The long term goals of this project are to enhance the capabilities of single photon emission computed tomography (SPECT) to image in vivo distributions of Tc-99m- and Tl-201- radiolabeled pharmaceuticals, and to improve SPECT quantification of source distribution parameters such as volumes, activities and concentrations. The main hypothesis of this project is that SPECT can be improved qualitatively and quantitatively by 1) using converging beam SPECT geometries, i.e. fan beam, cone beam, astigmatic, spatially varying, or (for limited source sizes) ultra-high resolution pinhole collimation; and 2) implementing reconstruction strategies that use a priori source information and account for source/acquisition factors such as attenuation, scatter, and geometric collimator response. We propose to investigate this hypothesis by implementing converging beam geometries appropriate for a triple camera SPECT system and reconstruction algorithms that model the acquisition process and gamma ray interactions within the source and surrounding attenuating medium. Filtered backprojection (FBP) is widely used since it offers the practical advantage of fast computational speed; however, with Maximum Likelihood-Expectation Maximization (ML-EM) and Bayesian approaches arbitrary acquisition geometries (cone beam, astigmatic, and spatially varying collimation) can be implemented appropriately within the reconstruction algorithm. Bayesian reconstruction approaches can integrally include a priori source distribution information. For SPECT cardiac imaging, the effects of heart wall motion also will be investigated. These acquisition geometries and algorithms will be qualitatively and quantitatively evaluated using Monte Carlo simulations and experimental scans of anthropomorphic phantoms, and with patient and animal studies. To achieve our scientific objectives we propose the following specific aims: A. SPECT Cardiac Imaging. Implement and evaluate 3D FBP, constrained ML-EM and 3D Bayesian reconstruction algorithms for parallel and converging beam SPECT imaging of the heart. The algorithms will account for the effects of geometric system response, nonuniform attenuation and scatter. A new spatially varying focusing collimator will be designed, built, and evaluated. B. SPECT Brain Imaging. Implement and evaluate 3D FBP, constrained ML-EM and 3D Bayesian reconstruction algorithms for converging beam SPECT imaging of the brain. The algorithms will account for the effects of geometric system response, attenuation and scatter. A new type of converging beam collimator will be designed, built, and evaluated. C. SPECT Pinhole Imaging. Develop and evaluate small-field-of-view, millimeter-resolution pinhole SPECT system. Iterative and FBP algorithms for single and multiple pinhole SPECT will be implemented and evaluated. Pinhole collimators for a triple camera SPECT system will be designed, built and evaluated.

Agency
National Institute of Health (NIH)
Institute
National Cancer Institute (NCI)
Type
Research Project (R01)
Project #
5R01CA033541-15
Application #
2007385
Study Section
Diagnostic Radiology Study Section (RNM)
Project Start
1983-03-01
Project End
1998-12-31
Budget Start
1997-01-01
Budget End
1997-12-31
Support Year
15
Fiscal Year
1997
Total Cost
Indirect Cost
Name
Duke University
Department
Radiation-Diagnostic/Oncology
Type
Schools of Medicine
DUNS #
071723621
City
Durham
State
NC
Country
United States
Zip Code
27705
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