Single Photon Emission Computed Tomography Projection Research Articles

Do short-time SPECT images of bone scintigraphy improve the diagnostic value in the evaluation of solitary lesions in the thoracic spine in patients with extraskeletal malignancies?

Single photon emission computed tomography (SPECT) images provide many details of the anatomical structure. Also about bone scintigraphy, there are many reports of the improvement of diagnosis by SPECT images. Although SPECT is useful, it requires much time. So to perform SPECT for all cases is difficult in the clinical situation. Recently, due to technical improvements in gamma cameras, we can get SPECT images in a short time. We examined diagnosis of solitary hot spots of thoracic spine in cancer patients using short-time SPECT. And we considered whether short-time SPECT contributes to the precise diagnosis of the lesion. We performed bone scintigraphy image acquisition and both planar and short-time SPECT of the chest. Short-time SPECT was acquired in 6 minutes. We selected 36 cases with malignancy, whose bone scintigraphy demonstrated a solitary accumulation hot spot in the thoracic spine. Three experienced radiologists in nuclear medicine and 4 beginners diagnosed the images. They interpreted planar, short-time SPECT and maximum intensity projection (MIP) view of the chest of each case. The observers' response data were analyzed with receiver operating characteristic (ROC) curve analysis. Of the three types of images, the Az (the area under ROC curve) values of short-time SPECT were the highest in all the observers except for only one beginner. Compared with experienced observers, beginners scored lower Az values of short-time SPECT. MIP images were constructed using SPECT data, but the Az values of MIP images were not higher than those of planar images. As to diagnosis, beginners tended to interprete most of the accumulations as metastatic lesions. Short-time SPECT can be helpful to some degree, but to provide greater benefit, the observers require considerable exercise and experience.

Comparison of 1‐ and 2‐day protocols for myocardial SPECT: a Monte Carlo study

Myocardial perfusion single-photon emission computed tomography (SPECT) is carried out by combining a rest and a stress study that are performed either on one day or two separate days. A problem when performing the two studies on 1 day is that the residual activity from the first study contributes to the activity measured in the second study. Our aim was to identify and evaluate trends in the quantification parameters of myocardial perfusion images as a function of separation time between rest and stress. A digital phantom was used for the generation of heart images and a Monte Carlo-based scintillation camera program was used to simulate SPECT projection images. In our simulations, the rest images were normal and the stress images included lesions of different types and localization. Two programs for quantification of myocardial perfusion images were used to assess the different images in an automated and objective way. The summed difference scores observed with the 2-day protocol were 3 +/- 1 (mean +/- SD) higher for AutoQUANT and 2 +/- 1 higher for 4D-MSPECT compared with those observed with the 1-day protocol. The extent values were 2% points higher for the 2-day protocol compared with the 1-day protocol for both programs. There are differences in the quantitative assessment of perfusion defects depending on the type of protocol used. The contribution of residual activity is larger when a 1-day protocol is used compared with the 2-day protocol. The differences, although small, are of a magnitude that results in a clear shift in quantification parameters.

A study of the influence of local variations in myocardial thickness on SPECT perfusion imaging

The objective of this project was to study the impact of local variations in myocardial thickness on single photon emission computed tomography (SPECT) perfusion imaging using segmented high-resolution gated-computer tomography (CT) data of the heart to define source distributions. High-resolution breath-hold gated CT data of 16 patients were obtained using a GE Lightspeed multislice CT system. Transverse slices (512/spl times/512) with x-y pixel size of 0.039 cm and a slice thickness of either 0.25 cm or 0.125 cm were segmented to obtain left-ventricular (LV) and right-ventricular (RV) myocardial walls for all time frames of the cardiac cycle. Polar maps of myocardial thickness were generated using radial and short-axis slices of the LV Absolute quantitation was performed on the myocardium thickness polar maps. The segmented LV and RV were also incorporated in the gated MCAT phantom, and analytical SPECT projections generated using typical acquisition parameters.

