P.H. Pretorius

LROC analysis of detector-response compensation in SPECT

Localization ROC (LROC) observer studies examined whether detector response compensation (DRC) in ordered-subset, expectation-maximization (OSEM) reconstructions helps in the detection and localization of hot tumors. Simulated gallium (Ga-67) images of the thoracic region were used in the study. The projection data modeled the acquisition of attenuated 93- and 185-keV photons with a medium-energy parallel-hole collimator, but scatter was not modeled. Images were reconstructed with five strategies: (1) OSEM with no DRC; (2) OSEM preceded by restoration filtering; (3) OSEM with iterative DRC; (4) OSEM with an ideal DRC; and (5) filtered backprojection (FBP) with no DRC. All strategies included attenuation correction. There were four LROC studies conducted. In a study using a single tumor activity, the ideal DRC offered the best performance, followed by iterative DRC, restoration filtering, OSEM with no DRC, and FBP. Statistical significance at the 5% level was found between all pairs of strategies except for restoration filtering and OSEM with no DRC. A similar ranking was found for a more realistic study using multiple tumor activities. Additional studies considered the effects of OSEM iteration number and tumor activity on the detection improvement that iterative DRC offered with respect to OSEM with no DRC.

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 patients head. List-mode event data were 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/sup 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 full-width at half-maximum and full-width at tenth-maximum values, and profiled maximum heart wall counts of cardiac phantom images, compared to the reconstructions with no motion.

Correction of the respiratory motion of the heart by tracking of the center of mass of thresholded projections: a simulation study using the dynamic MCAT phantom

During normal breathing, heart motion is about 15 mm along the body axis in humans. We propose a method to track and to correct this motion after a list-mode acquisition which involves the recording of a signal proportional to respiratory volume. We use the dynamic MCAT (DMCAT) chest phantom to simulate 24 temporal frames regularly spaced during the respiratory cycle, for 60 projection angles over 360/spl deg/. A 15-mm respiratory translation motion is simulated for the heart, liver and spleen. Thresholding of projections is used to reduce the influence of static activity on calculation of the axial center-of-mass (aCOM). Variation in the impact of attenuation as a function of projections and noise in the low-count projections rebinned from list-mode acquisitions is seen to limit ones ability to track respiratory motion using the aCOM. By including the recording of a signal proportional to the relative respiratory volume with the list-mode acquisition counts from different respiratory cycles can be combined to produce projections with common respiratory volumes. We have determined that the aCOMs determined from summing these common-volume based projections over the anterior to left-anterior oblique projection angles can be used to track respiratory motion as a function of the volume signal. Using this information on the variation of the aCOM as a function of the volume signal, the entire list-mode acquisition can then be rebinned into a projection set which is corrected for respiratory motion. After motion tracking, the mean absolute difference between the true motion curve and the aCOM curve is 0.10 cm for noisy studies. After correction no heart motion is visible on a cine display of projections. The polar map of myocardial MIBI uptake after motion correction is closer to that obtained when no respiratory motion is present than without correction.

Application of the Karhunen-Loeve transform to 4D reconstruction of cardiac gated SPECT images

Reconstruction of gated SPECT images is intrinsically a four-dimensional problem. Gated SPECT studies are normally reconstructed frame by frame; thus, the time frames are treated independently. This approach fails to exploit the strong signal correlations among the time frames which are critical for noise reduction and resolution recovery. The authors investigated two reconstruction approaches, developed for dynamic PET by Wernick et al. (1997, 1999), which utilize the compression and decorrelation properties of the Karhunen-Loeve (KL) transform. In Method I, the authors temporally filter the data by using only the first few KL components, then perform frame-by-frame reconstruction. In Method II, the authors KL transform the projection data, reconstruct only the significant KL component images, then perform an inverse KL transformation to obtain the full 4D image sequence. Results indicate that Methods I and II provide better noise performance than ordinary frame-by-frame reconstruction. Additionally, Method II requires substantially fewer computations than conventional reconstruction methods.

