Design study of a novel geometrical arrangement for an in-beam small animal positron emission tomography scanner.

Objective.We designed a geometrical solution for a small animal in-beam positron emission tomography (PET) scanner to be used in the project SIRMIO (Small animal proton irradiator for research in molecular image-guided radiation-oncology). The system is based on 56 scintillator blocks of pixelated LYSO crystals. The crystals are arranged providing a pyramidal-step shape to optimize the geometrical coverage in a spherical configuration.Approach.Different arrangements have been simulated and compared in terms of spatial resolution and sensitivity. The chosen setup enables us to reach a good trade-off between a solid angle coverage and sufficient available space for the integration of additional components of the first design prototype of the SIRMIO platform. The possibility of moving the mouse holder inside the PET scanner furthermore allows for achieving the optimum placement of the irradiation area for all the possible tumor positions in the body of the mouse. The work also includes a study of the scintillator material where LYSO and GAGG are compared with a focus on the random coincidence noise due to the natural radioactivity of Lutetium in LYSO, justifying the choice of LYSO for the development of the final system.Main results.The best imaging performance can be achieved with a sub-millimeter spatial resolution and sensitivity of 10% in the center of the scanner, as verified in thorough simulations of point sources. The simulation of realistic irradiation scenarios of proton beams in PMMA targets with/without air gaps indicates the ability of the proposed PET system to detect range shifts down to 0.2 mm.Significance.The presented results support the choice of the identified optimal design for a novel spherical in-beam PET scanner which is currently under commissioning for application to small animal proton and light ion irradiation, and which might find also application, e.g. for biological image-guidance in x-ray irradiation.

Towards real-time EPID-based 3D in vivo dosimetry for IMRT with Deep Neural Networks: A feasibility study.

We investigate the potential of the Deep Dose Estimate (DDE) neural network to predict 3D dose distributions inside patients with Monte Carlo (MC) accuracy, based on transmitted EPID signals and patient CTs. The network was trained using as input patient CTs and first-order dose approximations (FOD). Accurate dose distributions (ADD) simulated with MC were given as training targets. 83 pelvic CTs were used to simulate ADDs and respective EPID signals for subfields of prostate IMRT plans (gantry at 0∘). FODs were produced as backprojections from the EPID signals. 581 ADD-FOD sets were produced and divided into training and test sets. An additional dataset simulated with gantry at 90∘ (lateral set) was used for evaluating the performance of the DDE at different beam directions. The quality of the FODs and DDE-predicted dose distributions (DDEP) with respect to ADDs, from the test and lateral sets, was evaluated with gamma analysis (3%,2 mm). The passing rates between FODs and ADDs were as low as 46%, while for DDEPs the passing rates were above 97% for the test set. Meaningful improvements were also observed for the lateral set. The high passing rates for DDEPs indicate that the DDE is able to convert FODs into ADDs. Moreover, the trained DDE predicts the dose inside a patient CT within 0.6 s/subfield (GPU), in contrast to 14 h needed for MC (CPU-cluster). 3D in vivo dose distributions due to clinical patient irradiation can be obtained within seconds, with MC-like accuracy, potentially paving the way towards real-time EPID-based in vivo dosimetry.

Multi-stage image registration based on list-mode proton radiographies for small animal proton irradiation: A simulation study.

We present a multi-stage and multi-resolution deformable image registration framework for image-guidance at a small animal proton irradiation platform. The framework is based on list-mode proton radiographies acquired at different angles, which are used to deform a 3D treatment planning CT relying on normalized mutual information (NMI) or root mean square error (RMSE) in the projection domain. We utilized a mouse X-ray micro-CT expressed in relative stopping power (RSP), and obtained Monte Carlo simulations of proton images in list-mode for three different treatment sites (brain, head and neck, lung). Rigid transformations and controlled artificial deformation were applied to mimic position misalignments, weight loss and breathing changes. Results were evaluated based on the residual RMSE of RSP in the image domain including the comparison of extracted local features, i.e. between the reference micro-CT and the one transformed taking into account the calculated deformation. The residual RMSE of the RSP showed that the accuracy of the registration framework is promising for compensating rigid (>97% accuracy) and non-rigid (∼95% accuracy) transformations with respect to a conventional 3D-3D registration. Results showed that the registration accuracy is degraded when considering the realistic detector performance and NMI as a metric, whereas the RMSE in projection domain is rather insensitive. This work demonstrates the pre-clinical feasibility of the registration framework on different treatment sites and its use for small animal imaging with a realistic detector. Further computational optimization of the framework is required to enable the use of this tool for online estimation of the deformation.

