Advanced quantitative evaluation of PET systems using the ACR phantom and NiftyPET software.

PURPOSE: A novel phantom-imaging platform, a set of software tools, for automated and high-precision imaging of the American College of Radiology (ACR) positron emission tomography (PET) phantom for PET/magnetic resonance (PET/MR) and PET/computed tomography (PET/CT) systems is proposed. METHODS: The key feature of this platform is the vector graphics design that facilitates the automated measurement of the knife-edge response function and hence image resolution, using composite volume of interest templates in a 0.5 mm resolution grid applied to all inserts of the phantom. Furthermore, the proposed platform enables the generation of an accurate µ $\mu$ -map for PET/MR systems with a robust alignment based on two-stage image registration using specifically designed PET templates. The proposed platform is based on the open-source NiftyPET software package used to generate multiple list-mode data bootstrap realizations and image reconstructions to determine the precision of the two-stage registration and any image-derived statistics. For all the analyses, iterative image reconstruction was employed with and without modeled shift-invariant point spread function and with varying iterations of the ordered subsets expectation maximization (OSEM) algorithm. The impact of the activity outside the field of view (FOV) was assessed using two acquisitions of 30 min each, with and without the activity outside the FOV. RESULTS: The utility of the platform has been demonstrated by providing a standard and an advanced phantom analysis including the estimation of spatial resolution using all cylindrical inserts. In the imaging planes close to the edge of the axial FOV, we observed deterioration in the quantitative accuracy, reduced resolution (FWHM increased by 1-2 mm), reduced contrast, and background uniformity due to the activity outside the FOV. Although it slows convergence, the PSF reconstruction had a positive impact on resolution and contrast recovery, but the degree of improvement depended on the regions. The uncertainty analysis based on bootstrap resampling of raw PET data indicated high precision of the two-stage registration. CONCLUSIONS: We demonstrated that phantom imaging using the proposed methodology with the metric of spatial resolution and multiple bootstrap realizations may be helpful in more accurate evaluation of PET systems as well as in facilitating fine tuning for optimal imaging parameters in PET/MR and PET/CT clinical research studies.

Rapid processing of PET list-mode data for efficient uncertainty estimation and data analysis.

In this technical note we propose a rapid and scalable software solution for the processing of PET list-mode data, which allows the efficient integration of list mode data processing into the workflow of image reconstruction and analysis. All processing is performed on the graphics processing unit (GPU), making use of streamed and concurrent kernel execution together with data transfers between disk and CPU memory as well as CPU and GPU memory. This approach leads to fast generation of multiple bootstrap realisations, and when combined with fast image reconstruction and analysis, it enables assessment of uncertainties of any image statistic and of any component of the image generation process (e.g. random correction, image processing) within reasonable time frames (e.g. within five minutes per realisation). This is of particular value when handling complex chains of image generation and processing. The software outputs the following: (1) estimate of expected random event data for noise reduction; (2) dynamic prompt and random sinograms of span-1 and span-11 and (3) variance estimates based on multiple bootstrap realisations of (1) and (2) assuming reasonable count levels for acceptable accuracy. In addition, the software produces statistics and visualisations for immediate quality control and crude motion detection, such as: (1) count rate curves; (2) centre of mass plots of the radiodistribution for motion detection; (3) video of dynamic projection views for fast visual list-mode skimming and inspection; (4) full normalisation factor sinograms. To demonstrate the software, we present an example of the above processing for fast uncertainty estimation of regional SUVR (standard uptake value ratio) calculation for a single PET scan of (18)F-florbetapir using the Siemens Biograph mMR scanner.

Model-based correction for scatter and tailing effects in simultaneous 99mTc and 123I imaging for a CdZnTe cardiac SPECT camera.

An advantage of semiconductor-based dedicated cardiac single photon emission computed tomography (SPECT) cameras when compared to conventional Anger cameras is superior energy resolution. This provides the potential for improved separation of the photopeaks in dual radionuclide imaging, such as combined use of (99m)Tc and (123)I . There is, however, the added complexity of tailing effects in the detectors that must be accounted for. In this paper we present a model-based correction algorithm which extracts the useful primary counts of (99m)Tc and (123)I from projection data. Equations describing the in-patient scatter and tailing effects in the detectors are iteratively solved for both radionuclides simultaneously using a maximum a posteriori probability algorithm with one-step-late evaluation. Energy window-dependent parameters for the equations describing in-patient scatter are estimated using Monte Carlo simulations. Parameters for the equations describing tailing effects are estimated using virtually scatter-free experimental measurements on a dedicated cardiac SPECT camera with CdZnTe-detectors. When applied to a phantom study with both (99m)Tc and (123)I, results show that the estimated spatial distribution of events from (99m)Tc in the (99m)Tc photopeak energy window is very similar to that measured in a single (99m)Tc phantom study. The extracted images of primary events display increased cold lesion contrasts for both (99m)Tc and (123)I.

