Uncertainty analysis of a Compton camera imaging system for radiation therapy dose reconstruction

Design of 4π Directional Radiation Detector based on Compton Scattering Effect

Obtaining directional information is required in many applications such as nuclear homeland security, contamination mapping after a nuclear incident and radiological events, or during the decontamination work. However, many directional radiation detectors are based on directional shielding, made of lead or tungsten collimators, introducing two main drawbacks. The first is the size and weight, making those detectors too heavy and irrelevant for utilization in handheld devices, drone mapping, or space applications. The second drawback is the limited field of view, which requires multiple detectors to cover the whole required field of view or machinery to rotate the narrow field of view detector. We propose a novel 4π directional detector based on a segmented hollow cubic detector, which uses the Compton effect interactions with no heavy collimators. The symmetrical cubical design provides both higher efficiency and 4π detection ability. Instead of traditional two types of detectors (scatterer and absorber) structure, we use the same type of detector, based on GAGG(Ce) scintillator coupled to silicon photomultiplier. Additional advantage of the proposed detector obtained by locating the photon sensors inside the detector, behind the scintillators, which improves the radiation hardness required for space applications. Furthermore, such arrangement flattens the temperature variation across the detector, providing better gain stability. The main advantage of the proposed detector is the ability of 4pi radiation detection for high energy gamma-rays without the use of heavy collimators.

Characterization of Compton-scatter imaging with an analytical simulation method

By collimating the photons scattered when a megavoltage therapy beam interacts with the patient, a Compton-scatter image may be formed without the delivery of an extra dose. To characterize and assess the potential of the technique, an analytical model for simulating scatter images was developed and validated against Monte Carlo (MC). For three phantoms, the scatter images collected during irradiation with a 6 MV flattening-filter-free therapy beam were simulated. Images, profiles, and spectra were compared for different phantoms and different irradiation angles. The proposed analytical method simulates accurate scatter images up to 1000 times faster than MC. Minor differences between MC and analytical simulated images are attributed to limitations in the isotropic superposition/convolution algorithm used to analytically model multiple-order scattering. For a detector placed at 90° relative to the treatment beam, the simulated scattered photon energy spectrum peaks at 140-220 keV, and 40-50% of the photons are the result of multiple scattering. The high energy photons originate at the beam entrance. Increasing the angle between source and detector increases the average energy of the collected photons and decreases the relative contribution of multiple scattered photons. Multiple scattered photons cause blurring in the image. For an ideal 5 mm diameter pinhole collimator placed 18.5 cm from the isocenter, 10 cGy of deposited dose (2 Hz imaging rate for 1200 MU min^-1 treatment delivery) is expected to generate an average 1000 photons per mm² at the detector. For the considered lung tumor CT phantom, the contrast is high enough to clearly identify the lung tumor in the scatter image. Increasing the treatment beam size perpendicular to the detector plane decreases the contrast, although the scatter subject contrast is expected to be greater than the megavoltage transmission image contrast. With the analytical method, real-time tumor tracking may be possible through comparison of simulated and acquired patient images.

Feasibility Studies of a New Event Selection Method to Improve Spatial Resolution of Compton Imaging for Medical Applications

A Compton imaging method for medical applications that includes new energy determination and data filtering techniques has been tested using several point sources with known emission lines. Using a prototype Compton camera, a distance-of-closest approach technique has been employed to determine the initial energy of the incoming γs and to ensure the reconstructed source position is within an acceptable distance from the known γ source location. Further analysis is done by implementing a Compton line filtering technique, keeping only those interactions whose deposited energy in the first interaction matches the theoretical energy deposition predicted by the Compton equation. Using this new event filtering method, we see improvements in the full width at half maximum in the lateral profiles of γ point sources of up to 70% over standard Compton imaging methods, as well as achievable spatial resolutions in the reconstructed images of better than 2 mm. In addition, this new Compton imaging method was able to reconstruct an extended source of γ rays emitted during irradiation of a water tank with a clinical proton radiotherapy beam.

The effects of Doppler broadening and detector resolution on the performance of three-stage Compton cameras

PURPOSE

The authors investigated how the characteristics of the detectors used in a three-stage Compton camera (CC) affect the CC's ability to accurately measure the emission distribution and energy spectrum of prompt gammas (PG) emitted by nuclear de-excitations during proton therapy. The detector characteristics they studied included the material (high-purity germanium [HPGe] and cadmium zinc telluride [CZT]), Doppler broadening (DB), and resolution (lateral, depth, and energy).

METHODS

The authors simulated three-stage HPGe and CZT CCs of various configurations, detecting gammas from point sources with energies ranging from 0.511 to 7.12 MeV. They also simulated a proton pencil beam irradiating a tissue target to study how the detector characteristics affect the PG data measured by CCs in a clinical proton therapy setting. They used three figures of merit: the distance of closest approach (DCA) and the point of closest approach (PCA) between the measured and actual position of the PG emission origin, and the calculated energy resolution.