Impact of secondary particles on the magnetic field generated by a proton pencil beam: a finite-element analysis based on Geant4-DNA simulations.

PURPOSE: To investigate the static magnetic field generated by a proton pencil beam as a candidate for range verification by means of Monte Carlo simulations, thereby improving upon existing analytical calculations. We focus on the impact of statistical current fluctuations and secondary protons and electrons. METHODS: We considered a pulsed beam (10 µ ${\umu}$ s pulse duration) during the duty cycle with a peak beam current of 0.2 µ $\umu$ A and an initial energy of 100 MeV. We ran Geant4-DNA Monte Carlo simulations of a proton pencil beam in water and extracted independent particle phase spaces. We calculated longitudinal and radial current density of protons and electrons, serving as an input for a magnetic field estimation based on a finite element analysis in a cylindrical geometry. We made sure to allow for non-solenoidal current densities as is the case of a stopping proton beam. RESULTS: The rising proton charge density toward the range is not perturbed by energy straggling and only lowered through nuclear reactions by up to 15%, leading to an approximately constant longitudinal current. Their relative low density however (at most 0.37 protons/mm3 for the 0.2  µ ${\umu}$ A current and a beam cross-section of 2.5 mm), gives rise to considerable current density fluctuations. The radial proton current resulting from lateral scattering and being two orders of magnitude weaker than the longitudinal current is subject to even stronger fluctuations. Secondary electrons with energies above 10 eV, that far outnumber the primary protons, reduce the primary proton current by only 10% due to their largely isotropic flow. A small fraction of electrons (<1%), undergoing head-on collisions, constitutes the relevant electron current. In the far-field, both contributions to the magnetic field strength (longitudinal and lateral) are independent of the beam spot size. We also find that the nuclear reaction-related losses cause a shift of 1.3 mm to the magnetic field profile relative to the actual range, which is further enlarged to 2.4 mm by the electron current (at a distance of ρ = 50 $\rho =50$  mm away from the central beam axis). For ρ > 45 $\rho >45$  mm, the shift increases linearly. While the current density variations cause significant magnetic field uncertainty close to the central beam axis with a relative standard deviation (RSD) close to 100%, they average out at a distance of 10 cm, where the RSD of the total magnetic field drops below 2%. CONCLUSIONS: With the small influence of the secondary electrons together with the low RSD, our analysis encourages an experimental detection of the magnetic field through sensitive instrumentation, such as optical magnetometry or SQUIDs.

X-ray CT adaptation based on a 2D-3D deformable image registration framework using simulated in-room proton radiographies.

The aim of this work is to investigate in-room proton radiographies to compensate realistic rigid and non-rigid transformations in clinical-like scenarios based on 2D-3D deformable image registration (DIR) framework towards future clinical implementation of adaptive radiation therapy (ART). Monte Carlo simulations of proton radiographies (pRads) based on clinical x-ray CT of a head and neck, and a brain tumor patients are simulated for two different detector configurations (i.e. integration-mode and list-mode detectors) including high and low proton statistics. A realistic deformation, derived from cone beam CT of the patient, is applied to the treatment planning CT. Rigid inaccuracies in patient positioning are also applied and the effect of small, medium and large fields of view (FOVs) is investigated. A stopping criterion, as desirable in realistic scenarios devoid of ground truth proton CT (pCT), is proposed and investigated. Results show that rigid and non-rigid transformations can be compensated based on a limited number of low dose pRads. The root mean square error with respect to the pCT shows that the 2D-3D DIR of the treatment planning CT based on 10 pRads from integration-mode data and 2 pRads from list-mode data is capable of achieving comparable accuracy (∼90% and >90%, respectively) to conventional 3D-3D DIR. The dice similarity coefficient over the segmented regions of interest also verifies the improvement in accuracy prior to and after 2D-3D DIR. No relevant changes in accuracy are found between high and low proton statistics except for 2 pRads from integration-mode data. The impact of FOV size is negligible. The convergence of the metric adopted for the stopping criterion indicates the optimal convergence of the 2D-3D DIR. This work represents a further step towards the potential implementation of ART in proton therapy. Further computational optimization is however required to enable extensive clinical validation.

