Direct List Mode Parametric Reconstruction for Dynamic Cardiac SPECT.
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ABSTRACT:
SUBMITTER: Shi L
PROVIDER: S-EPMC7030971 | biostudies-literature | 2020 Jan
REPOSITORIES: biostudies-literature
Publications
Direct List Mode Parametric Reconstruction for Dynamic Cardiac SPECT.
Shi Luyao L Lu Yihuan Y Wu Jing J Gallezot Jean-Dominique JD Boutagy Nabil N Thorn Stephanie S Sinusas Albert J AJ Carson Richard E RE Liu Chi C
IEEE transactions on medical imaging 20190610 1
Recently introduced stationary dedicated cardiac SPECT scanners provide new opportunities to quantify myocardial blood flow (MBF) using dynamic SPECT. However, comparing to PET, the low sensitivity of SPECT scanners affects MBF quantification due to the high noise level, especially for <sup>201</sup> Thallium (<sup>201</sup>Tl) due to its typically low injected dose. The conventional indirect method for generating parametric images typically starts by reconstructing a time series of frame images ...[more]
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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.
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Project description:Receptor ligand-based dynamic Positron Emission Tomography (PET) permits the measurement of neurotransmitter release in the human brain. For single-scan paradigms, the conventional method of estimating changes in neurotransmitter levels relies on fitting a pharmacokinetic model to activity concentration histories extracted after PET image reconstruction. However, due to the statistical fluctuations of activity concentration data at the voxel scale, parametric images computed using this approach often exhibit low signal-to-noise ratio, impeding characterization of neurotransmitter release. Numerous studies have shown that direct parametric reconstruction (DPR) approaches, which combine image reconstruction and kinetic analysis in a unified framework, can improve the signal-to-noise ratio of parametric mapping. However, there is little experience with DPR in imaging of neurotransmission and the performance of the approach in this application has not been evaluated before in humans. In this report, we present and evaluate a DPR methodology that computes 3-D distributions of ligand transport, binding potential (BPND) and neurotransmitter release magnitude (γ) from a dynamic sequence of PET sinograms. The technique employs the linear simplified reference region model (LSRRM) of Alpert et al. (2003), which represents an extension of the simplified reference region model that incorporates time-varying binding parameters due to radioligand displacement by release of neurotransmitter. Estimation of parametric images is performed by gradient-based optimization of a Poisson log-likelihood function incorporating LSRRM kinetics and accounting for the effects of head movement, attenuation, detector sensitivity, random and scattered coincidences. A 11C-raclopride simulation study showed that the proposed approach substantially reduces the bias and variance of voxel-wise γ estimates as compared to standard methods. Moreover, simulations showed that detection of release could be made more reliable and/or conducted using a smaller sample size using the proposed DPR estimator. Likewise, images of BPND computed using DPR had substantially improved bias and variance properties. Application of the method in human subjects was demonstrated using 11C-raclopride dynamic scans and a reward task, confirming the improved quality of the estimated parametric images using the proposed approach.
| S-EPMC7800040 | biostudies-literature
Project description:Our research goal is to develop an algorithm to reconstruct cardiac positron emission tomography (PET) kinetic parametric images directly from sinograms and compare its performance with the conventional indirect approach.Time activity curves of a NCAT phantom were computed according to a one-tissue compartmental kinetic model with realistic kinetic parameters. The sinograms at each time frame were simulated using the activity distribution for the time frame. The authors reconstructed the parametric images directly from the sinograms by optimizing a cost function, which included the Poisson log-likelihood and a spatial regularization terms, using the preconditioned conjugate gradient (PCG) algorithm with the proposed preconditioner. The proposed preconditioner is a diagonal matrix whose diagonal entries are the ratio of the parameter and the sensitivity of the radioactivity associated with parameter. The authors compared the reconstructed parametric images using the direct approach with those reconstructed using the conventional indirect approach.At the same bias, the direct approach yielded significant relative reduction in standard deviation by 12%-29% and 32%-70% for 50 × 10(6) and 10 × 10(6) detected coincidences counts, respectively. Also, the PCG method effectively reached a constant value after only 10 iterations (with numerical convergence achieved after 40-50 iterations), while more than 500 iterations were needed for CG.The authors have developed a novel approach based on the PCG algorithm to directly reconstruct cardiac PET parametric images from sinograms, and yield better estimation of kinetic parameters than the conventional indirect approach, i.e., curve fitting of reconstructed images. The PCG method increases the convergence rate of reconstruction significantly as compared to the conventional CG method.
| S-EPMC3779266 | biostudies-other
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.
