Optimized acquisition time and image sampling for dynamic SPECT of Tl-201

Comparison of sparse domain approaches for 4D SPECT dynamic image reconstruction

PURPOSE

Dynamic imaging (DI) provides additional diagnostic information in emission tomography in comparison to conventional static imaging at the cost of being computationally more challenging. Dynamic single photon emission computed tomography (SPECT) reconstruction is particularly difficult because of the limitations in the sampling geometry present in most existing scanners. We have developed an algorithm Spline Initialized Factor Analysis of Dynamic Structures (SIFADS) that is a matrix factorization method for reconstructing the dynamics of tracers in tissues and blood directly from the projections in dynamic cardiac SPECT, without first resorting to any 3D reconstruction.

METHODS

SIFADS is different from "pure" factor analysis in dynamic structures (FADS) in that it employs a dedicated spline-based pre-initialization. In this paper, we analyze the convergence properties of SIFADS and FADS using multiple metrics. The performances of the two approaches are evaluated for numerically simulated data and for real dynamic SPECT data from canine and human subjects.

RESULTS

For SIFADS, metrics analyzed for reconstruction algorithm convergence show better features of the metric curves vs iterations. In addition, SIAFDS provides better tissue segmentations than that from pure FADS. Measured computational times are also typically better for SIFADS implementations than those with pure FADS.

CONCLUSION

The analysis supports the utility of the pre-initialization of a factorization algorithm for better dynamic SPECT image reconstruction.

Analysis of penalized likelihood image reconstruction for dynamic PET quantification

Quantification of tracer kinetics using dynamic positron emission tomography (PET) provides important information for understanding the physiological and biochemical processes in humans and animals. A common procedure is to reconstruct a sequence of dynamic images first, and then apply kinetic analysis to the time activity curve of a region of interest derived from the reconstructed images. Obviously, the choice of image reconstruction method and its parameters affect the accuracy of the time activity curve and hence the estimated kinetic parameters. This paper analyzes the effects of penalized likelihood image reconstruction on tracer kinetic parameter estimation. Approximate theoretical expressions are derived to study the bias, variance, and ensemble mean squared error of the estimated kinetic parameters. Computer simulations show that these formulae predict correctly the changes of these statistics as functions of the regularization parameter. It is found that the choice of the regularization parameter has a significant impact on kinetic parameter estimation, indicating proper selection of image reconstruction parameters is important for dynamic PET. A practical method has been developed to use the theoretical formulae to guide the selection of the regularization parameter in dynamic PET image reconstruction.

Global Compartmental Pharmacokinetic Models for Spatiotemporal SPECT and PET Imaging

A new mathematical framework is introduced for combining the linear compartmental models used in pharmacokinetics with the spatiotemporal distributions of activity that are measured in single photon emission computed tomography (SPECT) and PET imaging. This approach is global in the sense that the compartmental differential equations involve only the overall spatially integrated activity in each compartment. The kinetics for the local compartmental activities are not specified by the model and would be determined from data. It is shown that an increase in information about the spatial distribution of the local compartmental activities leads to an increase in the number of identifiable quantities associated with the compartmental matrix. These identifiable quantities, which are important kinetic parameters in applications, are determined by computing the invariants of a symmetry group. This group generates the space of compartmental matrices that are compatible with a given activity distribution, input function, and set of support constraints. An example is provided where all of the compartmental spatial supports have been separated, except that of the vascular compartment. The question of estimating the identifiable parameters from SPECT and PET data is also discussed.

Absolute quantitation of myocardial blood flow with (201)Tl and dynamic SPECT in canine: optimisation and validation of kinetic modelling

PURPOSE

201Tl has been extensively used for myocardial perfusion and viability assessment. Unlike 99mTc-labelled agents, such as 99mTc-sestamibi and 99mTc-tetrofosmine, the regional concentration of 201Tl varies with time. This study is intended to validate a kinetic modelling approach for in vivo quantitative estimation of regional myocardial blood flow (MBF) and volume of distribution of 201Tl using dynamic SPECT.

METHODS

Dynamic SPECT was carried out on 20 normal canines after the intravenous administration of 201Tl using a commercial SPECT system. Seven animals were studied at rest, nine during adenosine infusion, and four after beta-blocker administration. Quantitative images were reconstructed with a previously validated technique, employing OS-EM with attenuation-correction, and transmission-dependent convolution subtraction scatter correction. Measured regional time-activity curves in myocardial segments were fitted to two- and three-compartment models. Regional MBF was defined as the influx rate constant (K(1)) with corrections for the partial volume effect, haematocrit and limited first-pass extraction fraction, and was compared with that determined from radio-labelled microspheres experiments.

RESULTS

Regional time-activity curves responded well to pharmacological stress. Quantitative MBF values were higher with adenosine and decreased after beta-blocker compared to a resting condition. MBFs obtained with SPECT (MBF(SPECT)) correlated well with the MBF values obtained by the radio-labelled microspheres (MBF(MS)) (MBF(SPECT) = -0.067 + 1.042 x MBF(MS), p < 0.001). The three-compartment model provided better fit than the two-compartment model, but the difference in MBF values between the two methods was small and could be accounted for with a simple linear regression.

CONCLUSION

Absolute quantitation of regional MBF, for a wide physiological flow range, appears to be feasible using 201Tl and dynamic SPECT.