A Monte Carlo feasibility study on quantitative laser-driven proton radiography.

Laser-accelerated proton bunches with kinetic energies up to several tens of MeV and at repetition rates in the order of Hz are nowadays achievable at several research centres housing high-power laser system. The unique features of such ultra-short bunches are also arousing interest in the field of radiological and biomedical applications. For many of these applications, accurate positioning of the biological target is crucial, raising the need for on-site imaging. One convenient option is proton radiography, which can exploit the polyenergetic spectrum of laser-accelerated proton bunches. We present a Monte Carlo (MC) feasibility study to assess the applicability and potential of laser-driven proton radiography of millimetre to centimetre sized objects. Our radiography setup consists of a thin time-of-flight spectrometer operated in transmission prior to the object and a pixelated silicon detector for imaging. Proton bunches with kinetic energies up to 20MeV and up to 100MeV were investigated. The water equivalent thickness (WET) of the traversed material is calculated from the energy deposition inside an imaging detector, using an online generated calibration curve that is based on a MC generated look-up table and the reconstructed proton energy distribution. With a dose of 43mGy for a 1mm thin object imaged with protons up to 20MeV, the reconstructed WET of defined regions-of-interest was within 1.5% of the ground truth values. The spatial resolution, which strongly depends on the gap between object and imaging detector, was 2.5lpmm-1 for a realistic distance of 5mm. Due to this relatively high imaging dose, our proposed setup for laser-driven proton radiography is currently limited to objects with low radio-sensitivity, but possibilities for further dose reduction are presented and discussed.

Radioactive Beams for Image-Guided Particle Therapy: The BARB Experiment at GSI.

Several techniques are under development for image-guidance in particle therapy. Positron (ß+) emission tomography (PET) is in use since many years, because accelerated ions generate positron-emitting isotopes by nuclear fragmentation in the human body. In heavy ion therapy, a major part of the PET signals is produced by ß+-emitters generated via projectile fragmentation. A much higher intensity for the PET signal can be obtained using ß+-radioactive beams directly for treatment. This idea has always been hampered by the low intensity of the secondary beams, produced by fragmentation of the primary, stable beams. With the intensity upgrade of the SIS-18 synchrotron and the isotopic separation with the fragment separator FRS in the FAIR-phase-0 in Darmstadt, it is now possible to reach radioactive ion beams with sufficient intensity to treat a tumor in small animals. This was the motivation of the BARB (Biomedical Applications of Radioactive ion Beams) experiment that is ongoing at GSI in Darmstadt. This paper will present the plans and instruments developed by the BARB collaboration for testing the use of radioactive beams in cancer therapy.

The impact of path estimates in iterative ion CT reconstructions for clinical-like cases.

