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Showing papers on "Parametric Image published in 2012"


Journal ArticleDOI
TL;DR: A new optimization transfer algorithm for penalized likelihood direct reconstruction of nonlinear parametric images that is easy to use and has a fast convergence rate that has been applied to real 4-D PET data.
Abstract: Direct reconstruction of kinetic parameters from raw projection data is a challenging task in molecular imaging using dynamic positron emission tomography (PET). This paper presents a new optimization transfer algorithm for penalized likelihood direct reconstruction of nonlinear parametric images that is easy to use and has a fast convergence rate. Each iteration of the proposed algorithm can be implemented in three simple steps: a frame-by-frame maximum likelihood expectation-maximization (EM)-like image update, a frame-by-frame image smoothing, and a pixel-by-pixel time activity curve fitting. Computer simulation shows that the direct algorithm can achieve a better bias-variance performance than the indirect reconstruction algorithm. The convergence rate of the new algorithm is substantially faster than our previous algorithm that is based on a separable paraboloidal surrogate function. The proposed algorithm has been applied to real 4-D PET data.

71 citations


Journal ArticleDOI
TL;DR: Comparisons showed that the proposed direct method can lead to accurate estimation of the parametric image values with reduced variance, especially at low count levels, which is similar with PMOLAR-1T showing lower noise than FM.
Abstract: The production of images of kinetic parameters is often the ultimate goal of positron emission tomography (PET) imaging. The indirect method of PET parametric imaging, also called the frame-based method (FM), is performed by fitting the time-activity curve (TAC) for each voxel with an appropriate compartment model after image reconstruction. The indirect method is simple and easily implemented, however, it usually leads to some loss of accuracy or precision, due to the use of two separate steps. This paper presents a direct 4-D method for producing 3-D images of kinetic parameters from list mode PET data. In this application, the TAC for each voxel is described by a one-tissue compartment model (1T). Extending previous EM algorithms, a new spatiotemporal complete data space was introduced to optimize the maximum likelihood function. This leads to a straightforward closed-form parametric image update equation. This method was implemented by extending the current list mode platform MOLAR to produce a parametric algorithm PMOLAR-1T. Using an ordered subset approach, qualitative and quantitative evaluations were performed using 2-D (x, t) and 4-D (x, y, z, t) simulated list mode data based on brain receptor tracers and also with a human brain study. Comparisons with the indirect method showed that the proposed direct method can lead to accurate estimation of the parametric image values with reduced variance, especially at low count levels. In the 2-D test, the direct method showed similar bias to the frame-based method but with variance reduction of 23%-60%. In the 4-D test, bias values of both methods were no more than 4% and the direct method had lower variability (coefficient of variation reduction of 0%-64% compared to the frame-based method) at the normal count level. The direct method had a larger reduction in variability (27%-81%) and lower bias (1%-5% for 4-D and 1%-19% for FM) at low count levels. The results in the human brain study are similar with PMOLAR-1T showing lower noise than FM.

