Fast direct estimation of the blood input function and myocardial time activity curve from dynamic SPECT projections via reduction in spatial and temporal dimensions

Preclinical SPECT and SPECT-CT in Oncology

Molecular imaging enables both spatial and temporal understanding of the complex biologic systems underlying carcinogenesis and malignant spread. Single-photon emission tomography (SPECT) is a versatile nuclear imaging-based technique with ideal properties to study these processes in vivo in small animal models, as well as to identify potential drug candidates and characterize their antitumor action and potential adverse effects. Small animal SPECT and SPECT-CT (single-photon emission tomography combined with computer tomography) systems continue to evolve, as do the numerous SPECT radiopharmaceutical agents, allowing unprecedented sensitivity and quantitative molecular imaging capabilities. Several of these advances, their specific applications in oncology as well as new areas of exploration are highlighted in this chapter.

Effects of the attenuation correction and reconstruction method parameters on conventional cardiac dynamic SPECT

Nuclear cardiology has not witnessed development of new tracers or hardware for many years. Hence there is a need for the development of improvised techniques. Dynamic cardiac single photon emission computed tomography (SPECT) is one such technique that has a potential to overcome the limitations of conventional myocardial SPECT including the absolute quantification of blood flow. The main goal of this study is to evaluate the effect of attenuation correction (AC) on estimation of the washout parameters extracted from dynamic SPECT using a conventional protocol. The effect of the postprocessing on quantitative evaluation of dynamic SPECT is also assessed.A physical phantom was employed to physically simulate the dynamic behavior of a heart in the thorax. Using a dual detector SPECT system, 180° tomographic data in every 90 seconds were acquired. The SPECT data were reconstructed using ordered subset expectation maximization (OSEM) method while different iterations and a Butterworth filter with different cut-off frequencies were applied. Estimated washout parameter of the time activity curves (TACs) was compared with applying AC or without it.Results show that AC can improve the bias of computed washout parameter in normal regions (average bias reduction in normal ROI: 7%). Moreover, the postreconstruction filtering and reducing the number of iterations in reconstructing phase can reduce the variance of the computed washout values in normal regions (from 3.99% for cut-off frequency 0.5 cycle/cm and 32 times update in OSEM to 2.05% for cut-off frequency 0.35 cycle/cm and 16 times update in OSEM). They also reduce the actual size of the defect region (13% reduction in defect extent for above change in reconstruction parameters).According to the results, the AC and postprocessing filtration can directly affect the standard deviation of washout value acquired by cardiac dynamic SPECT. These parameters also showed a direct effect on the defect extent in final results. The study showed that the AC may partly improve the bias of calculated normal washout value. The effect of attenuation correction on the defective washout value could not be answered comprehensively in this paper.

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.

Development of computational small animal models and their applications in preclinical imaging and therapy research

The development of multimodality preclinical imaging techniques and the rapid growth of realistic computer simulation tools have promoted the construction and application of computational laboratory animal models in preclinical research. Since the early 1990s, over 120 realistic computational animal models have been reported in the literature and used as surrogates to characterize the anatomy of actual animals for the simulation of preclinical studies involving the use of bioluminescence tomography, fluorescence molecular tomography, positron emission tomography, single-photon emission computed tomography, microcomputed tomography, magnetic resonance imaging, and optical imaging. Other applications include electromagnetic field simulation, ionizing and nonionizing radiation dosimetry, and the development and evaluation of new methodologies for multimodality image coregistration, segmentation, and reconstruction of small animal images. This paper provides a comprehensive review of the history and fundamental technologies used for the development of computational small animal models with a particular focus on their application in preclinical imaging as well as nonionizing and ionizing radiation dosimetry calculations. An overview of the overall process involved in the design of these models, including the fundamental elements used for the construction of different types of computational models, the identification of original anatomical data, the simulation tools used for solving various computational problems, and the applications of computational animal models in preclinical research. The authors also analyze the characteristics of categories of computational models (stylized, voxel-based, and boundary representation) and discuss the technical challenges faced at the present time as well as research needs in the future.

Reconstruction of 4-D dynamic SPECT images from inconsistent projections using a Spline initialized FADS algorithm (SIFADS)

In this paper, we propose and validate an algorithm of extracting voxel-by-voxel time activity curves directly from inconsistent projections applied in dynamic cardiac SPECT. The algorithm was derived based on factor analysis of dynamic structures (FADS) approach and imposes prior information by applying several regularization functions with adaptively changing relative weighting. The anatomical information of the imaged subject was used to apply the proposed regularization functions adaptively in the spatial domain. The algorithm performance is validated by reconstructing dynamic datasets simulated using the NCAT phantom with a range of different input tissue time-activity curves. The results are compared to the spline-based and FADS methods. The validated algorithm is then applied to reconstruct pre-clinical cardiac SPECT data from canine and murine subjects. Images, generated from both simulated and experimentally acquired data confirm the ability of the new algorithm to solve the inverse problem of dynamic SPECT with slow gantry rotation.