Developments in cardiac-specific SPECT imaging.

In recent years there has been a trend towards designing single photon emission computed tomography (SPECT) systems specifically for application in cardiac imaging. There is now a wide range of systems designs ranging from compact dual detector system suited for either upright or supine patient positioning, specialized collimators or custom designed systems, some taking advantage of the compact design made possible with use of solid-state detectors. This paper provides an overview of these systems with discussion on merits and limitations.

Design of a novel slit-slat collimator system for SPECT imaging of the human brain.

We present three novel multi-slit-slat (MSS) system designs which allow for the acquisition of data with variable multiplexing in order to optimize the use of a high intrinsic resolution detector for clinical brain SPECT. In this paper we first study the relationship between the geometric parameters of a MSS collimator system and the resulting resolution and sensitivity for an on-axis point at the centre of the field-of-view (FOV), assuming a continuous cylindrical detector model. The model predicts that for optimal system sensitivity and resolution, the ratio of the detector radius to slit collimator radius should be 1.3-1.5, as any further increase in this ratio results in significant deterioration in both system resolution and sensitivity. The analytical results were used to fix the geometric parameters for the three novel MSS system designs. Comparison of the three designs, asymmetric rotating collimator (ARC), asymmetric rotating detector (ARD) and symmetric rotating collimator (SRC) with variable slit spacing, suggests that the SRC system performs better in terms of the system sensitivity (5.1 x 10(-4)) for the same average resolution (6.0 mm) in comparison to designs based on an ARC (3.7 x 10(-4)) and ARD (4.2 x 10(-4)).

Evaluation of a low-dose/slow-rotating SPECT-CT system.

The 4-slice CT that forms part of the GE Infinia Hawkeye-4 SPECT-CT scanner (Hawkeye) is evaluated against the diagnostic 16-slice CT that is incorporated in the GE Discovery ST PET-CT system (DST). The x-ray tube of the slow-rotating Hawkeye system (23 s/rotation) operates at approximately a third of the dose of diagnostic systems as used for conventional diagnostic imaging. Image reconstruction is optimized for low noise. High-contrast spatial resolution significantly falls behind diagnostic figures: the average of MTF(50) and MTF(10) (resolution where the MTF has fallen to 50% and 10%) is 2.8 +/- 0.1 cm(-1) for Hawkeye and 5.3 +/- 0.1 cm(-1) for the DST (standard reconstruction filters). Resolution in the direction of the couch movement (z coordinate) is governed by the fixed Hawkeye slice width of 5 mm. Reconstruction accuracy is found to be increased by reducing the default z increment from 4.4 mm to 2.2 mm. Low-contrast object detectability is superior compared with diagnostic systems operating in the Hawkeye dose range. In the diagnostic dose regime, however, small low-contrast details remain visible in DST that are not detectable with Hawkeye. Although not of diagnostic quality, the low-dose Hawkeye provides appropriate data for SPECT attenuation correction and anatomical localization capability.

Improved tolerance to missing data in myocardial perfusion SPET using OSEM reconstruction.

When projection data are incomplete for various technical reasons, artefacts may occur in the reconstructed images. This study examines whether an iterative reconstruction method, the ordered subsets implementation of the EM algorithm (OSEM), can improve reconstruction and minimise the artefacts compared to filtered back-projection (FBP). We varied the number and location of projections removed to investigate when significant artefacts occur, and whether diagnosis is affected. Phantom studies were analysed with sequential orthogonal pairs of projection angles removed (as would typically occur when either data loss or severe motion is detected during acquisition with a right-angled, dual-head cardiac single-photon emission tomography system) and reconstructed with both FBP and OSEM. Twelve normal myocardial perfusion studies were also assessed to study the effect of missing projections on clinical diagnosis. Differences between reconstructions with intact versus missing data were measured. Also, reconstructed images were clinically assessed and scored on a five-point scale based on whether the artefacts would alter clinical interpretation. Although both reconstruction methods showed artefacts, the absolute differences between reconstructed phantom data with intact and missing projection sets were significantly greater (P<0.005) for FBP than for OSEM for all numbers of missing projections. The clinical data showed similar differences between FBP and OSEM reconstructions. The three observers noted superiority of OSEM compared to FBP, with reduced incidence of clinically significant artefacts. However, neither reconstruction method could tolerate six or more missing pairs from 32 projections. There was no significant dependence on the angular location of missing projections. In the absence of any attempt to correct for missing projections, OSEM reduced the influence of artefacts compared to FBP.

