Sensitivity of a prompt-gamma slit-camera to detect range shifts for proton treatment verification.

BACKGROUND AND PURPOSE: A prompt-gamma imaging (PGI) slit-camera was recently applied successfully in clinical proton treatments using pencil beam scanning (PBS) and double scattering (DS). However, its full capability under clinical conditions has still to be systematically evaluated. Here, the performance of the slit-camera is systematically assessed in well-defined error scenarios using realistic treatment deliveries to an anthropomorphic head phantom. MATERIALS AND METHODS: The sensitivity and accuracy to detect introduced global and local range shifts with the slit-camera was investigated in PBS and DS irradiations. For PBS, measured PGI information of shifted geometries were compared spot-wise with un-shifted PGI information derived from either a reference measurement or a treatment-plan-based simulation. Furthermore, for DS and PBS the integral PGI signal of the whole field was evaluated. RESULTS: Deviations from the treatment plan were detected with an accuracy better than 2 mm in PBS. The PGI simulation accuracy was well below 1 mm. Interfractional comparisons are more affected by measurement noise. The field-integral PGI sum signal allows the detection of global shifts in DS. CONCLUSIONS: Detection of global and local range shifts under close-to-clinical conditions is possible with the PGI slit-camera. Especially for PBS, high sensitivity and high accuracy in shift detection were found.

First clinical application of a prompt gamma based in vivo proton range verification system.

BACKGROUND AND PURPOSE: To improve precision of particle therapy, in vivo range verification is highly desirable. Methods based on prompt gamma rays emitted during treatment seem promising but have not yet been applied clinically. Here we report on the worldwide first clinical application of prompt gamma imaging (PGI) based range verification. MATERIAL AND METHODS: A prototype of a knife-edge shaped slit camera was used to measure the prompt gamma ray depth distribution during a proton treatment of a head and neck tumor for seven consecutive fractions. Inter-fractional variations of the prompt gamma profile were evaluated. For three fractions, in-room control CTs were acquired and evaluated for dose relevant changes. RESULTS: The measurement of PGI profiles during proton treatment was successful. Based on the PGI information, inter-fractional global range variations were in the range of ±2 mm for all evaluated fractions. This is in agreement with the control CT evaluation showing negligible range variations of about 1.5mm. CONCLUSIONS: For the first time, range verification based on prompt gamma imaging was applied for a clinical proton treatment. With the translation from basic physics experiments into clinical operation, the potential to improve the precision of particle therapy with this technique has increased considerably.

First test of the prompt gamma ray timing method with heterogeneous targets at a clinical proton therapy facility.

Ion beam therapy promises enhanced tumour coverage compared to conventional radiotherapy, but particle range uncertainties significantly blunt the achievable precision. Experimental tools for range verification in real-time are not yet available in clinical routine. The prompt gamma ray timing method has been recently proposed as an alternative to collimated imaging systems. The detection times of prompt gamma rays encode essential information about the depth-dose profile thanks to the measurable transit time of ions through matter. In a collaboration between OncoRay, Helmholtz-Zentrum Dresden-Rossendorf and IBA, the first test at a clinical proton accelerator (Westdeutsches Protonentherapiezentrum Essen, Germany) with several detectors and phantoms is performed. The robustness of the method against background and stability of the beam bunch time profile is explored, and the bunch time spread is characterized for different proton energies. For a beam spot with a hundred million protons and a single detector, range differences of 5 mm in defined heterogeneous targets are identified by numerical comparison of the spectrum shape. For higher statistics, range shifts down to 2 mm are detectable. A proton bunch monitor, higher detector throughput and quantitative range retrieval are the upcoming steps towards a clinically applicable prototype. In conclusion, the experimental results highlight the prospects of this straightforward verification method at a clinical pencil beam and settle this novel approach as a promising alternative in the field of in vivo dosimetry.

Analytical computation of prompt gamma ray emission and detection for proton range verification.