Ion computed tomography (CT) promises to mitigate range uncertainties inherent in the conversion of x-ray Hounsfield units into ion relative stopping power (RSP) for ion beam therapy treatment planning. To improve accuracy and spatial resolution of ion CT by accounting for statistical multiple Coulomb scattering deflection of the ion trajectories from a straight line path (SLP), the most likely path (MLP) and the cubic spline path (CSP) have been proposed. In this work, we use FLUKA Monte Carlo simulations to investigate the impact of these path estimates in iterative tomographic reconstruction algorithms for proton, helium and carbon ions. To this end the ordered subset simultaneous algebraic reconstruction technique was used and coupled with a total variation superiorization (TVS). We evaluate the image quality and dose calculation accuracy in proton therapy treatment planning of cranial patient anatomies. CSP and MLP generally yielded nearly equal image quality with an average RSP relative error improvement over the SLP of 0.6%, 0.3% and 0.3% for proton, helium and carbon ion CT, respectively. Bone and low density materials have been identified as regions of largest enhancement in RSP accuracy. Nevertheless, only minor differences in dose calculation results were observed between the different models and relative range errors of better than 0.5% were obtained in all cases. Largest improvements were found for proton CT in complex scenarios with strong heterogeneities along the beam path. The additional TVS provided substantially reduced image noise, resulting in improved image quality in particular for soft tissue regions. Employing the CSP and MLP for iterative ion CT reconstructions enabled improved image quality over the SLP even in realistic and heterogeneous patient anatomy. However, only limited benefit in dose calculation accuracy was obtained even though an ideal detector system was simulated.

Deformable image registration of the treatment planning CT with proton radiographies in perspective of adaptive proton therapy.

The purpose of this work is to investigate the potentiality of using a limited number of in-room proton radiographies to compensate anatomical changes in adaptive proton therapy. The treatment planning CT is adapted to the treatment delivery scenario relying on 2D-3D deformable image registration (DIR). The proton radiographies, expressed in water equivalent thickness (WET) are simulated for both list-mode and integration-mode detector configurations in pencil beam scanning. Geometrical and analytical simulations of an anthropomorphic phantom in the presence of anatomical changes due to breathing are adopted. A Monte Carlo simulation of proton radiographies based on a clinical CT image in the presence of artificial anatomical changes is also considered. The accuracy of the 2D-3D DIR, calculated as root mean square error, strongly depends on the considered anatomical changes and is considered adequate for promising adaptive proton therapy when comparable to the accuracy of conventional 3D-3D DIR. In geometrical simulation, this is achieved with a minimum of eight/nine radiographies (more than 90% accuracy). Negligible improvement (sim1%) is obtained with the use of 180 radiographies. Comparing different detector configurations, superior accuracy is obtained with list-mode than integration-mode max (WET with maximum occurrence) and mean (average WET weighted by occurrences). Moreover, integration-mode max performs better than integration-mode mean. Results are minimally affected by proton statistics. In analytical simulation, the anatomical changes are approximately compensated (about 60%-70% accuracy) with two proton radiographies and minor improvement is observed with nine proton radiographies. In clinical data, two proton radiographies from list-mode have demonstrated better performance than nine from integration-mode (more than 100% and about 50%-70% accuracy, respectively), even avoiding the finer grid spacing of the last numerical optimization stage. In conclusion, the choice of detector configuration as well as the amount and complexity of the considered anatomical changes determine the minimum number of radiographies to be used.

Patient-specific CT calibration based on ion radiography for different detector configurations in 1H, 4He and 12C ion pencil beam scanning.

The empirical conversion of the treatment planning x-ray computed tomography (CT) image to ion stopping power relative to water causes dose calculation inaccuracies in ion beam therapy. A patient-specific calibration of the CT image is enabled by the combination of an ion radiography (iRad) with the forward-projection of the empirically converted CT image along the estimated ion trajectories. This work investigated the patient-specific CT calibration for list-mode and integration-mode detector configurations, with reference to a ground truth ion CT (iCT) image. Analytical simulations of idealized carbon ion and proton trajectories in a numerical anthropomorphic phantom and realistic Monte Carlo simulations of proton, helium and carbon ion pencil beam scanning in a clinical CT image of a head-and-neck patient were considered. Controlled inaccuracy and noise levels were applied to the calibration curve and to the iRad, respectively. The impact of the selection of slices and angles of the iRads, as well as the choice of the optimization algorithm, were investigated. Accurate and robust CT calibration was obtained in analytical simulations of straight carbon ion trajectories. Analytical simulations of non-straight proton trajectories due to scattering suggested limitations for integration-mode but not for list-mode. To make the most of integration-mode, a dedicated objective function was proposed, demonstrating the desired accuracy for sufficiently high proton statistics in analytical simulations. In clinical data the inconsistencies between the iRad and the forward-projection of the ground truth iCT image were in the same order of magnitude as the applied inaccuracies (up to 5%). The accuracy of the CT calibration were within 2%-5% for integration-mode and 1%-3% for list-mode. The feasibility of successful patient-specific CT calibration depends on detector technologies and is primarily limited by these above mentioned inconsistencies that slightly penalize protons over helium and carbon ions due to larger scattering and beam spot size.

