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A quantitative study of motion estimation methods on 4D cardiac gated SPECT reconstruction.

ABSTRACT: Motion-compensated temporal processing can have a major impact on improving the image quality in gated cardiac single photon emission computed tomography (SPECT). In this work, we investigate the effect of different optical flow estimation methods for motion-compensated temporal processing in gated SPECT. In particular, we explore whether better motion estimation can substantially improve reconstructed image quality, and how the estimated motion would compare to the ideal case of known motion in terms of reconstruction.We consider the following three methods for obtaining the image motion in 4D reconstruction: (1) the Horn-Schunck optical flow equation (OFE) method, (2) a recently developed periodic OFE method, and (3) known cardiac motion derived from the NURBS-based cardiac-torso (NCAT) phantom. The periodic OFE method is used to exploit the inherent periodic nature in cardiac gated images. In this method, the optical flow in a sequence is modeled by a Fourier harmonic representation, which is then estimated from the image data. We study the impact of temporal processing on 4D reconstructions when the image motion is obtained with the different methods above. For quantitative evaluation, we use simulated imaging with multiple noise realizations from the NCAT phantom, where different patient geometry and lesion sizes are also considered. To quantify the reconstruction results, we use the following measures of reconstruction accuracy and defect detection in the myocardium: (1) overall error level in the myocardium, (2) regional accuracy of the left ventricle (LV) wall, (3) accuracy of regional time activity curves of the LV, and (4) perfusion defect detectability with a channelized Hotelling observer (CHO). In addition, we also examine the effect of noise on the distortion in the reconstructed LV wall shape by detecting its contours. As a preliminary demonstration, these methods are also tested on two sets of clinical acquisitions.For the different quantitative measures considered, the periodic OFE further improved the reconstruction accuracy of the myocardium compared to OFE in 4D reconstruction; its improvement in reconstruction almost matched that of the known motion. Specifically, the overall mean-squared error in the myocardium was reduced by over 20% with periodic OFE; with noise level fixed at 10%, the regional bias on the LV was reduced from 20% (OFE) to 14% (periodic OFE), compared to 11% by the known motion. In addition, the CHO results show that there was also improvement in lesion detectability with the periodic OFE. The regional time activity curves obtained with the periodic OFE were also observed to be more consistent with the reference; in addition, the contours of the reconstructed LV wall with the periodic OFE were demonstrated to show less degree of variations among different noise realizations. Such improvements were also consistent with the results obtained from the clinical acquisitions.Use of improved optical flow estimation can further improve the accuracy of reconstructed images in 4D. The periodic OFE method not only can achieve improvements over the traditional OFE, but also can almost match that of the known motion in terms of the several quality measures considered.