Methodology for quantifying absolute myocardial perfusion with PET and SPECT

Noninvasive quantitative measurement of myocardial perfusion has played an important role in cardiac research and also has potential applications in clinical imaging. Positron emission tomography (PET) methods for measuring absolute perfusion are well established, although the need for an on-site cyclotron has restricted its use to a limited number of centers. Single-photon emission CT (SPECT) also has potential for quantifying myocardial perfusion and has more widespread availability. In this article we review the basic principles of absolute myocardial perfusion quantification and the radiopharmaceuticals that are available for both PET and SPECT. We also examine the extent to which recent developments in instrumentation have increased the practicality of absolute perfusion quantification in PET and the potential for absolute quantification in SPECT.

Fast and reliable estimation of multiple parametric images using an integrated method for dynamic SPECT

Dynamic single photon emission computed tomography (SPECT) has demonstrated the potential to quantitatively estimate physiological parameters in the brain and the heart. The generalized linear least square (GLLS) method is a well-established method for solving linear compartment models with fast computational speed. However, the high level of noise intrinsic in the SPECT data leads to reliability and instability problems of GLLS for generating parametric images. An integrated method is proposed to restrict the noise in both the temporal and spatial domains to estimate multiple parametric images for dynamic SPECT. This method comprises three steps which are optimum image sampling schedule in the projection space, cluster analysis applied postreconstruction and parametric image generation with GLLS. The simulation and experimental studies for the neuronal nicotine acetylcholine receptor tracer of 5-[123I]-iodo-A-85380 were employed to evaluate the performance of the proposed method. The results of influx rate of K1 and volume of distribution of Vd demonstrated that the integrated method was successful in generating low noise parametric images for high noise SPECT data without enhancing the partial volume effect. Furthermore, the integrated method is computationally efficient for potential clinical applications.

Quantitative Assessment of Regional Myocardial Flow Reserve Using Tc-99m-Sestamibi Imaging-Comparison With Results of O-15 Water PET-

BACKGROUND

The aims of this study were to develop a method for quantitative estimation of the myocardial blood flow index (MBFI) and myocardial flow reserve (MFR) of the whole left ventricle using (99m)technetium (Tc-99m)-sestamibi imaging.

METHODS AND RESULTS

Twenty-two patients with suspected coronary artery disease and 7 controls underwent both Tc-99m-sestamibi imaging and O-15 water positron emission tomography (PET). The global MBFI was calculated on the basis of the microsphere model from the ratio of the myocardial count to the area under the time - activity curve on the aortic arch. The regional MBFI was calculated from the relative distributions of Tc-99m-sestamibi uptake values. The regional MBFI and MFR (Tc-MFR) obtained using single-photon emission computed tomography were compared with the myocardial blood flow (MBF) and MFR (PET-MFR) obtained using PET as the gold standard. Regional MBFI significantly correlated with the MBF obtained using PET. Regional Tc-MFR also correlated with the regional PET-MFR, with some underestimation.

CONCLUSION

These results indicate that regional MBF and MFR may be estimated by dynamic Tc-99m-sestamibi imaging and can be used for the early detection and estimation of the functional severity of coronary lesions without the need for a PET camera.

Comparison of Static and Dynamic Cardiac Perfusion Thallium-201 SPECT

Cardiac SPECT is typically performed clinically with static imaging protocols and visually assessed for perfusion defects based upon the relative intensity of myocardial regions. Dynamic imaging, however, has the potential to provide quantitative measures of flow, possibly improving diagnosis. The objective of this study was to compare the information content of dynamic and static thallium SPECT imaging as measures of myocardial perfusion. Studies were performed in four canines, each with an occlusion placed on the left anterior descending coronary artery. Dynamic SPECT imaging was performed at rest and under adenosine stress, and subsets of the data were summed to provide corresponding static datasets for identical physiologic conditions. Microsphere-derived flow measurements were used as the gold standard. The dynamic data were fit to a two-compartment model to provide regional estimates of wash-in rate parameters. Occluded-to-normal ratios were also calculated for each canine study. The results show comparable correlations with microspheres for both wash-in and static scaled image intensities. The dynamic data provided higher defect contrasts, which were more accurate than the static occluded to normal ratios. Preliminary studies were also performed in two patients and the static and dynamic data compared. These results show that dynamic thallium imaging may provide improved diagnostic information compared to static imaging for myocardial perfusion SPECT studies.

Information technology applications in biomedical functional imaging

In parallel with rapid advances in computer technology, biomedical functional imaging is having an ever-increasing impact on healthcare. Functional imaging allows us to see dynamic processes quantitatively in the living human body. However, as we need to deal with four-dimensional time-varying images, space requirements and computational complexity are extremely high. This makes information management, processing, and communication difficult. Using the minimum amount of data to represent the required information, developing fast algorithms to process the data, organizing the data in such a way as to facilitate information management, and extracting the maximum amount of useful information from the recorded data have become important research tasks in biomedical information technology. For the last ten years, the Biomedical and Multimedia Information Technology (BMIT) Group and, recently, the Center for Multimedia Signal Processing have conducted systematic studies on these topics. Some of the results relating to functional imaging data acquisition, compression, storage, management, processing, modeling, and simulation are briefly reported in this paper.