CMOS flat panel detectors(FPD) have steadily gained acceptance into various medical imaging application over the last several years. Recently, major-medical OEMs incorporate CMOS FPDs (CFPD) into their product portfolios, alongside existing a-Si FPD(aSiFPD) systems. The superior mobility of crystalline silicon vs. amorphous silicon, give CMOS sensors some advantages over a-Si sensors. Specifically, CMOS sensors incorporate smaller pixels, with active circuitry built into each pixel. These features allow small CMOS pixels to achieve SNR comparable to larger a-Si pixels, while operating at faster frame rates and lower entrance exposure. High resolution and low dose performance is an enabling technology for certain types of imaging tasks, for example neurovascular imaging. However, to achieve a large area field of view (FOV) required by many medical imaging applications, multiple CMOS sensors must be tiled to form a large area FPD. Incorporating multiple tiles into a large area FPD increases both cost and complexity of the imaging system. Therefore, CMOS detectors are ideally suited for imaging tasks with low dose and high resolution requirements. While a-Si FPDS are suited for imaging tasks requiring higher dose and low to medium resolution such as cardiac imaging. In this work, we incorporate scientific imaging metrics, such as DQE, MTF, and CF, at RQA5 beam quality to assess the overall performance of CMOS FPDs and a-Si FPDs. The detectors evaluated in this study are the Varex CMOS 3131 (150um pixel), CMOS 1512 (74.8um pixel) and Varex a-Si 3030X (194um pixel). The large pixels incorporate a 700um CsI(Tl) scintillator, while the smaller pixel has 600um CsI(Tl) scintillator. In addition to fundamental detector performance assessments, we propose to include a quantitative measurement of the “imaging task” by analyzing the Artinis CDRAD phantom and CD Analyzer program to determine the contrast-detail curve. We demonstrate this methodology to be a useful and practical metric in selecting the appropriate detector technology based on the requirements of the imaging applications. To truly leverage the benefits of CMOS technology, a smaller pixel size should be used for imaging tasks related to neurovascular imaging, whereas a larger a-Si pixel is sufficient for an imaging task related to cardiology. The DQE imaging metric shows that the larger pixel CMOS detector is better suited for imaging midle resolution structures in the frequency range of 1.8-3.3 cycles/mm, while the smaller pixel excels at 2.5-6.5 cycles/mm. Whereas, the a-Si detector performs best in the frequency range of 0 - 1.2 cycles/mm. Future experiments shall include comparing smaller pixels of both a-Si and CMOS detectors, 83um and 74.8um, respectively. In addition, these experiments shall be repeated comparing 100um CMOS detector with the large area 100um based Varex IGZO FPDs, available in 2019. IGZO technology is being introduced to allow a-Si based imagers to achieve smaller pixels and better low dose performance without the added complexity and cost of CMOS FPD technology.
Dual Energy (DE) imaging has been widely used in digital radiography and fluoroscopy, as has dual energy CT for various medical applications. In this study, the imaging performance of a dynamic dual-layer a-Si flat panel detector (FPD) prototype was characterized for dual energy imaging tasks. Dual energy cone beam CT (DE CBCT) scans were acquired and used to perform material decomposition in the projection domain, followed by reconstruction to generate material specific and virtual monoenergetic (VM) images. The dual-layer FPD prototype was built on a Varex XRD 4343RF detector by adding a 200 μm thick CsI scintillator and a-Si panel of 150 μm pixel size on top as a low energy detector. A 1 mm copper filter was added as a middle layer to increase energy separation with the bottom layer as a high energy detector. The imaging performance, such as Modulation Transfer Function (MTF), Conversion Factor (CF), and Detector Quantum Efficiency (DQE) of both the top and bottom detector layers were characterized and compared with those of the standard single layer XRD4343 RF detector. Several tissue equivalent cylinders (solid water, liquid water, bone, acrylic, polyethylene, etc.) were placed on a rotating stand, and two separate 450-projection CBCT scans were performed under continuous 120 kV and 80 kV X-ray beams. After an empirical material decomposition calibration, water and bone images were generated for each projection, and their respective volumes were reconstructed using Varex’s CBCT Software Tools (CST 2.0). A VM image, which maximized the contrast-to-noise ratio of water to polyethylene, was generated based on the water and bone images. The MTF at 1.0 lp/mm from the low energy detector was 32% and 22% higher than the high energy detector and the standard detector, respectively; the DQE of both high and low energy detectors is much lower than that of the standard XRD 4343RF detector. The CNR of water to polyethylene from the VM image improved by 50% over that from the low energy image alone at 120 kV, and by 80% at 80 kV. This study demonstrates the feasibility of using a dual-layer FPD in applications such as DE CBCT for contrast enhancement and material decomposition. Further evaluations are underway.