Emission Projection Data Research Articles

A Macroquantification Approach for Region-of-Interest Assessment in Emission Tomography

In this article, we propose a quantification methodology for estimating the statistical parameters of the activity inside regions of interest (ROIs). Macroquantification implies a rearrangement of the emission projection data into macroprojections and a redefinition of the system matrix based either on an image reconstruction involving iterative ROI-wise regularization or on an ROI uniformity assumption. The technique allows a very fast computation of the ROI activities and covariance matrix in the least squares sense using a low-dimensional model of the tomographic problem. The macroquantification approach is evaluated through Monte Carlo simulations using a numerical thorax phantom, without taking into account the measurement artifacts and assuming a perfect a priori ROI definition. Various tumor ROI configurations and count rates are considered to reflect clinical situations. The results show that our technique yields low-bias ROI estimations that turn out to be more accurate than classical estimates relying on pixel summation. Macroquantification also provides an approximation for the ROI variance that describes the effective variance obtained through the simulations fairly well. The technique is then validated using single photon emission computed tomography (SPECT) data from a physical phantom composed of cylinders filled with different Tc concentrations for the task of ROI comparison. Here again, the study shows excellent agreement between the measured and predicted values of the ROI variance resulting in efficient estimations of ROI ratios and highly accurate ROI comparisons. In its simplest formulation, macroquantification has a short computation time, making it an ideal technique for quantitative ROI assessment that is compatible with a wide range of routine clinical applications.

Conditional entropy maximization for PET image reconstruction using adaptive mesh model

Iterative image reconstruction algorithms have been widely used in the field of positron emission tomography (PET). However, such algorithms are sensitive to noise artifacts so that the reconstruction begins to degrade when the number of iterations is high. In this paper, we propose a new algorithm to reconstruct an image from the PET emission projection data by using the conditional entropy maximization and the adaptive mesh model. In a traditional tomography reconstruction method, the reconstructed image is directly computed in the pixel domain. Unlike this kind of methods, the proposed approach is performed by estimating the nodal values from the observed projection data in a mesh domain. In our method, the initial Delaunay triangulation mesh is generated from a set of randomly selected pixel points, and it is then modified according to the pixel intensity value of the estimated image at each iteration step in which the conditional entropy maximization is used. The advantage of using the adaptive mesh model for image reconstruction is that it provides a natural spatially adaptive smoothness mechanism. In experiments using the synthetic and clinical data, it is found that the proposed algorithm is more robust to noise compared to the common pixel-based MLEM algorithm and mesh-based MLEM with a fixed mesh structure.

Calculation and validation of the use of effective attenuation coefficient for attenuation correction in In‐111 SPECT

Nuclear medicine tracers using 111In as a radiolabel are increasing in their use, especially in the domain of oncologic imaging. In these applications, it often is critical to have the capability of quantifying radionuclide uptake and being able to relate it to the biological properties of the tumor. However, images from single photon emission computed tomography (SPECT) can be degraded by photon attenuation, photon scattering, and collimator blurring; without compensation for these effects, image quality can be degraded, and accurate and precise quantification is impossible. Although attenuation correction for SPECT is becoming more common, most implementations can only model single energy radionuclides such as 99mTc and 123I. Thus, attenuation correction for 111In is challenging because it emits two photons (171 and 245 keV) at nearly equal rates (90.2% and 94% emission probabilities). In this paper, we present a method of calculating a single "effective" attenuation coefficient for the dual-energy emissions of 111In, and that can be used to correct for photon attenuation in radionuclide images acquired with this radionuclide. Using this methodology, we can derive an effective linear attenuation coefficient Micro(eff) and an effective photon energy E(eff) based on the emission probabilities and linear attenuation coefficients of the 111In photons. This approach allows us to treat the emissions from 111In as a single photon with an effective energy of 210 keV. We obtained emission projection data from a tank filled with a uniform solution of 111In. The projection data were reconstructed using an iterative maximum-likelihood algorithm with no attenuation correction, and with attenuation correction assuming photon energies of 171, 245, and 210 keV (the derived E(eff)). The reconstructed tomographic images demonstrate that the use of no attenuation correction, or correction assuming photon energies of 171 or 245 keV introduces inaccuracies into the reconstructed radioactivity distribution when compared against the effective energy method. In summary, this work provides both a theoretical framework and experimental methodology of attenuation correction for the dual-energy emissions from 111In. Although these results are specific to 111In, the foundation could easily be extended to other multiple-energy isotopes.

Iteration algorithm to correct absorption in PET

One of the difficulties arising in PET is attenuation of emission projection data. The most difficult situation arises in the cases in which no information as to the distribution of the absorption coefficient is available. It is this case that is considered in the present paper. A new approach to the problem is proposed. Its main idea consists in that the measurement data, as soon as they all belong to one object, are bound to be self-consistent. The whole set of projection data is considered as an invariant function of the operator PR/sup -1,/ where R/sup -1/ is an algorithm solving the emission tomography problem and P is the projecting operator. An iteration algorithm that permits reconstruction of emission projection data is developed. Numerical simulations are carried out.

A direct reconstruction method with variable constraints

In this article. a direct method to reconstruct images from projections is presented. This method, having its origin in astrophysics to restore images from observed data, uses a constant upper bound and a variable lower bound to constrain the maximum and minimum values taken by the emission intensity during iteration. Computer-simulated emission projection data from two phantoms are used for reconstruction. Comparison is made with other methods. The results show that a much better spatial resolution can be acquired by this method, especially for the sharp-shaped emission sources. (C) 1999 John Wiley & Sons, Inc.

Characterization and correction of pulse pile-up in simultaneous emission-transmission computed tomography.