Optimization of iterative reconstructions of /sup 99m/Tc cardiac SPECT studies using numerical observers

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.

Effect of block-iterative acceleration on Ga-67 tumor detection in thoracic SPECT

A combination of human localization receiver operating characteristic (LROC) and channelized Hotelling observer (CHO) ROC psychophysical studies were used to investigate how accelerated ordered-subset expectation maximization (OSEM) and rescaled block-iterative (RBI) EM reconstruction affect tumor detection in simulated Ga-67 SPECT images, The tumors were 1-cm-diameter spheres within the chest region of the three-dimensional mathematical cardiac-torso phantom. Previous work with iterative detector resolution compensation showed that eight iterations of the OSEM algorithm with a subset size of eight (16 subsets) offered optimal observer performance. For the LROC study in this paper, the OSEM and RBI algorithms were implemented using subset sizes P and iterations K that satisfied the relation P=K for P=1, 2, 4, and 8. The CHO was applied to reconstruction strategies that deviated from this relation. Results show that using P/spl les/2 penalized observer performance compared to strategies with larger subset sizes. Other researchers have reported on the more stable convergence and noise properties of the RBI algorithm [(Byrne, 1996) and (Lalush and Tsui, 2000)]. In a similar vein, we found that an RBI strategy with a subset size of P produced the same performance as an OSEM strategy with subset size 2P. As neither algorithm displayed a decisive advantage in speed over the other, we conclude that the RBI algorithm is the better choice for accelerating the Ga-67 reconstructions.

Correction of organ motion in SPECT using reprojection data

Organ motion during SPECT acquisition can cause artifacts in the reconstructed slices which may affect the clinical interpretation. A new algorithm is presented which corrects for translational organ motion in SPECT projection data and thus reduces the resulting artifacts. The projection data is first reconstructed and then reprojected to the original angles. These reprojection data provide a template for comparison with the true projection data to estimate motion. An organ of interest is selected interactively using a count threshold on the reconstructed slices. From this, regions of interest are reprojected and used to limit the region of comparison and improve efficiency. Parabolic interpolation is used to interpolate fractional shifts. The algorithm corrects for translational motion in the projection data along both X and Y axes. The algorithm was evaluated using point sources in air with physical motion induced during acquisition and artificially induced motion using Monte Carlo simulated MCAT phantom data. Results show that the FWHMs and FWTMs of corrected point source data compare favorably with point source data without motion induced. Polar maps of the MCAT phantom clearly show the improvement after the correction was implemented. Further validation and clinical testing are in progress.

Estimation of the Rigid-Body Motion From Three-Dimensional Images Using a Generalized Center-of-Mass Points Approach

We present an analytical method for the estimation of rigid-body motion in sets of three-dimensional (3-D) SPECT and PET slices. This method utilizes mathematically defined generalized center-of-mass points in images, requiring no segmentation. It can be applied to compensation of the rigid-body motion in both SPECT and PET, once a series of 3-D tomographic images are available. We generalized the formula for the center-of-mass to obtain a family of points comoving with the objects rigid-body motion. From the family of possible points we chose the best three points which resulted in the minimum root-mean-square difference between images as the generalized center-of-mass points for use in estimating motion. The estimated motion was used to sum the sets of tomographic images, or incorporated in the iterative reconstruction to correct for motion during reconstruction of the combined projection data. For comparison, the principle-axes method was also applied to estimate the rigid-body motion from the same tomographic images. To evaluate our method for different noise levels, we performed simulations with the MCAT phantom. We observed that though noise degraded the motion-detection accuracy, our method helped in reducing the motion artifact both visually and quantitatively. We also acquired four sets of the emission and transmission data of the Data Spectrum Anthropomorphic Phantom positioned at four different locations and/or orientations. From these we generated a composite acquisition simulating periodic phantom movements during acquisition. The simulated motion was calculated from the generalized center-of-mass points calculated from the tomographic images reconstructed from individual acquisitions. We determined that motion-compensation greatly reduced the motion artifact. Finally, in a simulation with the gated MCAT phantom, an exaggerated rigid-body motion was applied to the end-systolic frame. The motion was estimated from the end-diastolic and end-systolic images, and used to sum them into a summed image without obvious artifact. Compared to the principle-axes method, in two of the three comparisons with anthropomorphic phantom data our method estimated the motion in closer agreement to the Polaris system than the principal-axes method, while the principle-axes method gave a more accurate estimation of motion in most cases for the MCAT simulations. As an image-driven approach, our method assumes angularly complete data sets for each state of motion. We expect this method to be applied in correction of respiratory motion in respiratory gated SPECT, and respiratory or other rigid-body motion in PET