43 citations


Journal ArticleDOI
TL;DR: Direct 4D EM reconstruction resulted in notable qualitative and quantitative accuracy improvements and improvements were also observed in the coefficient of variation of the estimated DV and DVR values even for relatively low uptake cortical regions, suggesting the enhanced ability for robust parameter estimation.
Abstract: Due to high noise levels in the voxel kinetics, development of reliable parametric imaging algorithms remains one of most active areas in dynamic brain PET imaging, which in the vast majority of cases involves receptor/transporter studies with reversibly binding tracers. As such, the focus of this work has been to develop a novel direct 4D parametric image reconstruction scheme for such tracers. Based on a relative equilibrium (RE) graphical analysis formulation (Zhou et al 2009b Neuroimage 44 661-70), we developed a closed-form 4D EM algorithm to directly reconstruct distribution volume (DV) parametric images within a plasma input model, as well as DV ratio (DVR) images within a reference tissue model scheme (wherein an initial reconstruction was used to estimate the reference tissue time-activity curves). A particular challenge with the direct 4D EM formulation is that the intercept parameters in graphical (linearized) analysis of reversible tracers (e.g. Logan or RE analysis) are commonly negative (unlike for irreversible tracers, e.g. using Patlak analysis). Subsequently, we focused our attention on the AB-EM algorithm, derived by Byrne (1998, Inverse Problems 14 1455-67) to allow inclusion of prior information about the lower (A) and upper (B) bounds for image values. We then generalized this algorithm to the 4D EM framework, thus allowing negative intercept parameters. Furthermore, our 4D AB-EM algorithm incorporated and emphasized the use of spatially varying lower bounds to achieve enhanced performance. As validation, the means of parameters estimated from 55 human (11)C-raclopride dynamic PET studies were used for extensive simulations using a mathematical brain phantom. Images were reconstructed using conventional indirect as well as proposed direct parametric imaging methods. Noise versus bias quantitative measurements were performed in various regions of the brain. Direct 4D EM reconstruction resulted in notable qualitative and quantitative accuracy improvements (over 35% noise reduction, with matched bias, in both plasma and reference-tissue input models). Similar improvements were also observed in the coefficient of variation of the estimated DV and DVR values even for relatively low uptake cortical regions, suggesting the enhanced ability for robust parameter estimation. The method was also tested on a 90 min (11)C-raclopride patient study performed on the high-resolution research tomograph wherein the proposed method was shown across a variety of regions to outperform the conventional method in the sense that for a given DVR value, improved noise levels were observed.

40 citations


Journal ArticleDOI
TL;DR: An implementation of the algorithm that can be tailored to specific PET imaging tasks to minimize bias and maximize improvement in variance is developed, and a framework for validating the use of HYPR-LR processing for a particular imaging task is provided.
Abstract: Purpose: Highly constrained backprojection-local reconstruction (HYPR-LR) has made a dramatic impact on magnetic resonance angiography (MRA) and shows promise for positron emission tomography (PET) because of the improvements in the signal-to-noise ratio (SNR) it provides dynamic images. For PET in particular, HYPR-LR could improve kinetic analysis methods that are sensitive to noise. In this work, the authors closely examine the performance of HYPR-LR in the context of kinetic analysis, they develop an implementation of the algorithm that can be tailored to specific PET imaging tasks to minimize bias and maximize improvement in variance, and they provide a framework for validating the use of HYPR-LR processing for a particular imaging task. Methods: HYPR-LR can introduce errors into non sparse PET studies that might bias kinetic parameter estimates. An implementation of HYPR-LR is proposed that uses multiple temporally summed composite images that are formed based on the kinetics of the tracer being studied (HYPR-LR-MC). The effects of HYPR-LR-MC and of HYPR-LR using a full composite formed with all the frames in the study (HYPR-LR-FC) on the kinetic analysis of Pittsburgh compound-B ([11C]-PIB) are studied. HYPR-LR processing is compared to spatial smoothing. HYPR-LR processing was evaluated using both simulated and human studies. Nondisplaceable binding potential (BPND) parametric images were generated from fifty noise realizations of the same numerical phantom and eight [11C]-PIB positive human scans before and after HYPR-LR processing or smoothing using the reference region Logan graphical method and receptor parametric mapping (RPM2). The bias and coefficient of variation in the frontal and parietal cortex in the simulated parametric images were calculated to evaluate the absolute performance of HYPR-LR processing. Bias in the human data was evaluated by comparing parametric image BPND values averaged over large regions of interest (ROIs) to Logan estimates of the BPND from TACs averaged over the same ROIs. Variance was assessed qualitatively in the parametric images and semiquantitatively by studying the correlation between voxel BPND estimates from Logan analysis and RPM2. Results: Both the simulated and human data show that HYPR-LR-FC overestimates BPND values in regions of high [11C]-PIB uptake. HYPR-LR-MC virtually eliminates this bias. Both implementations of HYPR-LR reduce variance in the parametric images generated with both Logan analysis and RPM2, and HYPR-LR-FC provides a greater reduction in variance. This reduction in variance nearly eliminates the noise-dependent Logan bias. The variance reduction is greater for the Logan method, particularly for HYPR-LR-MC, and the variance in the resulting Logan images is comparable to that in the RPM2 images. HYPR-LR processing compares favorably with spatial smoothing, particularly when the data are analyzed with the Logan method, as it provides a reduction in variance with no loss of spatial resolution. Conclusions: HYPR-LR processing shows significant potential for reducing variance in parametric images, and can eliminate the noise-dependent Logan bias. HYPR-LR-FC processing provides the greatest reduction in variance but introduces a positive bias into the BPND of high-uptake border regions. The proposed method for forming HYPR composite images, HYPR-LR-MC, eliminates this bias at the cost of less variance reduction.

