The clinical application of Gemstone Spectral ImagingTM, a fast kV switching dual energy acquisition, is explored in the
context of noninvasive kidney stone characterization. Utilizing projection-based material decomposition, effective
atomic number and monochromatic images are generated for kidney stone characterization. Analytical and experimental
measurements are reported and contrasted. Phantoms were constructed using stone specimens extracted from patients.
This allowed for imaging of the different stone types under similar conditions. The stone specimens comprised of Uric
Acid, Cystine, Struvite and Calcium-based compositions. Collectively, these stone types span an effective atomic
number range of approximately 7 to 14. While Uric Acid and Calcium based stones are generally distinguishable in conventional CT, stone compositions like Cystine and Struvite are difficult to distinguish resulting in treatment uncertainty. Experimental phantom measurements, made under increasingly complex imaging conditions, illustrate the impact of various factors on measurement accuracy. Preliminary clinical studies are reported.
Dual energy CT cardiac imaging is challenging due to cardiac motion and the resolution requirements of clinical
applications. In this paper we investigate dual energy CT imaging via fast kVp switching acquisitions of a novel
dynamic cardiac phantom. The described cardiac phantom is realistic in appearance with pneumatic motion control
driven by an ECG waveform.
In the reported experiments the phantom is driven off a 60 beats per minute simulated ECG waveform. The cardiac
phantom is inserted into a phantom torso cavity. A fast kVp switching axial step and shoot acquisition is detailed. The
axial scan time at each table position exceeds one heart cycle so as to enable retrospective gating. Gating is performed
as a mechanism to mitigate the resolution impact of heart motion.
Processing of fast kVp data is overviewed and the resulting kVp, material decomposed density, and monochromatic
reconstructions are presented. Imaging results are described in the context of potential clinical cardiac applications.
Recently there has been significant interest in dual energy CT imaging with several acquisition methods being
actively pursued. Here we investigate fast kVp switching where the kVp alternates between low and high kVp
every view. Fast kVp switching enables fine temporal registration, helical and axial acquisitions, and full field
of view. It also presents several processing challenges. The rise and fall of the kVp, which occurs during the
view integration period, is not instantaneous and complicates the measurement of the effective spectrum for low
and high kVp views. Further, if the detector digital acquisition system (DAS) and generator clocks are not fully
synchronous, jitter is introduced in the kVp waveform relative to the view period.
In this paper we develop a method for estimation of the resulting spectrum for low and high kVp views. The
method utilizes static kVp acquisitions of air with a small bowtie filter as a basis set. A fast kVp acquisition of
air with a small bowtie filter is performed and the effective kVp is estimated as a linear combination of the basis
vectors. The effectiveness of this method is demonstrated through the reconstruction of a water phantom acquired
with a fast kVp acquisition. The impact of jitter due to the generator and detector DAS clocks is explored via
simulation. The error is measured relative to spectrum variation and material decomposition accuracy.
KEYWORDS: X-rays, X-ray computed tomography, X-ray imaging, Signal attenuation, Photons, Medical imaging, Switching, Fast packet switching, Sensors, Dual energy imaging
In a conventional X-ray CT system, where an object is scanned with a selected incident x-ray spectrum, or kVp, the
reconstructed images only approximate the linear X-ray attenuation coefficients of the imaged object at an effective
energy of the incident X-ray beam. The errors are primarily the result of beam hardening due to the polychromatic nature
of the X-ray spectrum. Modem clinical CT scanners can reduce this error by a process commonly referred to as spectral
calibration. Spectral calibration linearizes the measured projection value to the thickness of water. However, beam
hardening from bone and contrast agents can still induce shading and streaking artifacts and cause CT number
inaccuracies in the image.
In this paper, we present a dual kVp scanning method, where during the scan, the kVp is alternately switching between
target low and high preset values, typically 80kVp and 140 kVp, with a period less than 1ms. The measured projection
pairs are decomposed into the density integrals of two basis materials in projection space. The reconstructed density
images are further processed to obtain monochromatic attenuation coefficients of the object at any desired energy.
Energy levels yielding optimized monochromatic images are explored, and their analytical representations are derived.