SUBMITTER: Qi W

PROVIDER: S-EPMC3422358 | biostudies-other | 2012 Aug

REPOSITORIES: biostudies-other

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Project description:Due to the combination of high-frequency use and relatively high diagnostic radiation dose (>9 mSv for one scan), there is a need to lower the radiation dose used in myocardial perfusion imaging (MPI) studies in cardiac gated single photon emission computed tomography (GSPECT) in order to reduce its population based cancer risk. The aim of this study is to assess quantitatively the potential utility of advanced 4D reconstruction for GSPECT for significantly lowered imaging dose.For quantitative evaluation, Monte Carlo simulation with the 4D NURBS-based cardiac-torso (NCAT) phantom is used for GSPECT imaging at half and quarter count levels in the projections emulating lower injected activity (dose) levels. Both 4D and 3D reconstruction methods are applied at these lowered dose levels, and compared with standard clinical spatiotemporal reconstruction (ST121) at full dose using a number of metrics on the reconstructed images: (1) overall reconstruction accuracy of the myocardium, (2) regional bias-variance analysis of the left ventricle (LV) wall, (3) uniformity of the LV wall, (4) accuracy of the time activity curve (TAC) of the LV wall, and (5) detectability of perfusion defects using channelized Hotelling observer. As a preliminary demonstration, two sets of patient data acquired in list-mode are used to illustrate the conservation of both image quality and LV ejection fraction (LVEF) by 4D reconstruction where only a portion of the acquired counts at each projection angle are used to mimic low-dose acquisitions.Compared to ST121 at standard dose, even at quarter dose 4D achieved better performance on overall reconstruction accuracy of the myocardium (28.7% improvement on relative root mean square error: standard vs 4D quarter p-value < 10(-30)), regional bias-variance analysis, and similar performance on accuracy of the TAC of the LV wall and detectability of perfusion defects. A slight degradation in uniformity of the LV wall was observed in 4D at quarter dose due to use of scatter correction which increases reconstruction variance. The reconstructed images from simulated and patient data show that 4D at quarter dose is visually comparable to ST121 at standard dose, if not better. Compared to ST121 and 3D, 4D images exhibit less noise artifacts and better definition of the LV wall. The 4D images are also observed to be more consistent between half dose and quarter dose. 4D also yields more consistent LVEF results at different count levels on the patient data.With various quantitative metrics 4D reconstruction is demonstrated to achieve better or comparable performance at quarter dose (∼2.25 mSv, 75% dose reduction) compared to conventional clinical reconstruction at standard dose (∼9 mSv). Preliminary results from two patient datasets also show that 4D at an equivalent quarter dose can achieve better performance than clinical and 3D methods at higher dose levels. Such a significant dose reduction (75%) has not been demonstrated quantitatively in previous studies in GSPECT. These promising results warrant further investigations on the lower bound of dose reduction with different reconstruction strategies and more comprehensive clinical studies with greater patient variability.

Project description:In gated cardiac single photon emission computed tomography (SPECT), image reconstruction is often hampered by various degrading factors including depth-dependent spatial blurring, attenuation, scatter, motion blurring, and low data counts. Consequently, there has been significant development in image reconstruction methods for improving the quality of reconstructed images. The goal of this work is to investigate how these degrading factors will impact the reconstructed myocardium when different reconstruction methods are used.The authors conduct a comparative study of the effects of these degrading factors on the accuracy of myocardium by several reconstruction algorithms, including (1) a clinical spatiotemporal processing method, (2) maximum likelihood (ML) estimation, (3) 3D maximum a posteriori (MAP) estimation, (4) 3D MAP with posttemporal filtering, and (5) motion-compensated spatiotemporal (4D) reconstruction. To quantify the reconstruction results, the authors use the following measures on different aspects of the myocardium: (1) overall error level in the myocardium, (2) regional accuracy of the left ventricle (LV) wall, (3) uniformity of the LV, (4) accuracy of regional time activity curves by normalized cross-correlation coefficient, and (5) perfusion defect detectability. The authors also assess the effectiveness of degrading corrections in reconstruction by considering an upper bound for each reconstruction method, which represents what would be achieved by each method if the acquired data were free from attenuation and scatter degradations. In the experiments the authors use Monte Carlo simulated cardiac gated SPECT imaging based on the 4D NURBS-based cardiac-torso (NCAT) phantom with different patient geometry and lesion settings, in which the simulated ground truth is known for the purpose of quantitative evaluation.The results demonstrate that use of temporal processing in reconstruction (Methods 1, 4, and 5 above) can greatly improve the reconstructed myocardium in terms of both error level and perfusion defect detection. In low-count gated studies, it can have even greater impact than other degrading factors. Both attenuation and scatter corrections can lead to reduced error levels in the myocardium in all methods; in particular, with 4D the bias can be reduced by as much as four-fold compared to no correction. There is a slight increase in noise level observed with scatter correction. A significant improvement in heart wall appearance is demonstrated in reconstruction results from three sets of clinical acquisitions as correction for degradations is combined with refinement of temporal filtering.Correction for degrading factors such as resolution, attenuation, scatter, and motion blur can all lead to improved image quality in cardiac gated SPECT reconstruction. However, their effectiveness could also vary with the reconstruction algorithms used. Both attenuation and scatter corrections can effectively reduce the bias level of the reconstructed LV wall, though scatter correction is also observed to increase the variance level. Use of temporal processing in reconstruction can have greater impact on the accuracy of the myocardium than correction of other degrading factors. Overall, use of degrading corrections in 4D reconstruction is shown to be most effective for improving both reconstruction accuracy of the myocardium and detectability of perfusion defects in gated images.

