Dual energy (DE) CT imaging is expected to play a major role in the diagnostic arena as it provides a quantitative
decomposition of basis materials, opening the door for new clinical applications without significantly increasing dose to
the patient. DE-CT provides a particularly unique opportunity in preclinical CT where new elemental contrast agents are
providing novel approaches for quantitative tissue characterization. We have implemented DE-CT imaging with a
preclinical dual source micro-CT scanner. With this configuration, both forward and cross-scatter can substantially
degrade image quality. This work investigated the effect of scatter correction on the accuracy of post-reconstruction
iodine and calcium decomposition. Scatter has been estimated using a lead beam stop technique. Our approach involves
noise reduction in the scatter corrected images using bilateral filtering. The scatter correction has been quantitatively
evaluated using phantom experiments and in vivo cancer imaging. As shown by our measurements, the dual source
scanning is affected more by the cross-scatter from the high energy to the low energy imaging chain. The scatter
correction reduced the presence of cupping artifacts and increased both the accuracy and precision of dual energy
decompositions of calcium and iodine. On average, the root mean square errors in retrieving true iodine and calcium
concentrations via dual energy were reduced by 32%. As a result of scatter corrections, we expect more accurate
quantification of important vascular biomarkers such as fractional blood volume and vascular permeability in preclinical
Dual energy CT imaging is expected to play a major role in the diagnostic arena as it provides material
decomposition on an elemental basis. The purpose of this work is to investigate the use of dual energy micro-CT for
the estimation of vascular, tissue, and air fractions in rodent lungs using a post-reconstruction three-material
decomposition method. We have tested our method using both simulations and experimental work. Using
simulations, we have estimated the accuracy limits of the decomposition for realistic micro-CT noise levels. Next,
we performed experiments involving ex vivo lung imaging in which intact lungs were carefully removed from the
thorax, were injected with an iodine-based contrast agent and inflated with air at different volume levels. Finally, we
performed in vivo imaging studies in (n=5) C57BL/6 mice using fast prospective respiratory gating in endinspiration
and end-expiration for three different levels of positive end-expiratory pressure (PEEP). Prior to imaging,
mice were injected with a liposomal blood pool contrast agent. The mean accuracy values were for Air (95.5%),
Blood (96%), and Tissue (92.4%). The absolute accuracy in determining all fraction materials was 94.6%. The
minimum difference that we could detect in material fractions was 15%. As expected, an increase in PEEP levels for
the living mouse resulted in statistically significant increases in air fractions at end-expiration, but no significant
changes in end-inspiration. Our method has applicability in preclinical pulmonary studies where various
physiological changes can occur as a result of genetic changes, lung disease, or drug effects.
Spectral reconstruction algorithms for x-ray CT require an accurate spectral model of the system, including the spectrum
of the photons emitted by the source and the spectral sensitivity of the detector. Although these components of the
spectral model have been characterized in previous studies, there might be additional components that are unaccounted
for, such as the inherent filtration of the x-ray source and the detector. In this study, we present a technique for
measuring the inaccuracies in the spectral model and accounting for them. This technique entails the acquisition of
photon measurements with several materials placed between the source and the detector, and the solution of a linear
system of equations. We test the accuracy of this technique in simulations, and demonstrate its potential to improve the
results of spectral reconstruction.
Micro-CT has become a powerful tool for small animal research. Many micro-CT applications require exogenous
contrast agents, which are most commonly based on iodine. Despite advancements in contrast agents, single-energy
micro-CT is sometimes limited in the separation of two different materials that share similar grayscale intensity values as
in the case of bone and iodine. Dual energy micro-CT offers a solution to this separation problem, while eliminating the
need for pre-injection scanning. Various dual energy micro-CT sampling strategies are possible, including 1) single
source sequential scanning, 2) simultaneous dual source acquisition, or 3) single source with kVp switching. But, no
commercial micro-CT system exists in which all these sampling strategies have been implemented. This study reports on
the implementation and comparison of these scanning techniques on the same small animal imaging system.
Furthermore, we propose a new sampling strategy that combines dual source and kVp switching. Post-sampling and
reconstruction, a simple two-material dual energy decomposition was applied to differentiate iodine from bone. The
results indicate the time differences and the potential problems associated with each sampling strategy. Dual source
scanning allows for the fastest acquisition, but is prone to errors in decomposition associated with scattering and
imperfect geometric alignment of the two imaging chains. KVp switching prevents these types of artifacts, but requires
more time for sampling. The novel combination between the dual source and kVp switching has the potential to reduce
sampling time and provide better decomposition performance.
