Estimation and correction of cardiac respiratory motion in SPECT in the presence of limited-angle effects due to irregular respiration.

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<0.05) 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 cardiac-perfusion 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.

Impact on reader performance for lesion-detection/ localization tasks of anatomical priors in SPECT reconstruction.

With increasing availability of multimodality imaging systems, high-resolution anatomical images can be used to guide the reconstruction of emission tomography studies. By measuring reader performance on a lesion detection task, this study investigates the improvement in image-quality due to use of prior anatomical knowledge, for example organ or lesion boundaries, during SPECT reconstruction. Simulated (67)Ga -citrate source and attenuation distributions were created from the mathematical cardiac-torso (MCAT) anthropomorphic digital phantom. The SIMIND Monte Carlo software was then used to generate SPECT projection data. The data were reconstructed using the De Pierro maximum a posteriori (MAP) algorithm and the rescaled-block-iterative (RBI) algorithm for comparison. We compared several degrees of prior knowledge about the anatomy: no knowledge about the anatomy; knowledge of organ boundaries; knowledge of organ and lesion boundaries; and knowledge of organ, lesion, and pseudo-lesion (non-emission uptake altering) boundaries. The MAP reconstructions used quadratic smoothing within anatomical regions, but not across any provided region boundaries. The reconstructed images were read by human observers searching for lesions in a localization receiver operating characteristic (LROC) study of the relative detection/localization accuracies of the reconstruction algorithms. Area under the LROC curve was computed for each algorithm as the comparison metric. We also had humans read images reconstructed using different prior strengths to determine the optimal trade-off between data consistency and the anatomical prior. Finally by mixing together images reconstructed with and without the prior, we tested to see if having an anatomical prior only some of the time changes the observer's detection/localization accuracy on lesions where no boundary prior is available. We found that anatomical priors including organ and lesion boundaries improve observer performance on the lesion detection/localization task. Use of just organ boundaries did not provide a statistically significant improvement in performance however. We also found that optimal prior strength depends on the level of anatomical knowledge, with a broad plateau in which observer performance is near optimal. We found no evidence that having anatomical priors use lesion boundaries only when available changes the observer's performance when they are not available. We conclude that use of anatomical priors with organ and lesion boundaries improves reader performance on a lesion-detection/localization task, and that pseudo-lesion boundaries do not hurt reader performance. However, we did not find evidence that a prior using only organ boundaries helps observer performance. Therefore we suggest prior strength should be tuned to the organ-only case, since a prior will likely not be available for all lesions.

An Adaptive Approach to Decomposing Patient-Motion Tracking Data Acquired During Cardiac SPECT Imaging.

Patient motion during cardiac SPECT imaging can cause diagnostic imaging artifacts. We have implemented a Neural Network (NN) approach to decompose monitored patient motion data, gathered during cardiac SPECT imaging, using the Polaris stereo-IR real-time motion-tracking system. Herein, we show the successful decomposition of Polaris motion data into rigid body motion (RBM) and respiratory motion (RM). The motivation for separating RM from RBM is that each is corrected using different methods. The NN requires the input of a RBM threshold sensitivity limit, as well as the median filter window width. A two step approach can be used in setting the median filter width. In the 1(st) NN run the median filter window width is initially set to a "fixed" width typical of the respiration period. This 1(st) NN run does an initial decomposition of the data into RM and RBM. The RM is then fed into an FFT algorithm to produce a respiratory period output file for use during a 2(nd) NN run, where the median filter width can "adapt" to the patient respiratory rate at each time point. Implementation of the NN was in the UNIX environment with Interactive Data Language (IDL). Decomposition of simulated "signals known exactly" RBM and RM resulted in average value errors less than 0.11 mm for RBM steps, and an overall root mean square error of only 0.3 mm for RM or RBM. Volunteer RBM and RM Polaris data were successfully decomposed by the NN with RBM steps resolved with an average difference of only 0.8 mm as compared to values displayed on the SPECT gantry console which are only to the nearest mm. A plot of the NN RM trace and the synchronized trace from a pneumatic bellows shows virtually identical characteristics. Anthropomorphic phantom RBM and RM were decomposed and used to correct motion in SPECT images during reconstruction. The motion corrected slices looked visually identical to slices acquired without motion, and comparison of slice count profiles further confirmed the correction.

Human-observer LROC study of lesion detection in Ga-67 SPECT images reconstructed using MAP with anatomical priors.

We compare the image quality of SPECT reconstruction with and without an anatomical prior. Area under the localization-response operating characteristic (LROC) curve is our figure of merit. Simulated Ga-67 citrate images, a SPECT lymph-nodule imaging agent, were generated using the MCAT digital phantom. Reconstructed images were read by human observers.Several reconstruction strategies are compared, including rescaled block iterative (RBI) and maximum-a-posteriori (MAP) with various priors. We find that MAP reconstruction using prior knowledge of organ and lesion boundaries significantly improves lesion-detection performance (p < 0.05). Pseudo-lesion boundaries, regions without increased uptake which are incorrectly treated as prior knowledge of lesion boundaries, do not decrease performance.

A Robust Visual Tracking System for Patient Motion Detection in SPECT: Hardware Solutions.

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.

Feasibility of Stereo-Infrared Tracking to Monitor Patient Motion During Cardiac SPECT Imaging.

Patient motion during cardiac SPECT imaging can cause diagnostic imaging artifacts. We investigated the feasibility of monitoring patient motion using the Polaris motion-tracking system. This system uses passive infrared reflection from small spheres to provide real-time position data with vendor stated 0.35 mm accuracy and 0.2 mm repeatability. In our configuration, the Polaris system views through the SPECT gantry toward the patient's head. List-mode event data was temporally synchronized with motion-tracking data utilizing a modified LabVIEW virtual instrument that we have employed in previous optical motion-tracking investigations. Calibration of SPECT to Polaris coordinates was achieved by determining the transformation matrix necessary to align the position of four reflecting spheres as seen by Polaris, with the location of Tc-99m activity placed inside the sphere mounts as determined in SPECT reconstructions. We have successfully tracked targets placed on volunteers in simulated imaging positions on the table of our SPECT system. We obtained excellent correlation (R(2) > 0.998) between the change in location of the targets as measured by our SPECT system and the Polaris. We have also obtained excellent agreement between the recordings of the respiratory motion of four targets attached to an elastic band wrapped around the abdomen of volunteers and from a pneumatic bellows. We used the axial motion of point sources as determined by the Polaris to correct the motion in SPECT image acquisitions yielding virtually identical point source FWHM and FWTM values, and profiled maximum heart wall counts of cardiac phantom images, compared to the reconstructions with no motion.

Analytic and iterative reconstruction algorithms in SPECT.

Images of the inside of the human body can be obtained noninvasively using tomographic acquisition and processing techniques. In particular, these techniques are commonly used to obtain images of a gamma-emitter distribution after its administration in the human body. The reconstructed images are obtained given a set of their projections, acquired using rotating gamma cameras. A general overview of analytic and iterative methods of reconstruction in SPECT is presented with a special focus on filter backprojection (FBP), conjugate gradient, maximum likelihood expectation maximization, and maximum a posteriori expectation maximization algorithms. The FBP algorithm is faster than iterative algorithms, with the latter providing a framework for accurately modeling the emission and detection processes.