Microcolumnar CsI:Tl scintillator screens have been the gold standard in X-ray imaging for many years due to their high density, high atomic number, and scintillation efficiency. The structured screens provide an improvement in performance by channeling the light to the detector, improving detection efficiency and spatial resolution. We have taken this concept a step further by laser-machining the CsI:Tl scintillator to provide pixels that match the detector pixels. This allows for still thicker CsI:Tl layers up to 700 μm pixelated with pitch of 100 μm to match CMOS flat panel pixels, thus improving X-ray absorption and resolution. We are investigating the applications of CMOS detectors with pixelated scintillators for imaging of bone microarchitecture on diagnostic Cone Beam CT (CBCT) systems to provide improved quantitative metrics for diagnosis of osteoporosis and osteoarthritis. <p> </p>The scintillator design includes reflective coatings applied to the laser-cut grooves to improve optical isolation between pixels. Such coatings are created by atomic layer deposition (ALD), a unique approach, which permits formation of reflectors over inter-pixel grooves with aspect ratios as high as 140:1. Here we present initial results quantifying performance gains in CMOS detector resolution and their impact on the quality of bone microstructure segmentation. We demonstrate 77% gain in spatial resolution at 2 lp/mm and extension of the limiting resolution from 3 lp/mm to 4.5 lp/mm for the CMOS detector with a pixelated screen compared to a commercial sensor. In a bench-top CBCT study emulating diagnostic systems for orthopedic applications (extremity CBCT), we achieved >0.75 correlations in metrics of trabecular microarchitecture between pixelated CsI:Tl based CBCT and gold-standard micro-CT. The pixelated scintillator is expected to have significant impact for many other applications including mammography and digital radiography, where resolution and dose efficiency (DQE) of the detector are of critical importance.
Purpose: To evaluate the performance of a novel ultra-high resolution multi-detector CT scanner (Canon Aquilion Precision UHR CT), capable of visualizing ~150 μm details, in quantitative assessment of bone microarchitecture. Compared to conventional CT, the spatial resolution of UHR CT begins to approach the size of the trabeculae. This might enable measurements of microstructural correlates of osteoporosis, osteoarthritis, and other bone disease. Methods: The UHR CT system features a 160-row x-ray detector with 250x250 μm pixels (measured at isocenter) and a custom-designed x-ray source with a 0.4x0.5 mm focal spot. Visualization of high contrast details down to ~150 μm has been achieved on this device, which is now commercially available for clinical use. To evaluate the performance of UHR CT in quantification of bone microstructure, we imaged a variety of human bone samples (including ulna, hamate, radius, and vertebrae) embedded in a ~16 cm diameter plastic cylinder and in an anthropomorphic thorax phantom (QRM-Thorax, QRM Gmbh). Helical UHR CT acquisitions (120 kVp tube voltage) were acquired at scan exposures of 375 mAs - 5 mAs. For comparison, the samples were also imaged using a Normal Resolution (NR) mode available on the scanner, involving 500 μm slice thickness, exposure of 50 mAs, and a focal spot of 0.6x1.3 mm. We obtained micro-CT (μCT) of the bone samples at ~28 μm voxel size as a gold-standard reference. Geometric measurements of bone microstructure were performed in 17 regions-of-interests (ROIs) distributed throughout the bones of the phantoms; image registration was used to place the ROIs at corresponding locations in the UHR CT and NR CT. Trabecular thickness Tb.Th, spacing Tb.Sp, and Bone Volume fraction BvTv were obtained. The UHR and NR imaging protocols were compared terms of correlations to μCT and error of trabecular measurements. The effect of dose on trabecular morphometry was also studied for the UHR CT. Furthermore, we evaluated the sensitivity of texture features of trabecular bone (recently proposed as an alternative to geometric indices of microstructure) to imaging protocol. Image texture evaluation was performed using ~150 regions of interest (ROIs) across all bone samples. Three-dimensional Gray Level Co-occurrence Matrix (GLCM) and Gray Level Run Length Matrix (GLRM) features were extracted for each ROI. We analyzed correlation and concordance correlation coefficient (CCC) of the mean ROI values of texture features obtained using the UHR and NR modes. Results: UHR CT reconstructions of bone samples clearly demonstrated improved visualization of the trabeculae compared to NR CT. UHR CT achieved substantially better correlations for all three metrics of bone microstructure, in particular for BvTv (correlation coefficient of 0.91 for UHR CT compared to 0.84 for NR CT) and TbSp (correlation of 0.74 for UHR CT and 0.047 for NR CT). The error obtained with UHR CT was generally smaller than that of NR CT. For TbSp, the mean deviation from CT (averaged across all bone samples) was only ~0.07 for UHR CT, compared to 0.25 for NR CT. Analysis of reproducibility of texture features of trabecular bone between UHR CT and NR CT revealed fair correlations (<0.7) for the majority of GLCM features, but relatively poor CCC (e.g. 0.02 for Energy and 0.04 for Entropy). The magnitude of texture metrics is particularly affected by the enhanced spatial resolution of UHR CT. Conclusion: The recently introduced UHR CT achieves improved correlation and reduced error in measurements of trabecular bone microstructure compared to conventional resolution CT. Future development of diagnostic strategies based on textural biomarkers derived from UHR CT will need to account for potential sensitivity of texture features to image resolution.