Experimental comparison of clinically used ion beams for imaging applications using a range telescope.

In particle therapy, the x-ray based treatment planning converting photon attenuation values to relative stopping power ratio (RSP) introduces clinically relevant range uncertainties. Recently, novel imaging technologies using transmission ion beams have been investigated to directly assess the water equivalent thickness (WET) of tissue, showing improved accuracy in RSP reconstruction, while potentially reducing the imaging dose. Due to their greater availability, protons have been mostly used for ion imaging. To this end, in this work, the influence of three ion species (protons, helium and carbon ions) on the image quality of radiographic WET retrieval has been explored with a dedicated experimental setup and compared to Monte Carlo (MC) simulations. Three phantom setups with different tissue interfaces and features have been irradiated with clinically validated proton, helium and carbon ion pencil beams under comparable imaging dose and beam settings at the Heidelberg Ion-Beam Therapy Center. Ion radiographies (iRADs) were acquired with an integration mode detector, that functions as a range telescope with 61 parallel plate ionization chambers. For comparison, experiments were reproduced in-silico with FLUKA MC simulations. Carbon ions provide iRADs with highest image quality in terms of normalized root mean square error, followed by helium ions and protons. All ions show similar capabilities of resolving WET for the considered phantoms, as shown by the similar average relative error < 3%. Besides for the slab phantom, MC simulations yielded better results than the experiment, indicating potential improvement of the experimental setup. Our results showed that the ability to resolve the WET is similar for all particles, intrinsically limited by the granularity of the detector system. While carbon ions are best suited for acquiring iRADs with the investigated integration mode detector, helium ions are put forward as a less technical challenging alternative.

Analytical simulator of proton radiography and tomography for different detector configurations.

PURPOSE: An analytical simulator of ion Radiography (iRad) and Computed Tomography (iCT) for protons is proposed to serve as imaging benchmark for different detector configurations. METHODS: The analytical simulator is applied to an anthropomorphic phantom and provides iRad and iCT benchmarks. Proton trajectories are traced relying on the Most Likely Path (MLP) algorithm. To simulate the proton trajectories the Multiple Coulomb Scattering (MCS) model embedded in the MLP algorithm is extended to non-uniform water equivalent materials according to variable substitution in the well-known statistical description in uniform water. The proton trajectories are instead estimated relying on the typical assumption of uniform water, thus causing intrinsic inaccuracies of the MLP algorithm. In this work the analytical simulator is used to explore and firstly compare the imaging performances of list-mode and integration-mode detector configurations with proton pencil beam scanning. RESULTS: The intrinsic inaccuracies of the MLP algorithm affect the imaging performances of list-mode detector configuration, which nevertheless remains superior to integration-mode detector configuration for iCTs. For relatively higher proton statistics, comparable or better imaging performances are offered by integration-mode detector configuration for iRads (upto 29.2% of WET difference). Uncertainties of proton trajectories due to beam spot size are shown to compromise the imaging performances of integration-mode detector configuration, but also to affect the accuracy of the MLP algorithm for list-mode detector configuration. CONCLUSIONS: Based on MCS model in non-uniform water equivalent materials, the proposed simulation environment can serve for development and testing of dedicated imaging methodologies prior to and in combination with realistic Monte Carlo simulations.

Dosimetric accuracy and radiobiological implications of ion computed tomography for proton therapy treatment planning.