Project description:PurposeCardiac perfusion PET data can be reconstructed as a dynamic sequence and kinetic modeling performed to quantify myocardial blood flow, or reconstructed as static gated images to quantify function. Parametric images from dynamic PET are conventionally not gated, to allow use of all events with lower noise. An alternative method for dynamic PET is to incorporate the kinetic model into the reconstruction algorithm itself, bypassing the generation of a time series of emission images and directly producing parametric images. So-called "direct reconstruction" can produce parametric images with lower noise than the conventional method because the noise distribution is more easily modeled in projection space than in image space. In this work, we develop direct reconstruction of cardiac-gated parametric images for 82 Rb PET with an extension of the Parametric Motion compensation OSEM List mode Algorithm for Resolution-recovery reconstruction for the one tissue model (PMOLAR-1T).MethodsPMOLAR-1T was extended to accommodate model terms to account for spillover from the left and right ventricles into the myocardium. The algorithm was evaluated on a 4D simulated 82 Rb dataset, including a perfusion defect, as well as a human 82 Rb list mode acquisition. The simulated list mode was subsampled into replicates, each with counts comparable to one gate of a gated acquisition. Parametric images were produced by the indirect (separate reconstructions and modeling) and direct methods for each of eight low-count and eight normal-count replicates of the simulated data, and each of eight cardiac gates for the human data. For the direct method, two initialization schemes were tested: uniform initialization, and initialization with the filtered iteration 1 result of the indirect method. For the human dataset, event-by-event respiratory motion compensation was included. The indirect and direct methods were compared for the simulated dataset in terms of bias and coefficient of variation as a function of iteration.ResultsConvergence of direct reconstruction was slow with uniform initialization; lower bias was achieved in fewer iterations by initializing with the filtered indirect iteration 1 images. For most parameters and regions evaluated, the direct method achieved the same or lower absolute bias at matched iteration as the indirect method, with 23%-65% lower noise. Additionally, the direct method gave better contrast between the perfusion defect and surrounding normal tissue than the indirect method. Gated parametric images from the human dataset had comparable relative performance of indirect and direct, in terms of mean parameter values per iteration. Changes in myocardial wall thickness and blood pool size across gates were readily visible in the gated parametric images, with higher contrast between myocardium and left ventricle blood pool in parametric images than gated SUV images.ConclusionsDirect reconstruction can produce parametric images with less noise than the indirect method, opening the potential utility of gated parametric imaging for perfusion PET.

