MACACO II test-beam with high energy photons

A Portable Three-Layer Compton Camera for Wide-Energy-Range Gamma-ray Imaging: Design, Simulation and Preliminary Testing

(1) Background: The imaging energy range of a typical Compton camera is limited due to the fact that scattered gamma photons are seldom fully absorbed when the incident energies are above 3 MeV. Further improving the upper energy limit of gamma-ray imaging has important application significance in the active interrogation of special nuclear materials and chemical warfare agents, as well as range verification of proton therapy. (2) Methods: To realize gamma-ray imaging in a wide energy range of 0.3~7 MeV, a principle prototype, named a portable three-layer Compton camera, is developed using the scintillation detector that consists of an silicon photomultiplier array coupled with a Gd3Al2Ga3O12:Ce pixelated scintillator array. Implemented in a list-mode maximum likelihood expectation maximization algorithm, a far-field energy-domain imaging method based on the two interaction events is applied to estimate the initial energy and spatial distribution of gamma-ray sources. The simulation model of the detectors is established based on the Monte Carlo simulation toolkit Geant4. The reconstructed images of a 133Ba, a 137Cs and a 60Co point-like sources have been successfully obtained with our prototype in laboratory tests and compared with simulation studies. (3) Results: The proportion of effective imaging events accounts for about 2%, which allows our prototype to realize the reconstruction of the distribution of a 0.05 μSv/h 137Cs source in 10 s. The angular resolution for resolving two 137Cs point-like sources is 15°. Additional simulated imaging of the 6.13 MeV gamma-rays from 14.1 MeV neutron scattering with water preliminarily demonstrates the imaging capability for high incident energy. (4) Conclusions: We conclude that the prototype has a good imaging performance in a wide energy range (0.3~7 MeV), which shows potential in several MeV gamma-ray imaging applications.

Influence of the background in Compton camera images for proton therapy treatment monitoring

Objective. Background events are one of the most relevant contributions to image degradation in Compton camera imaging for hadron therapy treatment monitoring. A study of the background and its contribution to image degradation is important to define future strategies to reduce the background in the system.Approach. In this simulation study, the percentage of different kinds of events and their contribution to the reconstructed image in a two-layer Compton camera have been evaluated. To this end, GATE v8.2 simulations of a proton beam impinging on a PMMA phantom have been carried out, for different proton beam energies and at different beam intensities.Main results. For a simulated Compton camera made of Lanthanum (III) Bromide monolithic crystals, coincidences caused by neutrons arriving from the phantom are the most common type of background produced by secondary radiations in the Compton camera, causing between 13% and 33% of the detected coincidences, depending on the beam energy. Results also show that random coincidences are a significant cause of image degradation at high beam intensities, and their influence in the reconstructed images is studied for values of the time coincidence windows from 500 ps to 100 ns.Significance. Results indicate the timing capabilities required to retrieve the fall-off position with good precision. Still, the noise observed in the image when no randoms are considered make us consider further background rejection methods.

Joint image reconstruction algorithm in Compton cameras

Objective. To demonstrate the benefits of using an joint image reconstruction algorithm based on the List Mode Maximum Likelihood Expectation Maximization that combines events measured in different channels of information of a Compton camera. Approach. Both simulations and experimental data are employed to show the algorithm performance. Main results. The obtained joint images present improved image quality and yield better estimates of displacements of high-energy gamma-ray emitting sources. The algorithm also provides images that are more stable than any individual channel against the noisy convergence that characterizes Maximum Likelihood based algorithms. Significance. The joint reconstruction algorithm can improve the quality and robustness of Compton camera images. It also has high versatility, as it can be easily adapted to any Compton camera geometry. It is thus expected to represent an important step in the optimization of Compton camera imaging.