Non-rigid image registration using a median-filtered coarse-to-fine displacement field and a symmetric correlation ratio.

Conventional approaches to image registration are generally limited to image-wide rigid transformations. However, the body and its internal organs are non-rigid structures that change shape due to changes in the body's posture during image acquisition, and due to normal, pathological and treatment-related variations. Inter-subject matching also constitutes a non-rigid registration problem. In this paper, we present a fully automated non-rigid image registration method that maximizes a local voxel-based similarity metric. Overlapping image blocks are defined on a 3D grid. The transformation vector field representing image deformation is found by translating each block so as to maximize the local similarity measure. The resulting sparsely sampled vector field is median filtered and interpolated by a Gaussian function to ensure a locally smooth transformation. A hierarchical strategy is adopted to progressively establish local registration associated with image structures at diminishing scale. Simulation studies were carried out to evaluate the proposed algorithm and to determine the robustness of various voxel-based cost functions. Mutual information, normalized mutual information, correlation ratio (CR) and a new symmetric version of CR were evaluated and compared. A T1-weighted magnetic resonance (MR) image was used to test intra-modality registration. Proton density and T2-weighted MR images of the same subject were used to evaluate inter-modality registration. The proposed algorithm was tested on the 2D MR images distorted by known deformations and 3D images simulating inter-subject distortions. We studied the robustness of cost functions with respect to image sampling. Results indicate that the symmetric CR gives comparable registration to mutual information in intra- and inter-modality tasks at full sampling and is superior to mutual information in registering sparsely sampled images.

Choice of collimator for cardiac SPET when resolution compensation is included in iterative reconstruction.

In clinical cardiac single-photon emission tomography (SPET) studies, collimators of different spatial resolution and geometric efficiency are available for imaging. In selecting the appropriate collimator for clinical use, there is a trade-off between spatial resolution, which can limit the contrast of the reconstructed image, and detection efficiency, which determines the noise in the image. Our objective was to assess which collimator is best suited for cardiac SPET when reconstruction is performed with and without compensation for distance-dependent resolution (CDR). The dynamic MCAT thorax phantom was used to simulate 180 degree technetium-99m cardiac data, acquired using either a general-purpose (GP) or high-resolution (HR) collimator. For GP and HR, the resolution at 15 cm was 11.5 mm and 9.5 mm respectively, and the corresponding relative efficiency was 1.0 and 0.52 respectively. Distance-dependent resolution, attenuation and noise were included in the projection data; scatter was not included. Ordered subsets expectation maximisation reconstruction (subset size 4) was performed with and without CDR. Results were evaluated by comparing the myocardial recovery coefficient and contrast between myocardium and ventricle relative to the original phantom, each plotted for different noise levels corresponding to increasing iteration number. The study demonstrated that, without CDR, HR gave the best results. However, for any given noise level with CDR, GP gave superior recovery and contrast. These findings were confirmed in a physical phantom study. Results suggest that improved reconstruction can be achieved using a GP collimator in combination with resolution compensation.

Improved efficiency for MRI-SPET registration based on mutual information.

Mutual information has been proposed as a criterion for image registration. The criterion is calculated from a two-dimensional grey-scale histogram of the image pair being registered. In this paper we study how sparse sampling can be used to increase speed performance using the registration algorithm of Maes et al. (IEEE Trans Med Imaging 1997; 16: 187-198) with a focus on registration of MRI-SPET brain images. In particular we investigate how sparse sampling and parameters such as the number of bins used for the grey-scale histograms and smoothing of the data prior to registration affect accuracy and robustness of the registration. The method was validated using both simulated and human data. Our results show that sparse sampling introduced local maxima into the mutual information similarity function when the number of bins used for the histograms was large. To speed up registration while retaining robustness, smoothing of the data prior to registration was used and a coarse to fine subsampling protocol, where the number of bins in the histograms were dependent on the subsampling factor, was employed, For the simulated data, the method was able to recover known transformations with an accuracy of about 1 mm. Using the human data, there were no significant differences in the recovered transformation parameters when the suggested subsampling scheme was used compared with when no subsampling was used, but there was a more than tenfold increase in speed. Our results show that, with the appropriate choice of parameters, the method can accurately register MRI-SPET brain images even when very efficient sampling protocols are used.

A distance-assisted training program for nuclear medicine technologists.

We have developed training materials for nuclear medicine technologists to be used in distance-assisted training programs. We have completed our first pilot project in Asia and report that there will be nearly 500 students around the world, in Asia, Africa, Central America and South America, using our materials during the coming year.

