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.
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
A 3D CdZnTe detector can provide 3D position information as well as energy information of each individual interaction when a gamma ray is scattered or absorbed in the detector. This unique feature provides the 3D CdZnTe detector the capability to do Compton imaging with a single detector. After detector calibration, real-time data acquisition and imaging are implemented with a single detector system. Because the detector has a finite size and any point in the detector can be the first scattering position, 3D gamma-ray imaging in near field is possible. In this work we will show the result of the 4π Compton imaging with a single 15mm × 15mm × 10mm CdZnTe detector. Different algorithms for sequence and imaging reconstruction will be addressed and compared. The angular uncertainty is estimated and the most recent results from measurements are presented.