Compton imaging for medical applications

Compton imaging exploits inelastic scattering, known as Compton scattering, using a Compton camera consisting of a scatterer detector in the front layer and an absorber detector in the back layer. This method was developed for astronomy, and in recent years, research and development for environmental and medical applications has been actively conducted. Compton imaging can discriminate gamma rays over a wide energy range from several hundred keV to several MeV. Therefore, it is expected to be applied to the simultaneous imaging of multiple nuclides in nuclear medicine and prompt gamma ray imaging for range verification in particle therapy. In addition, multiple gamma coincidence imaging is expected to be realized, which allows the source position to be determined from a single coincidence event using nuclides that emit multiple gamma rays simultaneously, such as nuclides that emit a single gamma ray simultaneously with positron decay. This review introduces various efforts toward the practical application of Compton imaging in the medical field, including in vivo studies, and discusses its prospects.

Applications of Machine Learning to Improve the Clinical Viability of Compton Camera Based in vivo Range Verification in Proton Radiotherapy

We studied the application of a deep, fully connected Neural Network (NN) to process prompt gamma (PG) data measured by a Compton camera (CC) during the delivery of clinical proton radiotherapy beams. The network identifies 1) recorded "bad" PG events arising from background noise during the measurement, and 2) the correct ordering of PG interactions in the CC to help improve the fidelity of "good" data used for image reconstruction. PG emission from a tissue-equivalent target during irradiation with a 150 MeV proton beam delivered at clinical dose rates was measured with a prototype CC. Images were reconstructed from both the raw measured data and the measured data that was further processed with a neural network (NN) trained to identify "good" and "bad" PG events and predict the ordering of individual interactions within the good PG events. We determine if NN processing of the CC data could improve the reconstructed PG images to a level in which they could provide clinically useful information about the in vivo range and range shifts of the proton beams delivered at full clinical dose rates. Results showed that a deep, fully connected NN improved the achievable contrast to noise ratio (CNR) in our images by more than a factor of 8x. This allowed the path, range, and lateral width of the clinical proton beam within a tissue equivalent target to easily be identified from the PG images, even at the highest dose rates of a 150 MeV proton beam used for clinical treatments. On average, shifts in the beam range as small as 3 mm could be identified. However, when limited by the amount of PG data measured with our prototype CC during the delivery of a single proton pencil beam (~1 × 10⁹ protons), the uncertainty in the reconstructed PG images limited the identification of range shift to ~5 mm. Substantial improvements in CC images were obtained during clinical beam delivery through NN pre-processing of the measured PG data. We believe this shows the potential of NNs to help improve and push CC-based PG imaging toward eventual clinical application for proton RT treatment delivery verification.

Proton therapy monitoring: spatiotemporal emission reconstruction with prompt gamma timing and implementation with PET detectors

Objective. In this study we introduce spatiotemporal emission reconstruction prompt gamma timing (SER-PGT), a new method to directly reconstruct the prompt photon emission in the space and time domains inside the patient in proton therapy.Approach. SER-PGT is based on the numerical optimisation of a multidimensional likelihood function, followed by a post-processing of the results. The current approach relies on a specific implementation of the maximum-likelihood expectation maximisation algorithm. The robustness of the method is guaranteed by the complete absence of any information about the target composition in the algorithm.Main results. Accurate Monte Carlo simulations indicate a range resolution of about 0.5 cm (standard deviation) when considering 10⁷primary protons impinging on an homogeneous phantom. Preliminary results on an anthropomorphic phantom are also reported.Significance. By showing the feasibility for the reconstruction of the primary particle range using PET detectors, this study provides significant basis for the development of an hybrid in-beam PET and prompt photon device.