Linear discriminate analysis (LDA) is applied to dual kVp CT and used for tissue characterization. The
potential to quantitatively model both malignant and benign, hypo-intense liver lesions is evaluated by analysis of
portal-phase, intravenous CT scan data obtained on human patients. Masses with an a priori classification are mapped
to a distribution of points in basis material space. The degree of localization of tissue types in the material basis space
is related to both quantum noise and real compositional differences. The density maps are analyzed with LDA and
studied with system simulations to differentiate these factors. The discriminant analysis is formulated so as to
incorporate the known statistical properties of the data. Effective kVp separation and mAs relates to precision of tissue
localization. Bias in the material position is related to the degree of X-ray scatter and partial-volume effect.
Experimental data and simulations demonstrate that for single energy (HU) imaging or image-based decomposition
pixel values of water-like tissues depend on proximity to other iodine-filled bodies. Beam-hardening errors cause a
shift in image value on the scale of that difference sought between in cancerous and cystic lessons. In contrast,
projection-based decomposition or its equivalent when implemented on a carefully calibrated system can provide
accurate data. On such a system, LDA may provide novel quantitative capabilities for tissue characterization in dual
energy CT.
KEYWORDS: Sensors, Imaging systems, Image filtering, X-ray computed tomography, X-rays, Scintillators, Data modeling, Data acquisition, Systems modeling, Signal attenuation
The material specificity of computed tomography is quantified using an experimental benchtop imaging system
and a physics-based system model. The apparatus is operated with different detector and system configurations each
giving X-ray energy spectral information but with different overlap among the energy-bin weightings and noise
statistics. Multislice, computed tomography sinograms are acquired using dual kVp, sequential source filters or a
detector with two scintillator/photodiodes layers. Basis-material and atomic number images are created by first
applying a material decomposition algorithm followed by filtered backprojection. CT imaging of phantom materials
with known elemental composition and density were used for model validation. X-ray scatter levels are measured with a
beam-blocking technique and the impact to material accuracy is quantified. The image noise is related to the intensity
and spectral characteristics of the X-ray source. For optimal energy separation adequate image noise is required. The
system must be optimized to deliver the appropriate high mA at both energies. The dual kVp method supports the
opportunity to separately engineer the photon flux at low and high kvp. As a result, an optimized system can achieve
superior material specificity in a system with limited acquisition time or dose. In contrast, the dual-layer and sequential
acquisition modes rely on a material absorption mechanism that yields weaker energy separation and lower overall
performance.
We present the analysis of the accuracy and precision of dual energy material basis decomposition for the quantification of tissue fat content in computed tomography. We compare the benefits of a pre-reconstruction (sinogram-based) dual energy imaging technique versus a post-reconstruction (image) based dual energy decomposition technique using a numerical simulation. A phantom containing plastics of known composition is measured to validate the technique. The accuracy of the image based dual energy decomposition technique is contingent on the amount of beam hardening encountered in the phantom. The accuracy of the pre-reconstruction dual energy technique depends on how accurately the system spectral response can be modeled. In both cases the precision of the dual energy imaging is determined by the photon flux.
In addition to a conventional Computed Tomography (CT) image, dual energy (dual kVp) imaging can be used to generate an image of the same anatomy that represents the equivalent density of a particular material, for example, calcium, iodine, water, etc. This image can be used to improve the differentiation of materials as well as improve the accuracy of absolute density measurements in a cross-sectional image. It is important to understand the certainty of the estimation of the density of the material. Both simulations and measurements are used to quantify these errors. Data are acquired using a flat-panel based volumetric CT system, by taking two scans and adjusting the maximum energy of the source spectrum (kVp). Physics based simulations are used to compare with the measurements. After validating the simulation algorithms, the accuracy of the dual kVp method is determined using the simulations in a perturbation study.
Dose is becoming increasingly important for computed tomography clinical practice. It is of general interest to understand the impact that system design can have on dose and image quality. This study addresses the effect of bowtie shape on the dose and contrast-to-noise across the field of view. Simulation of the CT acquisition is used to calculate the energy deposition throughout a numerical phantom for a set of relevant system operating parameters and bowtie shapes. Mean absorbed dose is calculated by summing over the phantom volume and is compared with other typical dose specifications. A more aggressive attenuation profile of the bowtie which offers higher attenuation in the periphery of the field of view can offer the benefit of lower dose but at the expense of reduced contrast-to-noise at the edge of the cross-sectional image.