RESULTS

For CCs with HPGe detectors, DB caused the DCA to be greater than 3 mm for 14% of the 6.13 MeV gammas and 20% of the 0.511 MeV gammas. For CCs with CZT detectors, DB caused the DCA to be greater than 3 mm for 18% of the 6.13 MeV gammas and 25% of the 0.511 MeV gammas. The full width at half maximum (FWHM) of the PCA in the ẑ direction for HPGe and CZT detectors ranged from 1.3 to 0.4 mm for gammas with incident energy ranging from 0.511 to 7.12 MeV. For CCs composed of HPGe detectors, the resolution of incident gamma energy calculated by the CC ranged from 6% to 1% for gammas with true incident energies from 0.511 to 7.12 MeV. For CCs composed of CZT detectors, the resolution of gamma energy calculated by the CC ranged from 10% to 1% for gammas with true incident energies from 0.511 to 7.12 MeV. For HPGe and CZT CCs in which all detector effect were included, the DCA was less than 3 mm for 75% and 68% of the detected gammas, respectively, and restricting gammas to those having energy greater than 2.0 MeV increased these percentages to 83% and 77% for HPGe and CZT, respectively. Distributions of the true gamma origins and the PCA after detector characteristics had been included showed good agreement on beam range and some loss of resolution for the lateral profile of the PG emission. Characteristic energy lines were evident in the calculated gamma energy spectrum.

CONCLUSIONS

The authors found the following: (1) DB is the dominant source of spatial and energy resolution loss in the CCs at all energy levels; (2) the largest difference in the spatial resolution of HPGe and CZT CCs is that the spatial resolution distributions of CZT have broader tails. The differences in the FWHM of these distributions are small; (3) the energy resolution of both HPGe and CZT three-stage CCs is adequate for PG spectroscopy; and (4) restricting the gammas to those having energy greater than 2.0 MeV can improve the achievable image resolution.

Evaluation of a stochastic reconstruction algorithm for use in Compton camera imaging and beam range verification from secondary gamma emission during proton therapy

In this paper, we study the feasibility of using the stochastic origin ensemble (SOE) algorithm for reconstructing images of secondary gammas emitted during proton radiotherapy from data measured with a three-stage Compton camera. The purpose of this study was to evaluate the quality of the images of the gamma rays emitted during proton irradiation produced using the SOE algorithm and to measure how well the images reproduce the distal falloff of the beam. For our evaluation, we performed a Monte Carlo simulation of an ideal three-stage Compton camera positioned above and orthogonal to a proton pencil beam irradiating a tissue phantom. Scattering of beam protons with nuclei in the phantom produces secondary gamma rays, which are detected by the Compton camera and used as input to the SOE algorithm. We studied the SOE reconstructed images as a function of the number of iterations, the voxel probability parameter, and the number of detected gammas used by the SOE algorithm. We quantitatively evaluated the capabilities of the SOE algorithm by calculating and comparing the normalized mean square error (NMSE) of SOE reconstructed images. We also studied the ability of the SOE reconstructed images to predict the distal falloff of the secondary gamma production in the irradiated tissue. Our results show that the images produced with the SOE algorithm converge in ~10,000 iterations, with little improvement to the image NMSE for iterations above this number. We found that the statistical noise of the images is inversely proportional to the ratio of the number of gammas detected to the SOE voxel probability parameter value. In our study, the SOE predicted distal falloff of the reconstructed images agrees with the Monte Carlo calculated distal falloff of the gamma emission profile in the phantom to within ±0.6 mm for the positions of maximum emission (100%) and 90%, 50% and 20% distal falloff of the gamma emission profile. We conclude that the SOE algorithm is an effective method for reconstructing images of a proton pencil beam from the data collected by an ideal Compton camera and that these images accurately model the distal falloff of secondary gamma emission during proton irradiation.

An accelerated threshold-based back-projection algorithm for compton camera image reconstruction

PURPOSE

Compton camera imaging (CCI) systems are currently under investigation for radiotherapy dose reconstruction and verification. The ability of such a system to provide real-time images during dose delivery will be limited by the computational speed of the image reconstruction algorithm. In this work, the authors present a fast and simple method by which to generate an initial back-projected image from acquired CCI data, suitable for use in a filtered back-projection algorithm or as a starting point for iterative reconstruction algorithms, and compare its performance to the current state of the art.

METHODS

Each detector event in a CCI system describes a conical surface that includes the true point of origin of the detected photon. Numerical image reconstruction algorithms require, as a first step, the back-projection of each of these conical surfaces into an image space. The algorithm presented here first generates a solution matrix for each slice of the image space by solving the intersection of the conical surface with the image plane. Each element of the solution matrix is proportional to the distance of the corresponding voxel from the true intersection curve. A threshold function was developed to extract those pixels sufficiently close to the true intersection to generate a binary intersection curve. This process is repeated for each image plane for each CCI detector event, resulting in a three-dimensional back-projection image. The performance of this algorithm was tested against a marching algorithm known for speed and accuracy.

RESULTS

The threshold-based algorithm was found to be approximately four times faster than the current state of the art with minimal deficit to image quality, arising from the fact that a generically applicable threshold function cannot provide perfect results in all situations. The algorithm fails to extract a complete intersection curve in image slices near the detector surface for detector event cones having axes nearly parallel to the image plane. This effect decreases the sum of the image, thereby also affecting the mean, standard deviation, and SNR of the image. All back-projected events associated with a simulated point source intersected the voxel containing the source and the FWHM of the back-projected image was similar to that obtained from the marching method.

CONCLUSIONS

The slight deficit to image quality observed with the threshold-based back-projection algorithm described here is outweighed by the 75% reduction in computation time. The implementation of this method requires the development of an optimum threshold function, which determines the overall accuracy of the method. This makes the algorithm well-suited to applications involving the reconstruction of many large images, where the time invested in threshold development is offset by the decreased image reconstruction time. Implemented in a parallel-computing environment, the threshold-based algorithm has the potential to provide real-time dose verification for radiation therapy.