An ultra-high resolution (UHR) mode, with a detector pixel size of 0.25 mm×0.25 mm relative to isocenter, has been implemented on a whole body research photon-counting detector (PCD) computed tomography (CT) system. Twenty synthetic lung nodules were scanned using UHR and conventional resolution (macro) modes and reconstructed with medium and very sharp kernels. Linear regression was used to compare measured nodule volumes from CT images to reference volumes. The full-width-at-half-maximum of the calculated curvature histogram for each nodule was used as a shape index, and receiver operating characteristic analysis was performed to differentiate sphere- and star-shaped nodules. Results showed a strong linear relationship between measured nodule volumes and reference volumes for both modes. The overall volume estimation was more accurate using UHR mode and the very sharp kernel, having 4.8% error compared with 10.5% to 12.6% error in the macro mode. The improvement in volume measurements using the UHR mode was more evident for small nodule sizes or star-shaped nodules. Images from the UHR mode with the very sharp kernel consistently demonstrated the best performance [AUC=(0.839,0.867)] for separating star- from sphere-shaped nodules, showing advantages of UHR mode on a PCD CT scanner for lung nodule characterization.
A new ultra high-resolution (UHR) mode has been implemented on a whole body photon counting-detector (PCD) CT system. The UHR mode has a pixel size of 0.25 mm by 0.25 mm at the iso-center, while the conventional (macro) mode is limited to 0.5 mm by 0.5 mm. A set of synthetic lung nodules (two shapes, five sizes, and two radio-densities) was scanned using both the UHR and macro modes and reconstructed with 2 reconstruction kernels (4 sets of images in total). Linear regression analysis was performed to compare measured nodule volumes from CT images to reference volumes. Surface curvature was calculated for each nodule and the full width half maximum (FWHM) of the curvature histogram was used as a shape index to differentiate sphere and star shape nodules. Receiver operating characteristic (ROC) analysis was performed and area under the ROC curve (AUC) was used as a figure of merit for the differentiation task. Results showed strong linear relationship between measured nodule volume and reference standard for both UHR and macro mode. For all nodules, volume estimation was more accurate using UHR mode with sharp kernel (S80f), with lower mean absolute percent error (MAPE) (6.5%) compared with macro mode (11.1% to 12.9%). The improvement of volume measurement from UHR mode was more evident particularly for small nodule size (3mm, 5mm), or star-shape nodules. Images from UHR mode with sharp kernel (S80f) consistently demonstrated the best performance (AUC = 0.85) when separating star from sphere shape nodules among all acquisition and reconstruction modes. Our results showed the advantages of UHR mode on a PCD CT scanner in lung nodule characterization. Various clinical applications, including quantitative imaging, can benefit substantially from this high resolution mode.
In addition to the standard-resolution (SR) acquisition mode, a high-resolution (HR) mode is available on a research photon-counting-detector (PCD) whole-body CT system. In the HR mode each detector consists of a 2x2 array of 0.225 mm x 0.225 mm subpixel elements. This is in contrast to the SR mode that consists of a 4x4 array of the same subelements, and results in 0.25 mm isotropic resolution at iso-center for the HR mode. In this study, we quantified ex vivo the capabilities of the HR mode to characterize renal stones in terms of morphology and mineral composition. Forty pure stones - 10 uric acid (UA), 10 cystine (CYS), 10 calcium oxalate monohydrate (COM) and 10 apatite (APA) - and 14 mixed stones were placed in a 20 cm water phantom and scanned in HR mode, at radiation dose matched to that of routine dual-energy stone exams. Data from micro CT provided a reference for the quantification of morphology and mineral composition of the mixed stones. The area under the ROC curve was 1.0 for discriminating UA from CYS, 0.89 for CYS vs COM and 0.84 for COM vs APA. The root mean square error (RMSE) of the percent UA in mixed stones was 11.0% with a medium-sharp kernel and 15.6% with the sharpest kernel. The HR showed qualitatively accurate characterization of stone morphology relative to micro CT.
Two ultra-high-resolution (UHR) imaging modes, each with two energy thresholds, were implemented on a research, whole-body photon-counting-detector (PCD) CT scanner, referred to as sharp and UHR, respectively. The UHR mode has a pixel size of 0.25 mm at iso-center for both energy thresholds, with a collimation of 32 × 0.25 mm. The sharp mode has a 0.25 mm pixel for the low-energy threshold and 0.5 mm for the high-energy threshold, with a collimation of 48 × 0.25 mm. Kidney stones with mixed mineral composition and lung nodules with different shapes were scanned using both modes, and with the standard imaging mode, referred to as macro mode (0.5 mm pixel and 32 × 0.5 mm collimation). Evaluation and comparison of the three modes focused on the ability to accurately delineate anatomic structures using the high-spatial resolution capability and the ability to quantify stone composition using the multi-energy capability. The low-energy threshold images of the sharp and UHR modes showed better shape and texture information due to the achieved higher spatial resolution, although noise was also higher. No noticeable benefit was shown in multi-energy analysis using UHR compared to standard resolution (macro mode) when standard doses were used. This was due to excessive noise in the higher resolution images. However, UHR scans at higher dose showed improvement in multi-energy analysis over macro mode with regular dose. To fully take advantage of the higher spatial resolution in multi-energy analysis, either increased radiation dose, or application of noise reduction techniques, is needed.