Ion computed tomography (iCT) represents a potential replacement for x-ray CT (xCT) in ion therapy treatment planning to reduce range uncertainties, inherent in the semi-empirical conversion of xCT information into relative stopping power (RSP). In this work, we aim to quantify the increase in dosimetric accuracy associated with using proton-, helium- and carbon-CT compared to conventional xCT for clinical scenarios in proton therapy. Three cases imaged with active beam-delivery using an ideal single-particle-tracking detector were investigated using FLUKA Monte-Carlo (MC) simulations. The RSP accuracy of the iCTs was evaluated against the ground truth at similar physical dose. Next, the resulting dosimetric accuracy was investigated by using the RSP images as a patient model in proton therapy treatment planning, in comparison to common uncertainties associated with xCT. Finally, changes in relative biological effectiveness (RBE) with iCT particle type/spectrum were investigated by incorporating the repair-misrepair-fixation (RMF) model into FLUKA, to enable first insights on the associated biological imaging dose. Helium-CT provided the lowest overall RSP error, whereas carbon-CT offered the highest accuracy for bone and proton-CT for soft tissue. For a single field, the average relative proton beam-range variation was -1.00%, +0.09%, -0.08% and -0.35% for xCT, proton-, helium- and carbon-CT, respectively. Using a 0.5%/0.5mm gamma-evaluation, all iCTs offered comparable accuracy with a better than 99% passing rate, compared to 83% for xCT. The RMF model predictions for RBE for cell death relative to a diagnostic xCT spectrum were 0.82-0.85, 0.85-0.89 and 0.97-1.03 for proton-, helium-, and carbon-CT, respectively. The corresponding RBE for DNA double-strand break induction was generally below one. iCT offers great clinical potential for proton therapy treatment planning by providing superior dose calculation accuracy as well as lower physical and potentially biological dose exposure compared to xCT. For the investigated dose level and ideal detector, proton-CT and helium-CT yielded the best performance.

A clustering approach to 4D MRI retrospective sorting for the investigation of different surrogates.

PURPOSE: In retrospective 4-Dimensional Magnetic Resonance Imaging (4D MRI) sorting, respiratory surrogate selection affects the image quality of reconstructed volumes. We propose a method for retrospective 4D MRI sorting based on clustering, which allowed us to compare the performance of single or multiple internal surrogates vs. a conventional external signal. METHODS: A k-medoids clustering algorithm was exploited for sorting 2D MRI into 4D MRI, relying on (A) multiple or (B) single automatically tracked internal landmarks or (C) respiratory belt signal. 4D MRI reconstructions for seven liver cancer patients were compared to those of the state-of-the-art mutual information (MI) approach. Sorting artifacts were measured by the root mean square error (RMSE) between the diaphragm profile and a fitted second order curve. Diaphragm and tumor motions were evaluated. RESULTS: The median RMSEs ranged 0.97-1.66 mm, 1.24-1.89 mm, 1.43-2.27 mm, 1.74-3.72 mm for the MI, (A), (B) and (C) methods, respectively. Significant differences (Friedman, α = 5%) were found between (C) and all other methods, and between (B) and MI approaches. The discrepancies between (A) and MI approaches ranged 1.1-6.2 mm and 0.7-5.3 mm respectively in diaphragm and tumor motions. Methods (A) and (B) showed similar ranges of motion. CONCLUSION: With multiple internal points, our method yielded the description of a higher range of motion and similar image quality with respect to the MI approach. The single point method led to more artifacts, suggesting the superior suitability of multiple internal surrogates for retrospective 4D MRI sorting. Considering internal rather than external information favored superior performance.

A novel approach to EPID-based 3D volumetric dosimetry for IMRT and VMAT QA.