Effects of temporal modelling on the statistical uncertainty of spatiotemporal distributions estimated directly from dynamic SPECT projections

Artefacts can result when reconstructing a dynamic image sequence from inconsistent single photon emission computed tomography (SPECT) projection data acquired by a slowly rotating gantry. The artefacts can lead to biases in kinetic parameters estimated from time–activity curves generated by overlaying volumes of interest on the images. Insufficient sampling and truncation of projections by cone-beam collimators can cause additional artefacts. To overcome these sources of bias in conventional image based dynamic data analysis, we have been investigating the estimation of time–activity curves and kinetic model parameters directly from dynamic SPECT projection data by modelling the spatial and temporal distribution of the radiopharmaceutical throughout the projected field of view. In the present work, we perform Monte Carlo simulations to study the effects of the temporal modelling on the statistical variability of the reconstructed spatiotemporal distributions. The simulations utilize fast methods for fully four-dimensional (4D) direct estimation of spatiotemporal distributions and their statistical uncertainties, using a spatial segmentation and temporal B-splines. The simulation results suggest that there is benefit in modelling higher orders of temporal spline continuity. In addition, the accuracy of the time modelling can be increased substantially without unduly increasing the statistical uncertainty, by using relatively fine initial time sampling to capture rapidly changing activity distributions.

Analytical calculation of photon distributions in SPECT projections

In this paper the authors present a method for analytically calculating the distribution of photons detected in single photon emission computed tomography (SPECT) projections. The technique is applicable to sources in homogeneous and nonhomogeneous media. The photon distribution (primary, first-, and second-order Compton scatter) is computed using a precalculated camera-dependent look-up table in conjunction with an attenuation map of the scattering object and a map of the activity distribution. The speed and accuracy of this technique is compared to that of Monte Carlo simulations. The cases considered are a point source in a homogeneous and also in a nonhomogeneous scattering medium, an extended source in a nonhomogeneous medium, and a homogeneous cylinder filled uniformly with activity. The method is quantitatively accurate and faithfully reproduces the spatial distribution of the unscattered and scattered photons. For comparable statistical precision in the peak of the calculated distribution, their approach can result in a gain in calculation time over Monte Carlo simulators. For point sources, the computation times are improved by a factor of 20-150. However, this gain depends on the source configuration, and calculation times become comparable for an 800 voxel source and are five times slower for a 55000 voxel source. The method also offers an increase in the speed of computation of higher order Compton scatter events over a similar analytical technique.

Iterative restoration of SPECT projection images

Photon attenuation and the limited nonstationary spatial resolution of the detector can reduce both qualitative and quantitative image quality in single photon emission computed tomography (SPECT). In this paper, a reconstruction approach is described which can compensate for both of these degradations. The approach involves processing the projection data with Bellini's method for attenuation compensation followed by an iterative deconvolution technique which uses the frequency distance principle (FDP) to model the distance-dependent camera blur. Modeling of the camera blur with the FDP allows an efficient implementation using fast Fourier transform (FFT) methods. After processing of the projection data, reconstruction is performed using filtered backprojection. Simulation studies using two different brain phantoms show that this approach gives reconstructions with a favorable bias versus noise tradeoff, provides no visually undesirable noise artifacts, and requires a low computational load.

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 bound on the energy resolution required for quantitative SPECT

Scattered radiation is one of several physical perturbations that limit the accuracy of quantitative measurements in single-photon emission computed tomography (SPECT). Improvement in detector energy resolution leads to a reduction of scatter counts and a corresponding improvement in the quantitative accuracy of the SPECT measurement. In this study, simulated SPECT projections of a simple myocardial perfusion phantom were used to investigate the effect of detector energy resolution on the data. The phantom consists of a spherical shell of radionuclide within a 15 cm radius water-filled cylinder. Each projection contains on the order of 3 x 10(5) counts. The results demonstrate that a full-width, half-maximum energy resolution of 3-4 keV is sufficient to render the error due to scatter insignificant compared to the uncertainty due to photon statistics in this case. Further simulations verify that because smaller objects produce less scatter, they can be imaged accurately with degraded energy resolution. These results are useful when designing prototype systems that utilize solid-state detectors and low-noise electronics to achieve improved energy resolution.

