Purpose:One issue with amplitude binning list-mode studies in SPECT for respiratory motion correction is that variation in the patient's respiratory pattern will result in binned motion states with little or no counts at various projection angles. The reduced counts result in limited-angle reconstruction artifacts which can impact the accuracy of the necessary motion estimation needed to correct the images. In this work, the authors investigate a method to overcome the effect of limited-angle reconstruction artifacts in SPECT when estimating respiratory motion. Methods: In the first pass of the reconstruction method, only the projection angles with significant counts in common between the binned respiratory states are used in order to better estimate the motion between them. After motion estimation, the estimates are used to correct for motion within iterative reconstruction using all of the acquired projection data. Results: Using simulated SPECT studies based on the NCAT phantom, the authors demonstrate the problem caused by having data available for only a limited number of angles when estimating motion and the utility of the proposed method in diminishing this error. For NCAT data sets with a clinically appropriate level of Poisson noise, the average registration error for motion with the proposed method was always less with the use of their algorithm, the reduction being statistically significant ͑p Ͻ 0.05͒ in the majority of cases. The authors illustrate the ability of their method to correct the degradations caused by respiratory motion in short-axis slices and polar maps of the NCAT phantom for cases with 1 and 2 cm amplitudes of respiratory motion. In four cardiacperfusion patients acquired on the same day, the authors demonstrate the large variability of the number of counts in the amplitude-binned projections. Finally, the authors demonstrate a visual improvement in the slices and polar maps of patient studies with the algorithm for respiratory motion correction. Conclusions: The authors' method shows promise in reducing errors in respiratory motion estimation despite the presence of limited-angle reconstruction effects due to irregularity in respiration. Improvements in image quality were observed in both simulated and clinical studies.

Our overall research goal is to devise a robust method of tracking and compensating patient motion by combining an emission data based approach with a visual tracking system (VTS) that provides an independent estimate of motion. Herein, we present the latest hardware configuration of the VTS, a test of the accuracy of motion tracking by it, and our solution for synchronization between the SPECT and the optical acquisitions. The current version of the VTS includes stereo imaging with sets of optical network cameras with attached light sources, a SPECT/VTS calibration phantom, a black stretchable garment with reflective spheres to track chest motion, and a computer to control the cameras. The computer also stores the JPEG files generated by the optical cameras with synchronization to the list-mode acquisition of events on our SPECT system. Five Axis PTZ 2130 network cameras (Axis Communications AB, Lund, Sweden) were used to track motion of spheres with a highly retro-reflective coating using stereo methods. The calibration phantom is comprised of seven reflective spheres designed such that radioactivity can be added to the tip of the mounts holding the spheres. This phantom is used to determine the transformation to be applied to convert the motion detected by the VTS into the SPECT coordinates system. The ability of the VTS to track motion was assessed by comparing its results to those of the Polaris infra-red tracking system (Northern Digital Inc. Waterloo, ON, Canada). The difference in the motions assessed by the two systems was generally less than 1mm. Synchronization was assessed in two ways. First, optical cameras were aimed at a digital clock and the elapsed time estimated by the cameras was compared to the actual time shown by the clock in the images. Second, synchronization was also assessed by moving a radioactive and reflective sphere three times during concurrent VTS and SPECT acquisitions and comparing the time at which motion occurred in the optical and SPECT images. The results show that optical and SPECT images stay synchronized within a 150 ms range. The 100Mbit network load is less than 10%, and the computer's CPU load is between 15 and 25%; thus, the VTS can be improved by adding more cameras or by increasing the image size and/or resolution while keeping an acquisition rate of 30 images per second per camera.

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In this paper, we investigate the use of a numerical observer to optimize ordered-subset expectation maximization (OSEM) reconstructions for the detection of coronary artery disease (CAD). The parameters optimized were the iteration number and the full-width at half-maximum of three-dimensional Gaussian postfiltering. The numerical observer employed in the optimization was the channelized Hotelling observer (CHO). The CHO had been used previously to rank tumor detection accuracy for different reconstruction strategies in Ga-67 images, showing good agreement with the rankings of human observers. The intent of this paper was to determine if this CHO could also be employed for the detection of CAD. Results indicate that when grayscale (quantized) images are used, the CHO optimization results correlate well with human observers. On the other hand, when the CHO was used with floating-point images, it provided very good detection performance even when the images were excessively filtered. This result was at odds with the human-observer performance which showed a decrease in detection accuracy with highly smoothed images. This reflects the need to better model the detection task of the human observers who usually view and rank grayscale images and by appropriately modeling the image noise that quantization introduces, we show that the CHO can better match human-observer detection performance.