A Monte Carlo investigation of artifacts caused by liver uptake in single-photon emission computed tomography perfusion imaging with technetium 99m-labeled agents.

BACKGROUND: Significant hepatobiliary accumulation of technetium 99m-labeled cardiac perfusion agents has been shown to cause alterations in the apparent localization of the agents in the cardiac walls. A Monte Carlo study was conducted to investigate the hypothesis that the cardiac count changes are due to the inconsistencies in the projection data input to reconstruction, and that correction of the causes of these inconsistencies before reconstruction, or including knowledge of the physics underlying them in the reconstruction algorithm, would virtually eliminate these artifacts. METHODS AND RESULTS: The SIMIND Monte Carlo package was used to simulate 64 x 64 pixel projection images at 128 angles of the three-dimensional mathematical cardiac-torso (MCAT) phantom. Simulations were made of (1) a point source in the liver, (2) cardiac activity only, and (3) hepatic activity only. The planar projections and reconstructed point spread functions (PSFs) of the point source in the liver were investigated to study the nature of the inconsistencies introduced into the projections by imaging, and how these affect the distribution of counts in the reconstructed slices. Bull's eye polar maps of the counts at the center of the left ventricular wall of filtered back-projection (FBP) and maximum-likelihood expectation-maximization (MLEM) reconstructions of projections with solely cardiac activity, and with cardiac activity plus hepatic activity scaled to have twice the cardiac concentration, were compared to determine the magnitude and location of apparent changes in cardiac activity when hepatic activity is present. Separate simulations were made to allow the investigation of stationary spatial resolution, distance-dependent spatial resolution, attenuation, and scatter. The point source projections showed significant inconsistencies as a function of projection angle with the largest effect being caused by attenuation. When consistent projections were simulated, no significant impact of hepatic activity on cardiac counts was noted with FBP, or 100 iterations of MLEM. With inconsistent projections, reconstruction of 180 degrees resulted in greater apparent cardiac count losses than did 360 degrees reconstruction for both FBP and MLEM. The incorporation of attenuation correction in MLEM reconstruction reduced the changes in cardiac counts to that seen in simulations in which attenuation was not included, but resulted in increased apparent localization of activity in the posterior wall of the left ventricle when scatter was present in the simulated images. CONCLUSIONS: The apparent alterations in cardiac counts when significant hepatic localization is present is due to the inconsistency of the projections inherent in imaging. Prior correction of these, or accounting for them in the reconstruction algorithm, will virtually eliminate them as causes of artifactual changes in localization. Attenuation correction and scatter correction are both required to overcome the major sources of apparent count changes in the heart associated with hepatic uptake.

Collimator optimization for lesion detection incorporating prior information about lesion size.

A Bayesian estimator has been developed as a paradigm for human observer performance in detecting lesions of unknown size in a uniform noisy background. The Bayesian observer used knowledge of the range of possible lesion sizes as a prior; its predictions agreed well with the results of a six-observer perceptual study. The average human response to changes in collimator resolution, as measured by the detectability index, dA, was tracked by the Bayesian detector's signal-to-noise ratio (SNR) somewhat better than by two other estimation models based, respectively, on lesser and greater degrees of lesion size uncertainty. As the range of possible lesion sizes increased, the Bayesian detector's SNR decreased and the optimal collimator resolution shifted towards better resolution. An analytic approximation for the variance of lesion activity estimates (which included the same prior) was shown to predict the variance of the Bayesian estimator over a wide range of collimator resolution values. Because the bias of the Bayesian estimator was small (< 1%), the analytic variance estimate permitted a rapid and convenient prediction of the Bayesian detection SNR. This calculation was then used to optimize the geometric parameters of a two-layer tungsten collimator being constructed from crossed grids for a new imaging detector. A Monte Carlo program was first run to estimate all contributions to the radial point-spread function for collimators of differing tungsten contents and spatial resolution values, imaging 140-keV photons emitted from the center of a 15-cm-diameter, water-filled attenuator. The optimal collimator design for detecting lesions with unknown diameters in the range 2.5-7.5 mm yielded a system resolution of approximately 8.5-mm FWHM, a geometric collimator efficiency of 1.21 x 10(-4), and a single-septum penetration probability of 1%.