We have developed a novel method for fast image simulation of flat panel detectors, based on the photon energy deposition efficiency and the optical spread function (OSF). The proposed method, FastEPID, determines the photon detection using photon energy deposition and replaces particle transport within the detector with precalculated OSFs. The FastEPID results are validated against experimental measurement and conventional Monte Carlo simulation in terms of modulation transfer function (MTF), signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), contrast, and relative difference of pixel value, obtained with a slanted slit image, Las Vegas phantom, and anthropomorphic pelvis phantom. Excellent agreement is observed between simulation and measurement in all cases. Without degrading image quality, the FastEPID method is capable of reducing simulation time up to a factor of 150. Multiple applications, such as imager design optimization for planar and volumetric imaging, are expected to benefit from the implementation of the FastEPID method.

Megavoltage (MV) cone-beam computed tomography (CBCT) using an electronic portal imaging (EPID) offers advantageous features, including 3D mapping, treatment beam registration, high-z artifact suppression, and direct radiation dose calculation. Adoption has been slowed by image quality limitations and concerns about imaging dose. Developments in imager design, including pixelated scintillators, structured phosphors, inexpensive scintillation materials, and multi-layer imager (MLI) architecture have been explored to improve EPID image quality and reduce imaging dose. The present study employs a hybrid Monte Carlo and linear systems model to determine the effect of detector design elements, such as multi-layer architecture and scintillation materials. We follow metrics of image quality including modulation transfer function (MTF) and noise power spectrum (NPS) from projection images to 3D reconstructions to in-plane slices and apply a task based figure-of-merit, the ideal observer signal-to-noise ratio (d') to determine the effect of detector design on object detectability. Generally, detectability was limited by detector noise performance. Deploying an MLI imager with a single scintillation material for all layers yields improvement in noise performance and d' linear with the number of layers. In general, improving x-ray absorption using thicker scintillators results in improved DQE(0). However, if light yield is low, performance will be affected by electronic noise at relatively high doses, resulting in rapid image quality degradation. Maximizing image quality in a heterogenous MLI detector (i.e. multiple different scintillation materials) is most affected by limiting total noise. However, while a second-order effect, maximizing total spatial resolution of the MLI detector is a balance between the intensity contribution of each layer against its individual MTF. So, while a thinner scintillator may yield a maximal individual-layer MTF, its quantum efficiency will be relatively low in comparison to a thicker scintillator and thus, intensity contribution may be insufficient to noticeably improve the total detector MTF.

Electronic portal imaging devices (EPIDs) lend themselves to beams-eye view clinical applications, such as tumor tracking, but are limited by low contrast and detective quantum efficiency (DQE). We characterize a novel EPID prototype consisting of multiple layers and investigate its suitability for use under clinical conditions. A prototype multi-layer imager (MLI) was constructed utilizing four conventional EPID layers, each consisting of a copper plate, a Gd2O2S:Tb phosphor scintillator, and an amorphous silicon flat panel array detector. We measured the detector’s response to a 6 MV photon beam with regards to modulation transfer function, noise power spectrum, DQE, contrast-to-noise ratio (CNR), signal-to-noise ratio (SNR), and the linearity of the detector’s response to dose. Additionally, we compared MLI performance to the single top layer of the MLI and the standard Varian AS-1200 detector. Pre-clinical imaging was done on an anthropomorphic phantom, and the detector’s CNR, SNR and spatial resolution were assessed in a clinical environment. Images obtained from spine and liver patient treatment deliveries were analyzed to verify CNR and SNR improvements. The MLI has a DQE(0) of 9.7%, about 5.7 times the reference AS-1200 detector. Improved noise performance largely drives the increase. CNR and SNR of clinical images improved three-fold compared to reference. A novel MLI was characterized and prepared for clinical translation. The MLI substantially improved DQE and CNR performance while maintaining the same resolution. Pre-clinical tests on an anthropomorphic phantom demonstrated improved performance as predicted theoretically. Preliminary patient data were analyzed, confirming improved CNR and SNR. Clinical applications are anticipated to include more accurate soft tissue tracking.

We assess the feasibility of clinical megavoltage (MV) spectral imaging for material and bone separation with a novel multi-layer imager (MLI) prototype. The MLI provides higher detective quantum efficiency and lower noise than conventional electronic portal imagers. Simulated experiments were performed using a validated Monte Carlo model of the MLI to estimate energy absorption and energy separation between the MLI components. Material separation was evaluated experimentally using solid water and aluminum (Al), copper (Cu) and gold (Au) for 2.5 MV, 6 MV and 6 MV flattening filter free (FFF) clinical photon beams. An anthropomorphic phantom with implanted gold fiducials was utilized to further demonstrate bone/gold separation. Weighted subtraction imaging was employed for material and bone separation. The weighting factor (w) was iteratively estimated, with the optimal w value determined by minimization of the relative signal difference (ΔSR) and signal-difference-to-noise ratio (SDNR) between material (or bone) and the background. Energy separation between layers of the MLI was mainly the result of beam hardening between components with an average energy separation between 34 and 47 keV depending on the x-ray beam energy. The minimum average energy of the detected spectrum in the phosphor layer was 123 keV in the top layer of the MLI with the 2.5 MV beam. The w values that minimized ΔSR and SDNR for Al, Cu and Au were 0.89, 0.76 and 0.64 for 2.5 MV; for 6 MV FFF, w was 0.98, 0.93 and 0.77 respectively. Bone suppression in the anthropomorphic phantom resulted in improved visibility of the gold fiducials with the 2.5 MV beam. Optimization of the MLI design is required to achieve optimal separation at clinical MV beam energies.

While megavoltage cone-beam computed tomography (CBCT) using an electronic portal imaging device (EPID) provides many advantages over kilovoltage (kV) CBCT, clinical adoption is limited by its high doses. Multi-layer imager (MLI) EPIDs increase DQE(0) while maintaining high resolution. However, even well-designed, high-performance MLIs suffer from increased electronic noise from each readout, degrading low-dose image quality. To improve low-dose performance, shift-and-bin addition (ShiBA) imaging is proposed, leveraging the unique architecture of the MLI. ShiBA combines hardware readout-binning and super-resolution concepts, reducing electronic noise while maintaining native image sampling. The imaging performance of full-resolution (FR); standard, aligned binned (BIN); and ShiBA images in terms of noise power spectrum (NPS), electronic NPS, modulation transfer function (MTF), and the ideal observer signal-to-noise ratio (SNR)-the detectability index (d')-are compared. The FR 4-layer readout of the prototype MLI exhibits an electronic NPS magnitude 6-times higher than a state-of-the-art single layer (SLI) EPID. Although the MLI is built on the same readout platform as the SLI, with each layer exhibiting equivalent electronic noise, the multi-stage readout of the MLI results in electronic noise 50% higher than simple summation. Electronic noise is mitigated in both BIN and ShiBA imaging, reducing its total by ~12 times. ShiBA further reduces the NPS, effectively upsampling the image, resulting in a multiplication by a sinc function. Normalized NPS show that neither ShiBA nor BIN otherwise affects image noise. The LSF shows that ShiBA removes the pixilation artifact of BIN images and mitigates the effect of detector shift, but does not quantifiably improve the MTF. ShiBA provides a pre-sampled representation of the images, mitigating phase dependence. Hardware binning strategies lower the quantum noise floor, with 2  ×  2 implementation reducing the dose at which DQE(0) degrades by 10% from 0.01 MU to 0.004 MU, representing 20% improvement in d'.