| S-EPMC3555964 | biostudies-other
Project description:Respiratory motion during positron emission tomography (PET)/computed tomography (CT) imaging can cause significant image blurring and underestimation of tracer concentration for both static and dynamic studies. In this paper, with the aim to eliminate both intra-cycle and inter-cycle motions, and apply to dynamic imaging, we developed a non-rigid event-by-event (NR-EBE) respiratory motion-compensated list-mode reconstruction algorithm. The proposed method consists of two components: the first component estimates a continuous non-rigid motion field of the internal organs using the internal-external motion correlation. This continuous motion field is then incorporated into the second component, non-rigid MOLAR (NR-MOLAR) reconstruction algorithm to deform the system matrix to the reference location where the attenuation CT is acquired. The point spread function (PSF) and time-of-flight (TOF) kernels in NR-MOLAR are incorporated in the system matrix calculation, and therefore are also deformed according to motion. We first validated NR-MOLAR using a XCAT phantom with a simulated respiratory motion. NR-EBE motion-compensated image reconstruction using both the components was then validated on three human studies injected with 18F-FPDTBZ and one with 18F-fluorodeoxyglucose (FDG) tracers. The human results were compared with conventional non-rigid motion correction using discrete motion field (NR-discrete, one motion field per gate) and a previously proposed rigid EBE motion-compensated image reconstruction (R-EBE) that was designed to correct for rigid motion on a target lesion/organ. The XCAT results demonstrated that NR-MOLAR incorporating both PSF and TOF kernels effectively corrected for non-rigid motion. The 18F-FPDTBZ studies showed that NR-EBE out-performed NR-Discrete, and yielded comparable results with R-EBE on target organs while yielding superior image quality in other regions. The FDG study showed that NR-EBE clearly improved the visibility of multiple moving lesions in the liver where some of them could not be discerned in other reconstructions, in addition to improving quantification. These results show that NR-EBE motion-compensated image reconstruction appears to be a promising tool for lesion detection and quantification when imaging thoracic and abdominal regions using PET.
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Project description:Resolution degradation in PET image reconstruction can be caused by inaccurate modeling of the physical factors in the acquisition process. Resolution modeling (RM) is a common technique that takes into account the resolution degrading factors in the system matrix. Our previous work has introduced a probability density function (PDF) method of deriving the resolution kernels from Monte Carlo simulation and parameterizing the LORs to reduce the number of kernels needed for image reconstruction. In addition, LOR-PDF allows different PDFs to be applied to LORs from different crystal layer pairs of the HRRT. In this study, a thorough test was performed with this new model (LOR-PDF) applied to two PET scanners-the HRRT and Focus-220. A more uniform resolution distribution was observed in point source reconstructions by replacing the spatially-invariant kernels with the spatially-variant LOR-PDF. Specifically, from the center to the edge of radial field of view (FOV) of the HRRT, the measured in-plane FWHMs of point sources in a warm background varied slightly from 1.7?mm to 1.9?mm in LOR-PDF reconstructions. In Minihot and contrast phantom reconstructions, LOR-PDF resulted in up to 9% higher contrast at any given noise level than image-space resolution model. LOR-PDF also has the advantage in performing crystal-layer-dependent resolution modeling. The contrast improvement by using LOR-PDF was verified statistically by replicate reconstructions. In addition, [(11)C]AFM rats imaged on the HRRT and [(11)C]PHNO rats imaged on the Focus-220 were utilized to demonstrated the advantage of the new model. Higher contrast between high-uptake regions of only a few millimeter diameter and the background was observed in LOR-PDF reconstruction than in other methods.
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Project description:Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction.
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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.
| S-EPMC3247926 | biostudies-other
Project description:Images of the kidneys using dynamic contrast-enhanced magnetic resonance renography (DCE-MRR) contains unwanted complex organ motion due to respiration. This gives rise to motion artefacts that hinder the clinical assessment of kidney function. However, due to the rapid change in contrast agent within the DCE-MR image sequence, commonly used intensity-based image registration techniques are likely to fail. While semi-automated approaches involving human experts are a possible alternative, they pose significant drawbacks including inter-observer variability, and the bottleneck introduced through manual inspection of the multiplicity of images produced during a DCE-MRR study. To address this issue, we present a novel automated, registration-free movement correction approach based on windowed and reconstruction variants of dynamic mode decomposition (WR-DMD). Our proposed method is validated on ten different healthy volunteers' kidney DCE-MRI data sets. The results, using block-matching-block evaluation on the image sequence produced by WR-DMD, show the elimination of 99% of mean motion magnitude when compared to the original data sets, thereby demonstrating the viability of automatic movement correction using WR-DMD.
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Project description:In previous work, the authors developed and demonstrated the concept of an image reconstruction procedure aimed to unify gated and dynamic nuclear cardiac imaging, which the authors have termed five-dimensional (5D) SPECT. Gated imaging permits the clinician to evaluate wall motion and, through the use of stress and rest scans, allows perfusion defects to be observed. Dynamic imaging depicts kinetics in the myocardium, which can be used to evaluate perfusion, but traditional dynamic images are motionless and do not depict wall motion. In this article, the authors investigate the degree to which perfusion defects can be detected from the dynamic information conveyed by 5D images, a problem that is particularly challenging in the absence of multiple fast camera rotations.The authors first demonstrate the usefulness of dynamic reconstructed images for perfusion detection by using linear discriminant analyses (Fisher linear discriminant analysis and principal component analysis) and a numerical channelized Hotelling observer. The authors then derive three types of discriminant metrics for characterizing the temporal kinetic information in reconstructed dynamic images for differentiating perfusion defects from normal cardiac perfusion, which are the Fisher linear discriminant map, temporal derivative map, and kinetic parametric images.Results are based on the NURBS-based cardiac-torso phantom with simulation of Tc99m-teboroxime as the imaging agent. The derived metric maps and quantitative contrast-to-noise ratio results demonstrate that the reconstructed dynamic images could yield higher detectability of the perfusion defect than conventional gated reconstruction while providing wall motion information simultaneously.The proposed metrics can be used to produce new types of visualizations, showing wall motion and perfusion information, that may potentially be useful for clinical evaluation. Since 5D imaging permits wall motion and kinetics to be observed simultaneously, it may ultimately obviate the need for separate stress and rest scans.
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