Project description:The acquisition of data for cardiac imaging using a C-arm computed tomography system requires several seconds and multiple heartbeats. Hence, incorporation of motion correction in the reconstruction step may improve the resulting image quality. Cardiac motion can be estimated by deformable three-dimensional (3D)/3D registration performed on initial 3D images of different heart phases. This motion information can be used for a motion-compensated reconstruction allowing the use of all acquired data for image reconstruction. However, the result of the registration procedure and hence the estimated deformations are influenced by the quality of the initial 3D images. In this paper, the sensitivity of the 3D/3D registration step to the image quality of the initial images is studied. Different reconstruction algorithms are evaluated for a recently proposed cardiac C-arm CT acquisition protocol. The initial 3D images are all based on retrospective electrocardiogram (ECG)-gated data. ECG-gating of data from a single C-arm rotation provides only a few projections per heart phase for image reconstruction. This view sparsity leads to prominent streak artefacts and a poor signal to noise ratio. Five different initial image reconstructions are evaluated: (1) cone beam filtered-backprojection (FDK), (2) cone beam filtered-backprojection and an additional bilateral filter (FFDK), (3) removal of the shadow of dense objects (catheter, pacing electrode, etc) before reconstruction with a cone beam filtered-backprojection (cathFDK), (4) removal of the shadow of dense objects before reconstruction with a cone beam filtered-backprojection and a bilateral filter (cathFFDK). The last method (5) is an iterative few-view reconstruction (FV), the prior image constrained compressed sensing combined with the improved total variation algorithm. All reconstructions are investigated with respect to the final motion-compensated reconstruction quality. The algorithms were tested on a mathematical phantom data set with and without a catheter and on two porcine models using qualitative and quantitative measures. The quantitative results of the phantom experiments show that if no dense object is present within the scan field of view, the quality of the FDK initial images is sufficient for motion estimation via 3D/3D registration. When a catheter or pacing electrode is present, the shadow of these objects needs to be removed before the initial image reconstruction. An additional bilateral filter shows no major improvement with respect to the final motion-compensated reconstruction quality. The results with respect to image quality of the cathFDK, cathFFDK and FV images are comparable. In conclusion, in terms of computational complexity, the algorithm of choice is the cathFDK algorithm.

Project description:BackgroundMotion-compensated (MoCo) reconstruction shows great promise in improving four-dimensional cone-beam computed tomography (4D-CBCT) image quality. MoCo reconstruction for a 4D-CBCT could be more accurate using motion information at the CBCT imaging time than that obtained from previous 4D-CT scans. However, such data-driven approaches are hampered by the quality of initial 4D-CBCT images used for motion modeling.PurposeThis study aims to develop a deep-learning method to generate high-quality motion models for MoCo reconstruction to improve the quality of final 4D-CBCT images.MethodsA 3D artifact-reduction convolutional neural network (CNN) was proposed to improve conventional phase-correlated Feldkamp-Davis-Kress (PCF) reconstructions by reducing undersampling-induced streaking artifacts while maintaining motion information. The CNN-generated artifact-mitigated 4D-CBCT images (CNN enhanced) were then used to build a motion model which was used by MoCo reconstruction (CNN+MoCo). The proposed procedure was evaluated using in-vivo patient datasets, an extended cardiac-torso (XCAT) phantom, and the public SPARE challenge datasets. The quality of reconstructed images for XCAT phantom and SPARE datasets was quantitatively assessed using root-mean-square-error (RMSE) and normalized cross-correlation (NCC).ResultsThe trained CNN effectively reduced the streaking artifacts of PCF CBCT images for all datasets. More detailed structures can be recovered using the proposed CNN+MoCo reconstruction procedure. XCAT phantom experiments showed that the accuracy of estimated motion model using CNN enhanced images was greatly improved over PCF. CNN+MoCo showed lower RMSE and higher NCC compared to PCF, CNN enhanced and conventional MoCo. For the SPARE datasets, the average (± standard deviation) RMSE in mm-1 for body region of PCF, CNN enhanced, conventional MoCo and CNN+MoCo were 0.0040 ± 0.0009, 0.0029 ± 0.0002, 0.0024 ± 0.0003 and 0.0021 ± 0.0003. Corresponding NCC were 0.84 ± 0.05, 0.91 ± 0.05, 0.91 ± 0.05 and 0.93 ± 0.04.ConclusionsCNN-based artifact reduction can substantially reduce the artifacts in the initial 4D-CBCT images. The improved images could be used to enhance the motion modeling and ultimately improve the quality of the final 4D-CBCT images reconstructed using MoCo.

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A quantitative study of motion estimation methods on 4D cardiac gated SPECT reconstruction.

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