Intensity modulated radiation therapy (IMRT) and volumetric modulated arc therapy (VMAT) are relatively complex treatment delivery techniques and require quality assurance (QA) procedures. Pre-treatment dosimetric verification represents a fundamental QA procedure in daily clinical routine in radiation therapy. The purpose of this study is to develop an EPID-based approach to reconstruct a 3D dose distribution as imparted to a virtual cylindrical water phantom to be used for plan-specific pre-treatment dosimetric verification for IMRT and VMAT plans. For each depth, the planar 2D dose distributions acquired in air were back-projected and convolved by depth-specific scatter and attenuation kernels. The kernels were obtained by making use of scatter and attenuation models to iteratively estimate the parameters from a set of reference measurements. The derived parameters served as a look-up table for reconstruction of arbitrary measurements. The summation of the reconstructed 3D dose distributions resulted in the integrated 3D dose distribution of the treatment delivery. The accuracy of the proposed approach was validated in clinical IMRT and VMAT plans by means of gamma evaluation, comparing the reconstructed 3D dose distributions with Octavius measurement. The comparison was carried out using (3%, 3 mm) criteria scoring 99% and 96% passing rates for IMRT and VMAT, respectively. An accuracy comparable to the one of the commercial device for 3D volumetric dosimetry was demonstrated. In addition, five IMRT and five VMAT were validated against the 3D dose calculation performed by the TPS in a water phantom using the same passing rate criteria. The median passing rates within the ten treatment plans was 97.3%, whereas the lowest was 95%. Besides, the reconstructed 3D distribution is obtained without predictions relying on forward dose calculation and without external phantom or dosimetric devices. Thus, the approach provides a fully automated, fast and easy QA procedure for plan-specific pre-treatment dosimetric verification.

Time-of-flight spectrometry of ultra-short, polyenergetic proton bunches.

A common approach for spectrum determination of polyenergetic proton bunches from laser-ion acceleration experiments is based on the time-of-flight (TOF) method. However, spectra obtained using this method are typically given in relative units or are estimated based on some prior assumptions on the energy distribution of the accelerated ions. In this work, we present a new approach using the TOF method that allows for an absolute energy spectrum reconstruction from a current signal acquired with a sub-nanosecond fast and 10 µm thin silicon detector. The reconstruction is based on solving a linear least-squares problem, taking into account the response function of the detection system. The general principle of signal generation and spectrum reconstruction by setting up an appropriate system response matrix is presented. Proof-of-principle experiments at a 12 MV Tandem accelerator using different nanosecond-short (quasi-)monoenergetic and polyenergetic proton bunches at energies up to 20 MeV were successfully performed. Within the experimental uncertainties of 2.4% and 12.1% for energy and particle number, respectively, reconstructed energy distributions were found in excellent agreement with the spectra calculated using Monte Carlo simulations and measured by a magnetic spectrometer. This TOF method can hence be used for absolute online spectrometry of laser-accelerated particle bunches.

First clinical investigation of a 4D maximum likelihood reconstruction for 4D PET-based treatment verification in ion beam therapy.

BACKGROUND AND PURPOSE: In clinical applications of Positron Emission Tomography (PET)-based treatment verification in ion beam therapy (PT-PET), detection and interpretation of inconsistencies between Measured PET and Expected PET are mostly limited by Measured PET noise, due to low count statistics, and by Expected PET bias, especially due to inaccurate washout modelling in off-line implementations. In this work, a recently proposed 4D Maximum Likelihood (ML) reconstruction algorithm which considers Measured PET and Expected PET as two different motion phases of a 4D dataset is assessed on clinical 4D PET-CT datasets acquired after carbon ion therapy. MATERIAL AND METHODS: The 4D ML reconstruction algorithm estimates: (1) Measured PET of enhanced image quality with respect to the conventional Measured PET, thanks to the exploitation of Expected PET; (2) the deformation field mapping the Expected PET onto the Measured PET as a measure of the occurred displacements. RESULTS: Results demonstrate the desired sensitivity to inconsistencies due to breathing motion and/or setup modification, robustness to noise in different count statistics scenarios, but a limited sensitivity to Expected PET washout inaccuracy. CONCLUSIONS: The 4D ML reconstruction algorithm supports clinical 4D PT-PET in ion beam therapy. The limited sensitivity to washout inaccuracy can be detected and potentially overcome.

A tool for validating MRI-guided strategies: a digital breathing CT/MRI phantom of the abdominal site.

