth based on the phantom compositions. The same methodology was applied in a head-and-neck cancer patient using both SECT and dual-spiral DECT scans from the RT-specific scanner. A pencil-beam-scanning plan was designed, which was subsequently optimized by MC dose calculations, and differences in proton range for the different image-based simulations were assessed. For phantoms, the DECT method yielded overall better material segmentation with >86% of the voxel correctly assigned for the dual-spiral and dual-source scanners, but only 64% for a twin-beam scanner. For the calibration phantom, the dual-spiral scanner yielded range errors below 1.2 mm (0.6% of range), like the errors yielded by the dual-source scanner (<1.1 mm, <0.5%). With the validation phantom, the dual-spiral scanner yielded errors below 0.8 mm (0.9%), whereas SECT yielded errors up to 1.6 mm (2%). For the patient case, where the absolute truth was missing, proton range differences between DECT and SECT were on average in -1.2 ± 1.2 mm (-0.5% ± 0.5%). MC dose calculations were successfully performed on DECT images, where the dual-spiral scanner resulted in media segmentation and range accuracy as good as the dual-source CT. In the patient, the various methods showed relevant range differences.

VOXSI: A voxelized single- and dual-energy CT scenario generator for quantitative imaging.

BACKGROUND AND PURPOSE: Dedicated CT simulation models have the potential to investigate several acquisition, reconstruction, or post-processing parameters without giving any radiation dose to patients. A software program was developed for the simulation and the analysis of single-energy and dual-energy CT images. Simulation and analysis functionalities of the software are described. MATERIALS AND METHODS: In the software, named VOXSI (VOXelized CT SImulator), the X-ray source, user specified simulation geometry, CT setup and the detector energy response can be varied. CT image reconstructions can be performed with an implementation of the ASTRA toolbox. In the DECT post processing toolkit, GUI tools are provided to calculate effective atomic number, relative electron density, pseudo-monoenergetic images, and material map images. Quantitative CT number validation, based on a RMI 467 tissue characterization phantom model, was performed between experimental and simulated CT scans at three different X-ray tube potentials (80, 120, and 140 kVp) with a third generation CT scanner. RESULTS: Overall, a good agreement was found for the mean CT numbers of the RMI 467 inserts. For all energies, the maximum difference in CT numbers between experimental and simulated data was below 17 HU for the soft tissues and below 48 HU for the osseous tissues. CONCLUSION: The software's simulation algorithm showed a good agreement between the CT measurements and CT simulations of the RMI 467 phantom at different energies. The capabilities of the software are demonstrated by an elaborated dual-energy CT research example.

The impact of dual energy CT imaging on dose calculations for pre-clinical studies.

BACKGROUND: To investigate the feasibility of using dual-energy CT (DECT) for tissue segmentation and kilovolt (kV) dose calculations in pre-clinical studies and assess potential dose calculation accuracy gain. METHODS: Two phantoms and an ex-vivo mouse were scanned in a small animal irradiator with two distinct energies. Tissue segmentation was performed with the single-energy CT (SECT) and DECT methods. A number of different material maps was used. Dose calculations were performed to verify the impact of segmentations on the dose accuracy. RESULTS: DECT showed better overall results in comparison to SECT. Higher number of DECT segmentation media resulted in smaller dose differences in comparison to the reference. Increasing the number of materials in the SECT method yielded more instability. Both modalities showed a limit to which adding more materials with similar characteristics ceased providing better segmentation results, and resulted in more noise in the material maps and the dose distributions. The effect was aggravated with a decrease in beam energy. For the ex-vivo specimen, the choice of only one high dense bone for the SECT method resulted in large volumes of tissue receiving high doses. For the DECT method, the choice of more than one kind of bone resulted in lower dose values for the different tissues occupying the same volume. For the organs at risk surrounded by bone, the doses were lower when using the SECT method in comparison to DECT, due to the high absorption of the bone. SECT material segmentation may lead to an underestimation of the dose to OAR in the proximity of bone. CONCLUSIONS: The DECT method enabled the selection of a higher number of materials thereby increasing the accuracy in dose calculations. In phantom studies, SECT performed best with three materials and DECT with seven for the phantom case. For irradiations in preclinical studies with kV photon energies, the use of DECT segmentation combined with the choice of a low-density bone is recommended.

Dual-energy CT quantitative imaging: a comparison study between twin-beam and dual-source CT scanners.

PURPOSE: To assess image quality and to quantify the accuracy of relative electron densities (ρe ) and effective atomic numbers (Zeff ) for three dual-energy computed tomography (DECT) scanners: a novel single-source split-filter (i.e., twin-beam) and two dual-source scanners. METHODS: Measurements were made with a second generation dual-source scanner at 80/140Sn kVp, a third-generation twin-beam single-source scanner at 120 kVp with gold (Au) and tin (Sn) filters, and a third-generation dual-source scanner at 90/150Sn kVp. Three phantoms with tissue inserts were scanned and used for calibration and validation of parameterized methods to extract ρe and Zeff , whereas iodine and calcium inserts were used to quantify Contrast-to-Noise-Ratio (CNR). Spatial resolution in tomographic images was also tested. RESULTS: The third-generation scanners have an image resolution of 6.2, ~0.5 lp/cm higher than the second generation scanner. The twin-beam scanner has low imaging contrast for iodine materials due to its limited spectral separation. The parameterization methods resulted in calibrations with low fit residuals for the dual-source scanners, yielding values of ρe and Zeff close to the reference values (errors within 1.2% for ρe and 6.2% for Zeff for a dose of 20 mGy, excluding lung substitute tissues). The twin-beam scanner presented overall higher errors (within 3.2% for ρe and 28% for Zeff , also excluding lung inserts) and also larger variations for uniform inserts. CONCLUSIONS: Spatial resolution is similar for the three scanners. The twin-beam is able to derive ρe and Zeff , but with inferior accuracy compared to both dual-source scanners.

Optimizing dual energy cone beam CT protocols for preclinical imaging and radiation research.

OBJECTIVE: The aim of this work was to investigate whether quantitative dual-energy CT (DECT) imaging is feasible for small animal irradiators with an integrated cone-beam CT (CBCT) system. METHODS: The optimal imaging protocols were determined by analyzing different energy combinations and dose levels. The influence of beam hardening effects and the performance of a beam hardening correction (BHC) were investigated. In addition, two systems from different manufacturers were compared in terms of errors in the extracted effective atomic numbers (Zeff) and relative electron densities (ρe) for phantom inserts with known elemental compositions and relative electron densities. RESULTS: The optimal energy combination was determined to be 50 and 90 kVp. For this combination, Zeff and ρe can be extracted with a mean error of 0.11 and 0.010, respectively, at a dose level of 60 cGy. CONCLUSION: Quantitative DECT imaging is feasible for small animal irradiators with an integrated CBCT system. To obtain the best results, optimizing the imaging protocols is required. Well-separated X-ray spectra and a sufficient dose level should be used to minimize the error and noise for Zeff and ρe. When no BHC is applied in the image reconstruction, the size of the calibration phantom should match the size of the imaged object to limit the influence of beam hardening effects. No significant differences in Zeff and ρe errors are observed between the two systems from different manufacturers. Advances in knowledge: This is the first study that investigates quantitative DECT imaging for small animal irradiators with an integrated CBCT system.