Optimization of Ga-67 imaging for detection and estimation tasks: dependence of imaging performance on spectral acquisition parameters.
We have compared the use of two (93 and 185 keV) and three (93, 185, and 300 keV) photopeaks for Ga-67 tumor imaging and optimized the placement of each energy window.


METHODS
The bases for optimization and evaluation were ideal and Bayesian signal-to-noise ratios (SNR) for the detection of spheres embedded in a realistic anthropomorphic digital torso phantom and ideal SNR for the estimation of their size and activity concentration. Seven spheres of radii ranging from 1 to 3 cm, located at several sites in the torso, were simulated using a realistic Monte Carlo program. We also calculated the ideal SNR for the detection from simple phantom acquisitions.


RESULTS
For detection and estimation tasks, the optimum windows were identical for all sphere sizes and locations. For the 93 keV photopeak, the optimal window was 84-102 keV for the detection and 87-102 keV for estimation; these windows are narrower than the 20% window often used in the clinic (83-101 keV). For the 185 keV photopeak, the optimal window was 170-220 keV for the detection and 170-215 keV for estimation; these are substantially different than the 15% window used in our clinic (171-199 keV). For the 300 keV photopeak, the optimal window for detection was 270-320 keV, and for estimation, 280-320 keV. Using the three optimized, rather than only the two lower-energy, windows yielded a 9% increase in the SNR for the detection of the 3 cm diam sphere (a 12% increase for a 2 cm diam sphere) and a 7% increase in the SNR for estimation of its size. For the acquired phantom data, detection also increased by 9%-12% when using three, rather than two, energy windows.
El Fakhri
Georges
G
Department of Radiology, Harvard Medical School and Brigham and Women's Hospital, Boston, Massachusetts 02115, USA. elfakhri@bwh.harvard.edu
Moore
Stephen C
SC
Kijewski
Marie Foley
MF
D000005:Abdomen / Q000000981:diagnostic imaging*; D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D005710:Gallium Radioisotopes; D006801:Humans; D008297:Male; D008954:Models, Biological; D009010:Monte Carlo Method; D011786:Quality Control; D019275:Radiopharmaceuticals; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013269:Stochastic Processes; D013909:Thorax / Q000000981:diagnostic imaging*; D015899:Tomography, Emission-Computed, Single-Photon / Q000379:methods*
D005710:Gallium Radioisotopes; D019275:Radiopharmaceuticals