Photon-counting detectors in computed tomography (CT) allow for measuring the energy of the incident xray photons within certain energy windows. This information can be used to enhance contrast or reconstruct CT images of different material bases. Compared to energy-integrating CT-detectors, pixel dimensions have to be smaller to limit the negative effect of pulse pile-up at high X-ray fluxes. Unfortunately, reducing the pixel size leads to increased K-escape and charge sharing effects. As a consequence, an incident X-ray may generate more than one detector signal, and with deteriorated energy information. In earlier simulation studies it has been shown that these limitations can be mitigated by optimizing the X-ray spectrum using K-edge pre-filtration. In the current study, we have used a whole-body research CT scanner with a high-flux capable photon-counting detector, in which for the first time a pre-patient hafnium filter was installed. Our measurement results demonstrate substantial improvement of the material decomposition capability at comparable dose levels. The results are in agreement with the predictions provided in simulations.
This study evaluates the capabilities of a whole-body photon counting CT system to differentiate between four
common kidney stone materials, namely uric acid (UA), calcium oxalate monohydrate (COM), cystine (CYS),
and apatite (APA) ex vivo. Two different x-ray spectra (120 kV and 140 kV) were applied and two acquisition
modes were investigated. The macro-mode generates two energy threshold based image-volumes and two energy
bin based image-volumes. In the chesspattern-mode four energy thresholds are applied. A virtual low energy
image, as well as a virtual high energy image are derived from initial threshold-based images, while considering
their statistically correlated nature. The energy bin based images of the macro-mode, as well as the virtual
low and high energy image of the chesspattern-mode serve as input for our dual energy evaluation. The dual
energy ratio of the individually segmented kidney stones were utilized to quantify the discriminability of the
different materials. The dual energy ratios of the two acquisition modes showed high correlation for both applied
spectra. Wilcoxon-rank sum tests and the evaluation of the area under the receiver operating characteristics
curves suggest that the UA kidney stones are best differentiable from all other materials (AUC = 1.0), followed
by CYS (AUC ≈ 0.9 compared against COM and APA). COM and APA, however, are hardly distinguishable
(AUC between 0.63 and 0.76). The results hold true for the measurements of both spectra and both acquisition
modes.
The energy resolving capabilities of Photon Counting Detectors (PCD) in Computed Tomography (CT) facilitate energy-sensitive measurements. The provided image-information can be processed with Dual Energy and Multi Energy algorithms. A research PCD-CT firstly allows acquiring images with a close to clinical configuration of both the X-ray tube and the CT-detector. In this study, two algorithms (Material Decomposition and Virtual Non-Contrast-imaging (VNC)) are applied on a data set acquired from an anesthetized rabbit scanned using the PCD-CT system. Two contrast agents (CA) are applied: A gadolinium (Gd) based CA used to enhance contrasts for vascular imaging, and xenon (Xe) and air as a CA used to evaluate local ventilation of the animal's lung. Four different images are generated: a) A VNC image, suppressing any traces of the injected Gd imitating a native scan, b) a VNC image with a Gd-image as an overlay, where contrast enhancements in the vascular system are highlighted using colored labels, c) another VNC image with a Xe-image as an overlay, and d) a 3D rendered image of the animal's lung, filled with Xe, indicating local ventilation characteristics. All images are generated from two images based on energy bin information. It is shown that a modified version of a commercially available dual energy software framework is capable of providing images with diagnostic value obtained from the research PCD-CT system.
Photon counting detectors in computed tomography facilitate measurements of spectral distributions of detected X-ray quanta in discrete energy bins. Along with the dependency on wavelength and atomic number of the mass attenuation coefficient, this information allows for reconstruction of CT images of different material bases. Decomposition of two materials is considered standard in today’s dual-energy techniques. With photon-counting detectors the decomposition of more than two materials becomes achievable. Efficient detection of CT-typical X-ray spectra is a hard requirement in a clinical environment. This is fulfilled by only a few sensor materials such as CdTe or CdZnTe. In contrast to energy integrating CT-detectors, the pixel dimensions must be reduced to avoid pulse pile-up problems at clinically relevant count rates. However, reducing pixel sizes leads to increased K-escape and charge sharing effects. As a consequence, the correlation between incident and detected X-ray energy is reduced. This degradation is quantified by the detector response function. The goal of this study is to improve the achievable material decomposition by adapting the incident X-ray spectrum with respect to the properties (i.e. the detector response function) of a photon counting detector. A significant improvement of a material decomposition equivalent metric is achievable when using specific materials as X-ray pre-filtration (K-edge filtering) while maintaining the applied patient dose and image quality.
X-ray computed tomography (CT) with energy-discriminating capabilities presents exciting opportunities for increased dose efficiency and improved material decomposition analyses. However, due to constraints imposed by the inability of photon-counting detectors (PCD) to respond accurately at high photon flux, to date there has been no clinical application of PCD-CT. Recently, our lab installed a research prototype system consisting of two x-ray sources and two corresponding detectors, one using an energy-integrating detector (EID) and the other using a PCD. In this work, we report the first third-party evaluation of this prototype CT system using both phantoms and a cadaver head. The phantom studies demonstrated several promising characteristics of the PCD sub-system, including improved longitudinal spatial resolution and reduced beam hardening artifacts, relative to the EID sub-system. More importantly, we found that the PCD sub-system offers excellent pulse pileup control in cases of x-ray flux up to 550 mA at 140 kV, which corresponds to approximately 2.5×1011 photons per cm2 per second. In an anthropomorphic phantom and a cadaver head, the PCD sub-system provided image quality comparable to the EID sub-system for the same dose level. Our results demonstrate the potential of the prototype system to produce clinically-acceptable images in vivo.
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