A framework for rapid and reliable design of Volumetric Computed Tomography (VCT) systems is presented. This work uses detailed system simulation tools to model standard and anthropomorphic phantoms in order to simulate the CT image and choose optimal system specifications. CT systems using small-pitch, 2-D flat area detectors, initially developed for x-ray projection imaging, have been proposed to implement Volume CT for clinical applications. Such systems offer many advantages, but there are also many trade-offs not fully understood that affect image quality. Although many of these effects have been studied in the literature for traditional CT applications, there are unique interactions for very high-resolution flat-panel detectors that are proposed for volumetric CT. To demonstrate the process we describe an example that optimizes the parameters to achieve high detectability for thin slices. The VCT system was modeled over a range of operating parameters, including: tube voltage, tube current, tube focal spot size, detector cell size, number of views, and scintillator thickness. The response surface, which captures the effects of system components on image quality, was calculated. Optimal and robust designs can be achieved by determining an operating point from the response equations, given the constraints. We verify the system design with images from standard and low contrast phantoms. Eventually this design tool could be used, in conjunction with clinical researchers, to specify VCT scanner designs, optimize imaging protocols, and quantify image accuracy and repeatability.
Gadovist, a 1.0-molar Gd contrast agent from Schering AG, Berlin, Germany, in use in clinical MRI in Europe, was evaluated as a radiography contrast agent. In a collaboration with Brookhaven National Laboratory (BNL), Schering AG is developing several such lanthanide-based contrast agents, while BNL evaluates them using different x-ray beam energy spectra. These energy spectra include a 'truly' monochromatic beam (0.2 keV energy bandwidth) from the National Synchrotron Light Source (NSLS), BNL, tuned above the Gd K-edge, and x-ray-tube beams from different kVp settings and beam filtrations. Radiographs of rabbits' kidneys were obtained with Gadovist at the NSLS. Furthermore, a clinical radiography system was used for imaging rabbits' kidneys comparing Gadovist and Conray, an iodinated contrast agent. The study, using 74 kVp and standard Al beam filter for Conray and 66 kVp and an additional 1.5 mm Cu beam filter for Gadovist, produced comparable images for Gadovist and Conray; the injection volumes were the same, while the radiation absorbed dose for Gadovist was slightly smaller. A bent-crystal silicon monochromator operating in the Laue diffraction mode was developed and tested with a conventional x-ray tube beam; it narrows the energy spectrum to about 4 keV around the anode tungsten's K' line. Preliminary beam-flux results indicate that the method could be implemented in clinical CT if x-ray tubes with approximately twice higher output become available.
A monochromatic CT for imaging the human head and neck is being developed at the National Synchrotron Light Source. We compared the performance of this system, multiple energy computed tomography (MECT), with that of a conventional CT (CCT) using phantoms. The advantage in image contrast of MECT, with its beam energy tuned just above the K-edge of contrast element, over CCT carried out at 120 kVp, was approximately equal to 3.2-fold for iodine and approximately equal to 2.2 fold for gadolinium. Image noise was compared by simulations because this comparison requires matching the spatial resolutions of the two systems. Simulations at a 3- rad dose and 3-mm slice height on an 18-cm-diameter acrylic phantom, with MECT operating at 60.5 keV, showed that image noise for MECT was 1.4 HU vs. 1.8 HU for CCT. Simulations in the dual-energy quantitative CT mode showed a two-fold advantage for MECT in image noise, as well as its superior quantification. MECT operated in the planar mode revealed fatty tissue in the body of a rat using xenon K-edge subtraction. Our initial pan for clinical application of the system is to image the composition of carotid artery plaques non-invasively, separating the plaques' main constituents: the fatty, fibrous, and calcified tissues.
Access to the requested content is limited to institutions that have purchased or subscribe to SPIE eBooks.
You are receiving this notice because your organization may not have SPIE eBooks access.*
*Shibboleth/Open Athens users─please
sign in
to access your institution's subscriptions.
To obtain this item, you may purchase the complete book in print or electronic format on
SPIE.org.
INSTITUTIONAL Select your institution to access the SPIE Digital Library.
PERSONAL Sign in with your SPIE account to access your personal subscriptions or to use specific features such as save to my library, sign up for alerts, save searches, etc.