Reducing the effect of non-stationary resolution on activity quantitation with the frequency distance relationship in SPECT

The determination of quantitative parameters such as the maximum and total counts in a volume are influenced by the partial volume effect. The magnitude of this effect varies with the non-stationary spatial resolution inherent in SPECT imaging compared to the size and shape of the object, and the relative concentration of the object to its background. The objective of this investigation was to determine if the FDR (Frequency Distance Relationship) restoration filtering can reduce the impact of distance dependent spatial resolution on the quantitation of activity. An analytical projector which incorporates attenuation and distance dependent blurring was used to simulate small hot spherical objects in an cylindrical attenuator as imaged with a LEUHR collimator. FDR restoration filtering regularized using different Gaussian and parametric Wiener filters, was employed after attenuation correction with Bellinis method. Projections were also processed using Bellinis attenuation correction method followed by filtered backprojection and 3D Butterworth filtering with different cut-off frequencies. CCRs (Center Count Ratios) and TCRs (Total Count Ratios) were determined as the observed counts over true counts. Results show that after FDR restoration the CCR and TCR become approximately position invariant. However, when regularizing the FDR inverse filter with a Gaussian function, CCRs become highly unstable as the standard deviation (/spl sigma/) decreased below that at the center of rotation. The use of the Gaussian and parametric Wiener filters to regularize FDR filtering introduce noise in the CCRs but improve recovery of TCRs over that of the center of rotation.

Evaluation of scatter compensation strategies and their impact on human detection performance in Tc-99m myocardial perfusion imaging

Human-observer receiver-operating characteristic (ROC) results with clinical patient studies indicate that ordered-subset expectation-maximization (OSEM) reconstructions with a combination of corrections for attenuation, scatter, and distance-dependent resolution (DDR) significantly improves perfusion defect detection accuracy over filtered back-projection (FBP) images with no compensation. A recent Monte Carlo study has also shown that for scatter correction (SC) in particular, selection of an appropriate strategy can impact cardiac uniformity. The spatial domain based effective source scatter estimation (ESSE) technique was shown to provide more robust performance in improving cardiac uniformity than the triple-energy window (TEW) method. In this work, we investigate if further improvements in observer performance could be obtained by using the ESSE method of SC instead of the currently employed TEW SC, in combination with attenuation correction (AC) and resolution compensation (RC). We evaluated the effectiveness of the ESSE method to provide additional improvements in image quality objectively by using human-observer ROC studies on clinically acquired patient acquisitions. Results indicate that both ESSE and TEW SC in combination with AC and RC provide significantly higher detection accuracy than FBP with no compensation for the overall detection of coronary artery disease (CAD) as well as in localizing perfusion defects in the left anterior descending (LAD) and left circumflex (LCx) territories. Comparing, the two implementations of SC evaluated in this study, we note that the ESSE method resulted in larger aggregate areas under the ROC curve (A/sub z/) in each case. However, a statistically significant improvement over TEW correction was only observed in the LAD territory. This indicates that SC implemented with the ESSE and TEW methods were close in terms of their improvement in detection accuracy for perfusion defects in the clinical images of this investigation, with the ESSE method arguably being slightly better. However, the clinical implementation of ESSE will be hampered by its longer computing time.