We have developed an emission-transmission CT (ETCT) system capable of both single-photon emission computed tomography (SPECT) imaging and x-ray transmission CT imaging using a common photon counting detector. In principle, SPECT and x-ray CT projection data can be acquired simultaneously with the ETCT system; however, doing so results in contamination of the SPECT projection data due to pulse pile-up caused by the relatively high x-ray fluence rate. In this study, we characterize the effects of pulse pile-up for simultaneous ETCT imaging through computer simulation and experimental studies. We demonstrate that pulse pile-up in the SPECT energy window can be well approximated by a simple quadratic relationship between the pile-up rate and the x-ray fluence rate for sufficiently small x-ray fluence rates. Using this quadratic relationship, we developed a simple pile-up correction scheme that subtracts the pile-up counts from the emission data and also truncates the exterior regions of the emission projection data. Analysis of difference images and profiles indicate that this method permits us to reconstruct SPECT images with no apparent noise or resolution degradation in comparison to those obtained via sequential emission and transmission scans.

A transmission-map-based scatter correction technique for SPECT in inhomogeneous media.

In this paper a method of modeling the distribution of scattered events in emission projection data is developed and applied. This method is based on the use of a transmission map to define the inhomogeneous scattering object. The key point is the use of the set of line integrals calculated as part of the attenuation correction technique, as the basis of a model of the distribution of scattered events. The probability of a photon being scattered through a given angle and being detected in the emission energy window is approximated using a Gaussian function. The parameters of this Gaussian are determined using Monte Carlo generated parallel-beam scatter line spread functions from a nonuniformly attenuating phantom. The model is incorporated into a two-dimensional projector-backprojector and used with the Expectation-Maximization-Maximum-Likelihood algorithm for the reconstruction of fan-beam phantom data. The correction is shown to perform well for a phantom that varies slowly in the axial direction. For the more clinically realistic situation of a torso phantom, the method produces improvements in terms of blood pool to myocardium contrast, but does not restore the contrast to the level exhibited in a reconstruction from "scatter free" data.

Investigation of the use of X-ray CT images for attenuation compensation in SPECT

This study investigates the general use of single-beam X-ray computed tomography (CT) images for generating attenuation maps for compensation of photon attenuation in SPECT images. A 3D mathematical thorax phantom is used to simulate both emission and transmission projection data for monoenergetic (radionuclide) and polyenergetic (X-ray) sources. Polyenergetic transmission projection data are simulated for a standard X-ray spectrum and fan-beam geometry. The projection data are reconstructed using filtered backprojection to form an X-ray CT image which is then scaled to produce an estimate of the attenuation map at the energy of the emission radionuclide. Emission projection data are simulated for a fan-beam geometry at the energies of /sup 201/Tl and /sup 99m/Tc, two radionuclides commonly used in cardiac SPECT. Detector response and scatter are not included in the model. Noiseless, emission projection data are iteratively reconstructed using the ML-EM algorithm with nonuniform attenuation compensation and attenuation maps derived from both the simulated X-ray CT image and from a simulated monoenergetic transmission CT image. The attenuation maps generated from the X-ray CT images accurately estimate the attenuation coefficient for muscle and lung tissues, but not for bone tissues, which show error in the attenuation coefficient of 21-42% for spinal bone and 34-58% for rib bone. However, despite the inaccurate estimate of bone attenuation, the reconstructed SPECT images provide estimates of myocardial radioactivity concentration to within 9% and show few artifacts. >

Quantitative cardiac SPECT reconstruction with reduced image degradation due to patient anatomy

Patient anatomy has complicated effects on cardiac SPECT images. The authors investigated reconstruction methods which substantially reduced these effects for improved image quality. A 3D mathematical cardiac-torso (MCAT) phantom which models the anatomical structures in the thorax region were used in the study. The phantom was modified to simulate variations in patient anatomy including regions of natural thinning along the myocardium, body size, diaphragmatic shape, gender, and size and shape of breasts for female patients. Distributions of attenuation coefficients and Tl-201 uptake in different organs in a normal patient were also simulated. Emission projection data were generated from the phantoms including effects of attenuation and detector response. The authors have observed the attenuation-induced artifacts caused by patient anatomy in the conventional FBP reconstructed images. Accurate attenuation compensation using iterative reconstruction algorithms and attenuation maps substantially reduced the image artifacts and improved quantitative accuracy. The authors conclude that reconstruction methods which accurately compensate for nonuniform attenuation can substantially reduce image degradation caused by variations in patient anatomy in cardiac SPECT.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Noise propagation in SPECT images reconstructed using an iterative maximum-likelihood algorithm

The effects of photon noise in the emission projection data and uncertainty in the attenuation map on the image noise in attenuation-corrected SPECT images reconstructed using a maximum-likelihood expectation-maximization algorithm were investigated. Emission projection data of a physical Hoffman brain phantom and a thorax-like phantom were acquired from a prototype emission-transmission computed tomography (ETCT) scanner being developed at UCSF. Computer-simulated emission projection data from a head-like phantom and a thorax-like phantom were also obtained using a fan-beam geometry consistent with the ETCT system. The simulation assumed a 99Tcm source, included collimator blurring but ignored photon scatter. For each phantom, a region of interest (ROI) at the centre of the reconstructed image was chosen for the purpose of noise analysis. In all cases, the mean value (m) in the ROI approached a constant value after approximately 20 iterations. The standard deviation ( sigma ) generally increased with the number of iterations. The ratio ( sigma /m) was found to be inversely proportional to the square root of the total detected counts and proportional to the relative uncertainty in the attenuation maps. These two noise components contributed independently towards the noise in the reconstructed image. In the ETCT system employing an X-ray tube for attenuation map acquisition, the uncertainty in the reconstructed radionuclide distribution is limited mainly by photon noise in the emission projection data.