The proposed research extends our previous work on evaluation of scatter and attenuation correction methods using task-dependent criteria to more complex models incorporating realistic anatomy. Estimation performance from simulated and phantom images, reconstructed by filtered backprojection of data corrected by these methods, will be compared to the best possible performance from the measured data. This ideal performance will be represented by the Cramer-Rao lower bound (CRB) on variance of estimated model parameters. Values of the CRB will be calculated from the expected sinograms, which will be determined by Monte Carlo (MC) simulation. Any difference between actual and ideal performance would represent the potential advantage to be gained by iterative reconstruction. We will also continue our development of task-based figures-of-merit, particularly those which apply to low-count conditions or to tasks which incorporate a priori information. The imaging tasks on which performance measures will be based include clinical classification tasks related to Alzheimer's disease, as well as the mathematically modeled estimation tasks. The proposed research is also directed toward several objectives beyond the major goal of evaluation of correction methods. The first of these is to improve estimation performance by altering the data collection strategy. An analysis completed during the previous project period has shown that collimators with centrally peaked sensitivity functions can significantly improve task performance. During the proposed project period, we will validate these improvements by phantom experiments. We are also addressing the question of the value of a priori information, such as intermodality transfer of structure boundaries, in estimation tasks. We will evaluate, using a clinical classification task, a method, developed during the previous project period, of estimating structure activity using such information. Progress in these first two areas is expected to have significant clinical impact. At present deep brain structures, although known to be involved in dementia, are rarely examined because of difficulties in quantifying their activity. These problems are related to high noise levels at the center of the brain, the small size of the structures, and imprecision of defining boundaries of these structures from the functional SPECT images, the very issues addressed by the proposed research. Finally, we will continue the development of methods to handle estimation performance at low signal-to-noise ratio (SNR), where the CRB is not attainable.

Agency
National Institute of Health (NIH)
Institute
National Institute of Neurological Disorders and Stroke (NINDS)
Type
Research Project (R01)
Project #
2R01NS031902-05
Application #
2037677
Study Section
Diagnostic Radiology Study Section (RNM)
Program Officer
Oliver, Eugene J
Project Start
1993-08-01
Project End
2001-11-30
Budget Start
1996-12-01
Budget End
1997-11-30
Support Year
5
Fiscal Year
1997
Total Cost
Indirect Cost
Name
Brigham and Women's Hospital
Department
Type
DUNS #
071723621
City
Boston
State
MA
Country
United States
Zip Code
02115
El Fakhri, Georges; Moore, Stephen C; Kijewski, Marie Foley (2002) Optimization of Ga-67 imaging for detection and estimation tasks: dependence of imaging performance on spectral acquisition parameters. Med Phys 29:1859-66
Moore, S C; Kijewski, M F; Muller, S P et al. (2001) Evaluation of scatter compensation methods by their effects on parameter estimation from SPECT projections. Med Phys 28:278-87
El Fakhri, G; Moore, S C; Maksud, P et al. (2001) Absolute activity quantitation in simultaneous 123I/99mTc brain SPECT. J Nucl Med 42:300-8
Abbey, C K; Clarkson, E; Barrett, H H et al. (1998) A method for approximating the density of maximum-likelihood and maximum a posteriori estimates under a Gaussian noise model. Med Image Anal 2:395-403
Zimmerman, R E; Williams, B B; Chan, K H et al. (1997) Limitations of dual-photopeak window scatter correction for brain imaging. J Nucl Med 38:1902-6
Kijewski, M F; Muller, S P; Moore, S C (1997) Nonuniform collimator sensitivity: improved precision for quantitative SPECT. J Nucl Med 38:151-6
Logigian, E L; Johnson, K A; Kijewski, M F et al. (1997) Reversible cerebral hypoperfusion in Lyme encephalopathy. Neurology 49:1661-70
Moore, S C; deVries, D J; Nandram, B et al. (1995) Collimator optimization for lesion detection incorporating prior information about lesion size. Med Phys 22:703-13