35 citations


Patent
Chi-Yin Lee1, Liexiang Fan1, Caroline Maleke1, Kevin Michael Sekins1, Patrick Gross1 
30 Mar 2012
TL;DR: In this paper, a curve representing the values of the parameter over time is fit to the available MRI and ultrasound data of each location, resulting in fused data at times for which MRI data is not available.
Abstract: Magnetic resonance and ultrasound parametric image is fused or combined. MRI and ultrasound imaging are used to acquire the same type of parametric images. Fused data is created by combining ultrasound and MRI parametric data at times for which both types of data are available. Rather than sacrificing rate, fused data is created for times for which MRI data is not acquired. A curve representing the values of the parameter over time is fit to the available MRI and ultrasound data of each location, resulting in fused data at times for which MRI data is not available.

14 citations


Journal ArticleDOI
TL;DR: Bayesian estimation can improve the SNR of parametric images and better detect localized changes in cohorts of subjects.

9 citations


Proceedings ArticleDOI
01 Oct 2012
TL;DR: This study facilitates the integration of whole body parametric imaging into the clinic as a competitive alternative to SUV, and shows enhanced CNR when ridge regression is applied only to voxels associated with high WR, while ordinary least squares and WR driven post-smoothing is performed to the rest.
Abstract: Whole body PET/CT, a well established imaging method in nuclear medicine for the clinical evaluation of a wide variety of metastatic cancer malignancies, commonly involves static scanning over multiple beds. Recently, we proposed a clinically feasible transition of whole-body PET/CT imaging to the dynamic domain, by acquiring (i) an initial 6min dynamic scan over the heart, followed by (ii) an optimized sequence of whole-body PET scans, allowing for quantitative whole body parametric imaging. Comparative evaluation of parametric and SUV images indicated enhanced contrast-to-noise ratio (CNR) but also higher noise for the parametric images. The objective of this study is to further improve parametric image CNR to enhance tumor detectability, by limiting noise in the estimates, while enhancing contrast and quantitative accuracy of parametric images. For this purpose, we utilize the weighted correlation coefficient (WR) of the kinetic model (Patlak) fits at each voxel to determine the cluster of voxels, where (i) advanced, as opposed to conventional, statistical parameter estimation, (ii) spatial smoothing or (iii) thresholding is applied. Thus, we facilitate the integration of whole body parametric imaging into the clinic as a competitive alternative to SUV. Through quantitative analysis on selected tumor regions of the resulting images, we show enhanced CNR when ridge regression is applied only to voxels associated with high WR, while ordinary least squares (OLS) and WR driven post-smoothing is performed to the rest. This hybrid regression method yields reduced mean squared error in tumor regions, compared to OLS. In addition, by setting the WR threshold level in the range [0.85 0.9], CNR is further enhanced for tumor regions of high WR. Finally, for the same type of tumors, hybrid regression also achieves higher CNR, compared to SUV, when the last two dynamic frames are omitted, allowing for shorter acquisition times.

5 citations


Patent
03 Oct 2012
TL;DR: In this article, a method and system for displaying an ultrasonic parametric image showing tissue perfusion in registration with an anatomical ultrasonic image of the tissue containing the blood flow is described.
Abstract: A method and system are described for displaying an ultrasonic parametric image showing tissue perfusion in registration with an anatomical ultrasonic image of the tissue containing the blood flow The relative opacities of the parametric image and the anatomical image can be varied, enabling the clinician to view both the perfusion parameters and the blood flow simultaneously or in rapid succession In an illustrated embodiment the anatomical image or the parametric image can be viewed alone, or in anatomical registration with different or equal opacities The relative opacity can be changedin a smoothly continuous or stepwise manner

4 citations