A prompt gamma (PG) slit camera prototype recently demonstrated that Bragg Peak position in a clinical proton scanned beam could be measured with 1-2 mm accuracy by comparing an expected PG detection profile to a measured one. The computation of the expected PG detection profile in the context of a clinical framework is challenging but must be solved before clinical implementation. Obviously, Monte Carlo methods (MC) can simulate the expected PG profile but at prohibitively long calculation times. We implemented a much faster method that is based on analytical processing of precomputed MC data that would allow practical evaluation of this range monitoring approach in clinical conditions. Reference PG emission profiles were generated with MC simulations (PENH) in targets consisting of either (12)C, (14)N, (16)O, (31)P or (40)Ca, with 10% of (1)H. In a given geometry, the local PG emission can then be derived by adding the contribution of each element, according to the local energy of the proton obtained by continuous slowing down approximation and the local composition. The actual incident spot size is taken into account using an optical model fitted to measurements and by super sampling the spot with several rays (up to 113). PG transport in the patient/camera geometries and the detector response are modelled by convolving the PG production profile with a transfer function. The latter is interpolated from a database of transfer functions fitted to MC data (PENELOPE) generated for a photon source in a cylindrical phantom with various radiuses and a camera placed at various positions. As a benchmark, the analytical model was compared to MC and experiments in homogeneous and heterogeneous phantoms. Comparisons with MC were also performed in a thoracic CT. For all cases, the analytical model reproduced the prediction of the position of the Bragg peak computed with MC within 1 mm for the camera in nominal configuration. When compared to measurements, the shape of the profiles was well reproduced and agreement for the estimation of the position of the Bragg peak was within 2.7 mm on average (1.4 mm standard deviation). On a non-optimized MATLAB code, computation time with the analytical model is between 0.3 to 10 s depending on the number of rays simulated per spot. The analytical model can be further used to determine which spots are the best candidates to evaluate the range in clinical conditions and eventually correct for over- and under-shoots depending on the acquired PG profiles.

Dependence of simulated positron emitter yields in ion beam cancer therapy on modeling nuclear fragmentation.

In ion beam cancer therapy, range verification in patients using positron emission tomography (PET) requires the comparison of measured with simulated positron emitter yields. We found that (1) changes in modeling nuclear interactions strongly affected the positron emitter yields and that (2) Monte Carlo simulations with SHIELD-HIT10Areasonably matched the most abundant PET isotopes (11)C and (15)O. We observed an ion-energy (i.e., depth) dependence of the agreement between SHIELD-HIT10Aand measurement. Improved modeling requires more accurate measurements of cross-section values.

Comparison of PHITS, GEANT4, and HIBRAC simulations of depth-dependent yields of ß(+)-emitting nuclei during therapeutic particle irradiation to measured data.

For quality assurance in particle therapy, a non-invasive, in vivo range verification is highly desired. Particle therapy positron-emission-tomography (PT-PET) is the only clinically proven method up to now for this purpose. It makes use of the ß(+)-activity produced during the irradiation by the nuclear fragmentation processes between the therapeutic beam and the irradiated tissue. Since a direct comparison of ß(+)-activity and dose is not feasible, a simulation of the expected ß(+)-activity distribution is required. For this reason it is essential to have a quantitatively reliable code for the simulation of the yields of the ß(+)-emitting nuclei at every position of the beam path. In this paper results of the three-dimensional Monte-Carlo simulation codes PHITS, GEANT4, and the one-dimensional deterministic simulation code HIBRAC are compared to measurements of the yields of the most abundant ß(+)-emitting nuclei for carbon, lithium, helium, and proton beams. In general, PHITS underestimates the yields of positron-emitters. With GEANT4 the overall most accurate results are obtained. HIBRAC and GEANT4 provide comparable results for carbon and proton beams. HIBRAC is considered as a good candidate for the implementation to clinical routine PT-PET.

Analysis of metabolic washout of positron emitters produced during carbon ion head and neck radiotherapy.