X-ray Luminescence CT (XLCT) is a hybrid imaging modality combining x-ray and optical imaging in which x-ray
luminescent nanophosphors (NPs) are used as emissive imaging probes. NPs are easily excited using common CT
energy x-ray beams, and the NP luminescence is efficiently collected using sensitive light-based detection systems.
XLCT can be recognized as a close analog to fluorescence diffuse optical tomography (FDOT). However, XLCT has
remarkable advantages over FDOT due to the substantial excitation penetration depths provided by x-rays relative to
laser light sources, long-term photo-stability of NPs, and the ability to tune NP emission within the NIR spectral
window. Since XCLT uses an x-ray pencil beam excitation, the emitted light can be measured and back-projected
along the x-ray path during reconstruction, where the size of the x-ray pencil beam determines the resolution for
XLCT. In addition, no background signal competes with NP luminescence (i.e., no auto fluorescence) in XLCT.
Currently, no small animal XLCT system has been proposed or tested. This paper investigates an XLCT system built
and integrated with a dual source micro-CT system. A novel sampling paradigms that results in more efficient
scanning is proposed and tested via simulations. Our preliminary experimental results in phantoms indicate that a
basic CT-like reconstruction is able to recover a map of the NP locations and differences in NP concentrations. With
the proposed dual source system and faster scanning approaches, XLCT has the potential to revolutionize molecular
imaging in preclinical studies.
Spectral CT imaging is expected to play a major role in the diagnostic arena as it provides material decomposition on
an elemental basis. One fascinating possibility is the ability to discriminate multiple contrast agents targeting different
biological sites. We investigate the feasibility of dual energy micro-CT for discrimination of iodine (I) and gold (Au)
contrast agents when simultaneously present in the body. Simulations and experiments were performed to measure
the CT enhancement for I and Au over a range of voltages from
40-to-150 kVp using a dual source micro-CT system.
The selected voltages for dual energy micro-CT imaging of Au and I were 40 kVp and 80 kVp. On a massconcentration
basis, the relative average enhancement of Au to I was 2.75 at 40 kVp and 1.58 at 80 kVp. We have
demonstrated the method in a preclinical model of colon cancer to differentiate vascular architecture and
extravasation. The concentration maps of Au and I allow quantitative measure of the bio-distribution of both agents.
In conclusion, dual energy micro-CT can be used to discriminate probes containing I and Au with immediate impact
in pre-clinical research.
X-ray CT imaging of dynamic physiological processes entails the reconstruction of volumetric images of objects with x-ray
attenuation properties that vary over time and energy. We show how the same algebraic model can be used to
represent both temporal and spectral information. This model enables the formulation of algorithms capable of
recovering information in either dimension. These dimensions can also be combined to develop algorithms that recover
both dimensions simultaneously. We present such an algorithm, describe its implementation, and test it in simulations.
Gating in small animal imaging can compensate for artifacts due to physiological motion. This paper presents a strategy
for sampling and image reconstruction in the rodent lung using
micro-CT. The approach involves rapid sampling of freebreathing
mice without any additional hardware to detect respiratory motion. The projection images are analyzed postacquisition
to derive a respiratory signal, which is used to provide weighting factors for each projection that favor a
selected phase of the respiration (e.g. end-inspiration or end-expiration) for the reconstruction. Since the sampling cycle
and the respiratory cycle are uncorrelated, the sets of projections corresponding to any of the selected respiratory phases
do not have a regular angular distribution. This drastically affects the image quality of reconstructions based on simple
filtered backprojection. To address this problem, we use an iterative reconstruction algorithm that combines the
Simultaneous Algebraic Reconstruction Technique with Total Variation minimization (SART-TV). At each SART-TV
iteration, backprojection is performed with a set of weighting factors that favor the desired respiratory phase. To reduce
reconstruction time, the algorithm is implemented on a graphics processing unit. The performance of the proposed
approach was investigated in simulations and in vivo scans of mice with primary lung cancers imaged with our in-house
developed dual tube/detector micro-CT system. We note that if the ECG signal is acquired during sampling, the same
approach could be used for phase-selective cardiac imaging.