Efficient scatter modelling for incorporation in maximum likelihood reconstruction.

Definition of a simplified model of scatter which can be incorporated in maximum likelihood reconstruction for single-photon emission tomography (SPET) continues to be appealing; however, implementation must be efficient for it to be clinically applicable. In this paper an efficient algorithm for scatter estimation is described in which the spatial scatter distribution is implemented as a spatially invariant convolution for points of constant depth in tissue. The scatter estimate is weighted by a space-dependent build-up factor based on the measured attenuation in tissue. Monte Carlo simulation of a realistic thorax phantom was used to validate this approach. Further efficiency was introduced by estimating scatter once after a small number of iterations using the ordered subsets expectation maximisation (OSEM) reconstruction algorithm. The scatter estimate was incorporated as a constant term in subsequent iterations rather than modifying the scatter estimate each iteration. Monte Carlo simulation was used to demonstrate that the scatter estimate does not change significantly provided at least two iterations OSEM reconstruction, subset size 8, is used. Complete scatter-corrected reconstruction of 64 projections of 40¿128 pixels was achieved in 38 min using a Sun Sparc20 computer.

Half-fanbeam collimators combined with scanning point sources for simultaneous emission-transmission imaging.

UNLABELLED: One type of SPECT system often used for simultaneous emission-transmission tomography is equipped with parallel-hole collimators, moving line sources (MLS) and electronic windows that move in synchrony with the sources. Although downscatter from the emission distribution is reduced by the use of the electronic window, this still can represent a sizable fraction of the transmitted counts. These systems have relatively poor spatial resolution and use costly transmission sources. METHODS: Using a two-head SPECT system, with heads at right angles, two 153Gd line sources (5800 MBq each) were replaced by two 153Gd point sources of only 750 MBq each and positioned to move along the focal lines of two half-fanbeam collimators. A suitable acquisition protocol for a moving point source (MPS) system was selected by considering the results of a simulation study. With this protocol, physical phantom experiments were conducted. RESULTS: Simulations showed that by using two half-fanbeam collimators, a gantry rotation of 90 degrees, such as used for 180 degrees acquisition with parallel-beam collimators for cardiac imaging, was insufficient. A gantry rotation of 180 degrees resulted in attenuation maps where only an area to the posterior of a 400-mm wide thorax phantom was affected by truncation. The MPS system had a 14.7 times higher sensitivity for transmission counts than the MLS system. Despite the smaller sources in the MPS system, the number of acquired transmission counts was a factor 1.91 times higher compared with the MLS system, resulting in reduced noise. The relative downscatter contribution from 99mTc (140 keV) in the 153Gd moving electronic window (100 keV) was reduced by a factor of 1.81. Transmission images of a rod phantom with segments containing acrylic rods of different diameters showed an improvement of resolution in favor of the MPS system from about 11 mm to about 6 mm (five instead of two segments of rods were clearly visible). In addition, the noise level in the MPS thorax transmission images was significantly lower. CONCLUSION: The MPS system has important advantages when compared with the MLS system. The use of low-activity point sources is economically beneficial when compared with line sources and reduces radiation exposure to staff and patients.

Correction of partial volume effects in myocardial SPECT.

BACKGROUND: Marked partial volume effects occur in myocardial single photon emission computed tomographic (SPECT) studies because of limited resolution in imaging the myocardial wall and contractile motion of the heart. Little work has been undertaken to develop correction techniques for SPECT except for efforts to improve the reconstructed resolution. Our purpose was to examine the extent of the problem and propose a correction method. METHODS AND RESULTS: A potential correction method, developed initially for positron emission tomography, involved estimation of extravascular density by means of subtracting vascular density derived in a blood pool study from total density derived from a transmission study. Provided partial volume errors are the same for transmission and emission data, activity per gram of extravascular tissue can be obtained by means of dividing the perfusion regional data by extravascular density for the same region. Simulations were designed to assess the importance of partial volume errors and the use of extravascular density to correct the errors. Recovery coefficients for the myocardium were estimated by means of simulation of the beating heart on the basis of published values for ventricular dimensions. Resolution for transmission with a scanning line source system was compared with emission resolution. The effect of spillover on measured partial volume losses was assessed, and a method for matching spillover for emission and extravascular density was demonstrated. Correction for partial volume effects was demonstrated for a phantom with variable wall thickness. Significant variation in recovery coefficient was demonstrated between posterior and septal walls for individual patients independent of heart size. Filtering was necessary to account for the difference in transmission resolution measured in the axial direction. Spillover effects had a significant influence on the measured recovery for small objects; however, for a specific reconstruction algorithm and defined region size, correction was implemented to match the spillover effects for emission and extravascular density. Use of extravascular density for correction of partial volume loss, for ordered subsets expectation maximization reconstruction with compensation for resolution, was demonstrated to be accurate to within 10%. CONCLUSIONS: The feasibility of correcting partial volume effects with extravascular density was demonstrated. Correction is effective provided care is taken to match both resolution and spillover for emission and extravascular density.

