Title :
Effects of scatter modeling on time-activity curves estimated directly from dynamic SPECT projections
Author :
Reutter, Bryan W. ; Gullberg, Grant T. ; Huesman, Ronald H.
Author_Institution :
Dept. of Nucl. Medicine & Functional Imaging, California Univ., Berkeley, CA, USA
Abstract :
Quantitative analysis of uptake and washout of cardiac single photon emission computed tomography (SPECT) radiopharmaceuticals has the potential to provide better contrast between healthy and diseased tissue, compared to conventional reconstruction of static images. Previously, we used B-splines to model time-activity curves (TACs) for segmented volumes of interest and developed fast least-squares algorithms to estimate spline TAC coefficients and their statistical uncertainties directly from dynamic SPECT projection data. This previous work incorporated physical effects of attenuation and depth-dependent collimator response. In the present work, we incorporate scatter and use a computer simulation to study how scatter modeling affects directly estimated TACs and subsequent estimates of compartmental model parameters. An idealized single-slice emission phantom was used to simulate a 15 min dynamic 99mTc-teboroxime cardiac patient study in which 500,000 events containing scatter were detected from the slice. When scatter was modeled, unweighted least-squares estimates of TACs had root mean square (RMS) error that was less than 0.6% for normal left ventricular myocardium, blood pool, liver, and background tissue volumes and averaged 3% for two small myocardial defects. When scatter was not modeled, RMS error increased to average values of 16% for the four larger volumes and 35% for the small defects. Noise-to-signal ratios (NSRs) for TACs ranged between 1-18% for the larger volumes and averaged 110% for the small defects when scatter was modeled. When scatter was not modeled, NSR improved by average factors of 1.04 for the larger volumes and 1.25 for the small defects, as a result of the better-posed (though more biased) inverse problem. Weighted least-squares estimates of TACs had slightly better NSR and worse RMS error, compared to unweighted least-squares estimates. Compartmental model uptake and washout parameter estimates obtained from the TACs were less sensitive to whether or not scatter was modeled, compared to the TACs themselves.
Keywords :
biological tissues; cardiology; image reconstruction; inverse problems; least mean squares methods; liver; medical computing; medical image processing; phantoms; pharmaceuticals; radioactive tracers; single photon emission computed tomography; splines (mathematics); technetium; 15 min; B-spline model estimation; RMS error; Tc; attenuation response; background tissue volume; blood pool; cardiac single photon emission computed tomography; compartmental model uptake parameter; computer simulation; depth-dependent collimator response; diseased tissue; dynamic 99Tcm-teboroxime cardiac patient study; dynamic SPECT projections; fast least-squares algorithm; healthy tissue; idealized single-slice emission phantom; inverse problem; liver; noise-to-signal ratio; normal left ventricular myocardium; quantitative analysis; radiopharmaceuticals; root mean square error; scatter modeling; segmented volume; small myocardial defects; spline time-activity curve coefficients; static image reconstruction; statistical uncertainties; unweighted least-squares estimates; washout parameter estimates; weighted least-squares estimates; Electromagnetic scattering; Image analysis; Image reconstruction; Image segmentation; Myocardium; Particle scattering; Scattering parameters; Single photon emission computed tomography; Spline; Uncertainty;
Conference_Titel :
Nuclear Science Symposium Conference Record, 2003 IEEE
Print_ISBN :
0-7803-8257-9
DOI :
10.1109/NSSMIC.2003.1352443