Fourier correction for spatially variant collimator blurring in SPECT

In single-photon emission computed tomography (SPECT), projection data are acquired by rotating the photon detector around a patient, either in a circular orbit or in a noncircular orbit. The projection data of the desired spatial distribution of emission activity is blurred by the point-response function of the collimator that is used to define the range of directions of gamma-ray photons reaching the detector. The point-response function of the collimator is not spatially stationary, but depends on the distance from the collimator to the point. Conventional methods for deblurring collimator projection data are based on approximating the actual distance-dependent point-response function by a spatially invariant blurring function, so that deconvolution methods can be applied independently to the data at each angle of view. A method is described here for distance-dependent preprocessing of SPECT projection data prior to image reconstruction. Based on the special distance-dependent characteristics of the Fourier coefficients of the sinogram, a spatially variant inverse filter can be developed to process the projection data in all views simultaneously. The algorithm is first derived from Fourier analysis of the projection data from the circular orbit geometry. For circular orbit projection data, experimental results from both simulated data and real phantom data indicate the potential of this method. It is shown that the spatial filtering method can be extended to the projection data from the noncircular orbit geometry. Experiments on simulated projection data from an elliptical orbit demonstrate correction of the spatially variant blurring and distortion in the reconstructed image caused by the noncircular orbit geometry.

Pre-reconstruction restoration of SPECT projection images by a neural network

In single photon emission computed tomography (SPECT) the projection images obtained at view angles surrounding the patient are degraded due to the geometric response of the imaging system (a spatially-variant blur), Compton scatter, Poisson noise, and other factors. Various methods have been proposed for compensating for the spatially varying geometric response of the camera. Here the authors examine restoration of SPECT projection images using an artificial neural network. A three layer feedforward neural network is trained to compute the spatially-variant standard deviations of a symmetric Gaussian blur. A Hopfield network is then used to restore the projection images in which the restoration problem is formulated as a minimization of an error function of the network. Results from applying this restoration procedure on SPECT projection images are presented and the resulting SPECT reconstructions are analysed.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modelling photon transport in non-uniform media for SPECT with a vectorized Monte Carlo code

A vectorized Monte Carlo code has been developed for modelling photon transport in nonuniform media for single-photon-emission computed tomography (SPECT). The code is designed to compute photon detection kernels, which are used to build system matrices for simulating SPECT projection data acquisition and for use in matrix-based image reconstruction. Nonuniform attenuating and scattering regions are constructed from simple 3D geometric shapes, in which the density and mass attenuation coefficients are individually specified. On a Stellar GS1000 computer, Monte Carlo simulations are performed between 1.6 and 2.0 times faster when the vector processor is utilized than when computations are performed in scalar mode. Projection data acquired with a clinical SPECT gamma camera for a line source in a non-uniform thorax phantom are well modelled by Monte Carlo simulations. The vectorized Monte Carlo code was used to simulate a 99Tcm SPECT myocardial perfusion study, and compensations for nonuniform attenuation and the detection of scattered photons improve activity estimation. The speed increase due to vectorization makes Monte Carlo simulation more attractive as a tool for modelling photon transport in nonuniform media for SPECT.

Improved lesion detection in SPECT using MLEM reconstruction

Receiver operating characteristic (ROC) analysis was applied to determine if the maximum likelihood expectation maximization (MLEM) reconstruction algorithm improves lesion detectability in single photon emission computed tomography (SPECT) when compared with a filtered backprojection (FBP) algorithm. The performance of the reconstruction algorithms was evaluated based on cold lesion detection by human observers. Simulated SPECT projection data with added Poisson noise were constructed using the MLEM and the FBP algorithms. The parameters of the study, including lesion size and total counts, were chosen to maximize the statistical power of the test. Three hundred images were generated and nine observers were employed for the study. The average ROC curves for both reconstruction methods were measured. Diagnostic performance was quantified using the area under the ROC curves. MLEM showed improved detectability for all the observers. Observer P-values were calculated, and Student's t-test was performed in order to verify the statistical significance of the observed improvement.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

Modifying constrained least-squares restoration for application to single photon emission computed tomography projection images.

Image restoration methods have been shown to increase the contrast of nuclear medicine images by decreasing the effects of scatter and septal penetration. Image restoration can also reduce the high-frequency noise in the image. This study applies constrained least-squares (CLS) restoration to the projection images of single photon emission computed tomography (SPECT). In a previous study, it was noted that CLS restoration has the potential advantage of automatically adapting to the blurred object. This potential is confirmed using planar images. CLS restoration is then modified to improve its performance when applied to SPECT projection image sets. The modification was necessary because the Poisson noise in low count SPECT images causes considerable variation in the CLS filter. On phantom studies, count-dependent Metz restoration was slightly better than the modified CLS restoration method, according to measures of contrast and noise. However, CLS restoration was generally judged as yielding the best results when applied to clinical studies, apparently because of its ability to adapt to the image being restored.