Dynamic imaging with micro-CT often produces poorly-distributed sets of projections, and reconstructions of this data
with filtered backprojection algorithms (FBP) may be affected by artifacts. Iterative reconstruction algorithms and total
variation (TV) denoising are promising alternatives to FBP, but may require running times that are frustratingly long.
This obstacle can be overcome by implementing reconstruction algorithms on graphics processing units (GPU). This
paper presents an implementation of a family of iterative reconstruction algorithms with TV denoising on a GPU, and a
series of tests to optimize and compare the ability of different algorithms to reduce artifacts. The mathematical and
computational details of the implementation are explored. The performance, measured by the accuracy of the
reconstruction versus the running time, is assessed in simulations with a virtual phantom and in an in vivo scan of a
mouse. We conclude that the simultaneous algebraic reconstruction technique with TV minimization (SART-TV) is a
time-effective reconstruction algorithm for producing reconstructions with fewer artifacts than FBP.
The attenuation of x-rays in matter is dependent on the energy of the x-rays and the atomic composition of the matter.
Attenuation measurements at multiple x-ray energies can be used to improve the identification of materials. We present a
method to estimate the fractional composition of three materials in an object from x-ray CT measurements at two
different energies. The energies can be collected from measurements from a single source-detector system at two points
in time, or from a dual source-detector system at one point in time. This method sets up a linear system of equations
from the measurements and finds the solution through a geometric construction of the inverse matrix equation. This
method enables the estimation of the blood fraction within a region of living tissue in which blood containing an
iodinated contrast agent is mixed with two other materials. We verified this method using x-ray CT simulations
implemented in MATLAB, investigated the parameters needed to optimize the estimation, and then applied the method
to a mouse model of lung cancer. A direct application of this method is the estimation of blood fraction in lung tumors in
preclinical studies. This work was performed at the Duke Center for In Vivo Microscopy, an NCRR/NCI National
Resource (P41 RR005959/U24 CA092656), and also supported by NCI R21 CA124584.
Quantitative in-vivo imaging of lung perfusion in rodents can provide critical information for preclinical studies. However, the combined challenges of high temporal and spatial resolution have made routine quantitative perfusion imaging difficult in rodents. We have recently developed a dual tube/detector micro-CT scanner that is well suited to
capture first-pass kinetics of a bolus of contrast agent used to compute perfusion information. Our approach is based on
the paradigm that the same time density curves can be reproduced in a number of consecutive, small (i.e. 50μL) injections of iodinated contrast agent at a series of different angles. This reproducibility is ensured by the high-level integration of the imaging components of our system, with a micro-injector, a mechanical ventilator, and monitoring applications. Sampling is controlled through a biological pulse sequence implemented in LabVIEW. Image reconstruction is based on a simultaneous algebraic reconstruction technique implemented on a GPU. The capabilities of 4D micro-CT imaging are demonstrated in studies on lung perfusion in rats. We report 4D micro-CT imaging in the rat lung with a heartbeat temporal resolution of 140 ms and reconstructed voxels of 88 μm. The approach can be readily
extended to a wide range of important preclinical models, such as tumor perfusion and angiogenesis, and renal function.
Micro-CT is a non-invasive imaging modality usually used to assess morphology in small animals. In our previous
work, we have demonstrated that functional micro-CT imaging is also possible. This paper describes a dual micro-CT system with two fixed x-ray/detectors developed to address such challenging tasks as cardiac or perfusion studies
in small animals. A two-tube/detector system ensures simultaneous acquisition of two projections, thus reducing
scanning time and the number of contrast injections in perfusion studies by a factor of two. The system is integrated
with software developed in-house for cardio-respiratory monitoring and gating. The sampling geometry was
optimized for 88 microns in such a way that the geometric blur of the focal spot matches the Nyquist sample at the
detector. A geometric calibration procedure allows one to combine projection data from the two chains into a single
reconstructed volume. Image quality was measured in terms of spatial resolution, uniformity, noise, and linearity.
The modulation transfer function (MTF) at 10% is 3.4 lp/mm for single detector reconstructions and 2.3 lp/mm for
dual tube/detector reconstructions. We attribute this loss in spatial resolution to the compounding of slight errors in
the separate single chain calibrations. The dual micro-CT system is currently used in studies for morphological and
functional imaging of both rats and mice.