Dynamic magnetic resonance imaging (MRI) is emerging as the elected image modality for organ motion quantification and management in image-guided radiotherapy. However, the lack of validation tools is an open issue for image guidance in the abdominal and thoracic organs affected by organ motion due to respiration. We therefore present an abdominal four-dimensional (4D) CT/MRI digital phantom, including the estimation of MR tissue parameters, simulation of dedicated abdominal MR sequences, modeling of radiofrequency coil response and noise, followed by k-space sampling and image reconstruction. The phantom allows the realistic simulation of images generated by MR pulse sequences with control of scan and tissue parameters, combined with co-registered CT images. In order to demonstrate the potential of the phantom in a clinical scenario, we describe the validation of a virtual T1-weighted 4D MRI strategy. Specifically, the motion extracted from a T2-weighted 4D MRI is used to warp a T1-weighted breath-hold acquisition, with the aim of overcoming trade-offs that limit T1-weighted acquisitions. Such an application shows the applicability of the digital CT/MRI phantom as a validation tool, which should be especially useful for cases unsuited to obtain real imaging data.

Comparative Monte Carlo study on the performance of integration- and list-mode detector configurations for carbon ion computed tomography.

Ion beam therapy offers the possibility of a highly conformal tumor-dose distribution; however, this technique is extremely sensitive to inaccuracies in the treatment procedures. Ambiguities in the conversion of Hounsfield units of the treatment planning x-ray CT to relative stopping power (RSP) can cause uncertainties in the estimated ion range of up to several millimeters. Ion CT (iCT) represents a favorable solution allowing to directly assess the RSP. In this simulation study we investigate the performance of the integration-mode configuration for carbon iCT, in comparison with a single-particle approach under the same set-up. The experimental detector consists of a stack of 61 air-filled parallel-plate ionization chambers, interleaved with 3 mm thick PMMA absorbers. By means of Monte Carlo simulations, this design was applied to acquire iCTs of phantoms of tissue-equivalent materials. An optimization of the acquisition parameters was performed to reduce the dose exposure, and the implications of a reduced absorber thickness were assessed. In order to overcome limitations of integration-mode detection in the presence of lateral tissue heterogeneities a dedicated post-processing method using a linear decomposition of the detector signal was developed and its performance was compared to the list-mode acquisition. For the current set-up, the phantom dose could be reduced to below 30 mGy with only minor image quality degradation. By using the decomposition method a correct identification of the components and a RSP accuracy improvement of around 2.0% was obtained. The comparison of integration- and list-mode indicated a slightly better image quality of the latter, with an average median RSP error below 1.8% and 1.0%, respectively. With a decreased absorber thickness a reduced RSP error was observed. Overall, these findings support the potential of iCT for low dose RSP estimation, showing that integration-mode detectors with dedicated post-processing strategies can provide a RSP accuracy comparable to list-mode configurations.

Intra-fraction respiratory motion and baseline drift during breast Helical Tomotherapy.

BACKGROUND AND PURPOSE: To investigate the intra-fraction breast motion during long-lasting treatments of breast cancer with Helical Tomotherapy by means of an optical tracking system. MATERIALS AND METHODS: A set of seven radio-transparent passive markers was placed on the thoraco-abdominal surface of twenty breast cancer patients and tracked by an infrared tracking system. A continuous non-invasive monitoring of intra-fraction motion from patient setup verification and correction to the end of radiation delivery was thus obtained. The measured displacements were analysed in terms of cyclic respiratory motion and slow baseline drift. RESULTS: The average monitoring time per patient was 15.57min. The breathing amplitude of the chest was less than 2mm, on average, along all anatomical directions. The baseline drift of the body led to more significant setup uncertainties than the respiratory motion. The main intra-fraction baseline drifts were in posterior and inferior directions and occurred within the first eight minutes of monitoring. Considering the intra-fraction motion only, the resultant clinical-to-planning target volume safety margins are highly patient-specific and largely anisotropic. CONCLUSION: The non-respiratory motion occurring during prolonged treatments induces notable uncertainties. Non-invasive continuous monitoring of patient setup variations including baseline drifts is recommended in order to minimize dosimetric deviations, which might jeopardize the therapeutic ratio between target coverage and the sparing of organs at risk.