Towards machine learning aided real-time range imaging in proton therapy

Compton imaging represents a promising technique for range verification in proton therapy treatments. In this work, we report on the advantageous aspects of the i-TED detector for proton-range monitoring, based on the results of the first Monte Carlo study of its applicability to this field. i-TED is an array of Compton cameras, that have been specifically designed for neutron-capture nuclear physics experiments, which are characterized by [Formula: see text]-ray energies spanning up to 5-6 MeV, rather low [Formula: see text]-ray emission yields and very intense neutron induced [Formula: see text]-ray backgrounds. Our developments to cope with these three aspects are concomitant with those required in the field of hadron therapy, especially in terms of high efficiency for real-time monitoring, low sensitivity to neutron backgrounds and reliable performance at the high [Formula: see text]-ray energies. We find that signal-to-background ratios can be appreciably improved with i-TED thanks to its light-weight design and the low neutron-capture cross sections of its LaCl[Formula: see text] crystals, when compared to other similar systems based on LYSO, CdZnTe or LaBr[Formula: see text]. Its high time-resolution (CRT [Formula: see text] 500 ps) represents an additional advantage for background suppression when operated in pulsed HT mode. Each i-TED Compton module features two detection planes of very large LaCl[Formula: see text] monolithic crystals, thereby achieving a high efficiency in coincidence of 0.2% for a point-like 1 MeV [Formula: see text]-ray source at 5 cm distance. This leads to sufficient statistics for reliable image reconstruction with an array of four i-TED detectors assuming clinical intensities of 10[Formula: see text] protons per treatment point. The use of a two-plane design instead of three-planes has been preferred owing to the higher attainable efficiency for double time-coincidences than for threefold events. The loss of full-energy events for high energy [Formula: see text]-rays is compensated by means of machine-learning based algorithms, which allow one to enhance the signal-to-total ratio up to a factor of 2.

Multi-modal 3D imaging of radionuclides using multiple hybrid Compton cameras

For radiological diagnosis and radionuclide therapy, X-ray and gamma-ray imaging technologies are essential. Single-photon emission tomography (SPECT) and positron emission tomography (PET) play essential roles in radiological diagnosis, such as the early detection of tumors. Radionuclide therapy is also rapidly developing with the use of these modalities. Nevertheless, a limited number of radioactive tracers are imaged owing to the limitations of the imaging devices. In a previous study, we developed a hybrid Compton camera that conducts simultaneous Compton and pinhole imaging within a single system. In this study, we developed a system that simultaneously realizes three modalities: Compton, pinhole, and PET imaging in 3D space using multiple hybrid Compton cameras. We achieved the simultaneous imaging of Cs-137 (Compton mode targeting 662 keV), Na-22 (PET mode targeting 511 keV), and Am-241 (pinhole mode targeting 60 keV) within the same field of view. In addition, the imaging of Ga-67 and In-111, which are used in various diagnostic scenarios, was conducted. We also verified that the 3D distribution of the At-211 tracer inside a mouse could be imaged using the pinhole mode.

Influence of sub-nanosecond time of flight resolution for online range verification in proton therapy using the line-cone reconstruction in Compton imaging

Online ion range monitoring in hadron therapy can be performed via detection of secondary radiation, such as promptγ-rays, emitted during treatment. The promptγemission profile is correlated with the ion depth-dose profile and can be reconstructed via Compton imaging. The line-cone reconstruction, using the intersection between the primary beam trajectory and the cone reconstructed via a Compton camera, requires negligible computation time compared to iterative algorithms. A recent report hypothesised that time of flight (TOF) based discrimination could improve the precision of theγfall-off position (FOP) measured via line-cone reconstruction, where TOF comprises both the proton transit time from the phantom entrance untilγemission, and the flight time of theγ-ray to the detector. The aim of this study was to implement such a method and investigate the influence of temporal resolution on the precision of the FOP. Monte Carlo simulations of a 160 MeV proton beam incident on a homogeneous PMMA phantom were performed using GATE. The Compton camera consisted of a silicon-based scatterer and CeBr₃scintillator absorber. The temporal resolution of the detection system (absorber + beam trigger) was varied between 0.1 and 1.3 ns rms and a TOF-based discrimination method applied to eliminate unlikely solution(s) from the line-cone reconstruction. The FOP was obtained for varying temporal resolutions and its precision obtained from its shift across 100 independentγemission profiles compared to a high statistics reference profile. The optimal temporal resolution for the given camera geometry and 10⁸primary protons was 0.2 ns where a precision of 2.30 ± 0.15 mm (1σ) on the FOP was found. This precision is comparable to current state-of-the-art Compton imaging using iterative reconstruction methods or 1D imaging with mechanically collimated devices, and satisfies the requirement of being smaller than the clinical safety margins.