PURPOSE: Particle Therapy Positron Emission Tomography (PT-PET) is a suitable method for verification of therapeutic dose delivery by measurements of irradiation-induced ß(+)-activity. Due to metabolic processes in living tissue ß(+)-emitters can be removed from the place of generation. This washout is a limiting factor for image quality. The purpose of this study is to investigate whether a washout model obtained by animal experiments is applicable to patient data. METHODS: A model for the washout has been developed by Mizuno et al. [Phys. Med. Biol. 48(15), 2269-2281 (2003)] and Tomitani et al. [Phys. Med. Biol. 48(7), 875-889 (2003)]. It is based upon measurements in a rabbit in living and dead conditions. This model was modified and applied to PET data acquired during the experimental therapy project at GSI Helmholtzzentrum für Schwerionenforschung Darmstadt, Germany. Three components are expected: A fast one with a half life of 2 s, a medium one in the range of 2-3 min, and a slow component of the order of 2-3 h. Ten patients were selected randomly for investigation of the fast component. To analyze the other two components, 12 one-of-a-kind measurements from a single volunteer patient are available. RESULTS: A fast washout on the time scale of a few seconds was not observed in the patient data. The medium processes showed a mean half life of 155.7 ± 4.6 s. This is in the expected range. Fractions of the activity not influenced by the washout were found. CONCLUSIONS: On the time scale of an in-beam or in-room measurement only the medium-time washout processes play a remarkable role. A slow component may be neglected if the measurements do not exceed 20 min after the end of the irradiation. The fast component is not observed due to the low relative blood filled volume in the brain.

Implementation and workflow for PET monitoring of therapeutic ion irradiation: a comparison of in-beam, in-room, and off-line techniques.

An independent assessment of the dose delivery in ion therapy can be performed using positron emission tomography (PET). For that a distribution of positron emitters which appear as the result of interaction between ions of the therapeutic beam and the irradiated tissue is measured during or after the irradiation. Three concepts for PET monitoring implemented in various therapy facilities are considered in this paper. The in-beam PET concept relies on the PET measurement performed simultaneously to the irradiation by means of a PET scanner which is completely integrated into the irradiation site. The in-room PET concept allows measurement immediately after irradiation by a standalone PET scanner which is installed very close to the irradiation site. In the off-line PET scenario the measurement is performed by means of a standalone PET/CT scanner 10-30 min after the irradiation. These three concepts were evaluated according to image quality criteria, integration costs, and their influence onto the workflow of radiotherapy. In-beam PET showed the best performance. However, the integration costs were estimated as very high for this modality. Moreover, the performance of in-beam PET depends heavily on type and duty cycle of the accelerator. The in-room PET is proposed for planned therapy facilities as a good compromise between the quality of measured data and integration efforts. For facilities which are close to the nuclear medicine departments off-line PET can be suggested under several circumstances.

In-beam PET measurements of biological half-lives of 12C irradiation induced beta+-activity.

One of the long-standing problems in carbon-ion therapy is the monitoring of the treatment, i.e. of the delivered dose to a given tissue volume within the patient. Over the last 8 years, in-beam positron emission tomography (PET) has been used at the experimental carbon ion treatment facility at the Gesellschaft fur Schwerionenforschung (GSI) Darmstadt and has become a valuable quality assurance tool. In order to determine and evaluate the correct delivery of the patient dose, a simulation of the positron emitter distribution has been compared to the measurement. One particular effect is the blurring as well as the reduction of the measured activity distribution via washout. The objective of this study is the investigation of tissue dependent effective half-lives from patient data. We find no significant dependence of the effective half-life on the Hounsfield unit but on the local dose. The biological half-life within the high dose region is longer than in the low dose region. Furthermore, the influence of the overall treatment time on the kinetics of the positron emitter is reported. There are indications for a metabolic response of the tissue on the irradiation. Taking into account the biological half-life in the simulation leads to an improvement of the quality of the PET-images in some cases.