Application of distance-dependent resolution compensation and post-reconstruction filtering for myocardial SPECT.

Compensation for distance-dependent resolution can be directly incorporated in maximum likelihood reconstruction. Our objective was to examine the effectiveness of this compensation using either the standard expectation maximization (EM) algorithm or an accelerated algorithm based on use of ordered subsets (OSEM). We also investigated the application of post-reconstruction filtering in combination with resolution compensation. Using the MCAT phantom, projections were simulated for 360 degrees data, including attenuation and distance-dependent resolution. Projection data were reconstructed using conventional EM and OSEM with subset size 2 and 4, with/without 3D compensation for detector response (CDR). Also post-reconstruction filtering (PRF) was performed using a 3D Butterworth filter of order 5 with various cutoff frequencies (0.2-1.2 cycles cm(-1)). Image quality and reconstruction accuracy were improved when CDR was included. Image noise was lower with CDR for a given iteration number. PRF with cutoff frequency greater than 0.6 cycles cm(-1) improved noise with no reduction in recovery coefficient for myocardium but the effect was less when CDR was incorporated in the reconstruction. CDR alone provided better results than use of PRF without CDR. Results suggest that using CDR without PRF, and stopping at a small number of iterations, may provide sufficiently good results for myocardial SPECT. Similar behaviour was demonstrated for OSEM.

Dynamic imaging and tracer kinetic modeling for emission tomography using rotating detectors.

When performing dynamic studies using emission tomography the tracer distribution changes during acquisition of a single set of projections. This is particularly true for some positron emission tomography (PET) systems which, like single photon emission computed tomography (SPECT), acquire data over a limited angle at any time, with full projections obtained by rotation of the detectors. In this paper, an approach is proposed for processing data from these systems, applicable to either PET or SPECT. A method of interpolation, based on overlapped parabolas, is used to obtain an estimate of the total counts in each pixel of the projections for each required frame-interval, which is the total time to acquire a single complete set of projections necessary for reconstruction. The resultant projections are reconstructed using traditional filtered backprojection (FBP) and tracer kinetic parameters are estimated using a method which relies on counts integrated over the frame-interval rather than instantaneous values. Simulated data were used to illustrate the technique's capabilities with noise levels typical of those encountered in either PET or SPECT. Dynamic datasets were constructed, based on kinetic parameters for fluoro-deoxy-glucose (FDG) and use of either a full ring detector or rotating detector acquisition. For the rotating detector, use of the interpolation scheme provided reconstructed dynamic images with reduced artefacts compared to unprocessed data or use of linear interpolation. Estimates for the metabolic rate of glucose had similar bias to those obtained from a full ring detector.

A clinical perspective of accelerated statistical reconstruction.

Although the potential benefits of maximum likelihood reconstruction have been recognised for many years, the technique has only recently found widespread popularity in clinical practice. Factors which have contributed to the wider acceptance include improved models for the emission process, better understanding of the properties of the algorithm and, not least, the practicality of application with the development of acceleration schemes and the improved speed of computers. The objective in this article is to present a framework for applying maximum likelihood reconstruction for a wide range of clinically based problems. The article draws particularly on the experience of the three authors in applying an acceleration scheme involving use of ordered subsets to a range of applications. The potential advantages of statistical reconstruction techniques include: (a) the ability to better model the emission and detection process, in order to make the reconstruction converge to a quantitative image, (b) the inclusion of a statistical noise model which results in better noise characteristics, and (c) the possibility to incorporate prior knowledge about the distribution being imaged. The great flexibility in adapting the reconstruction for a specific model results in these techniques having wide applicability to problems in clinical nuclear medicine.

Monte Carlo and experimental evaluation of accuracy and noise properties of two scatter correction methods for SPECT.

Scatter correction is a prerequisite for quantitative SPECT, but potentially increases noise. Monte Carlo simulations (EGS4) and physical phantom measurements were used to compare accuracy and noise properties of two scatter correction techniques: the triple-energy window (TEW), and the transmission dependent convolution subtraction (TDCS) techniques. Two scatter functions were investigated for TDCS: (i) the originally proposed mono-exponential function (TDCSmono) and (ii) an exponential plus Gaussian scatter function (TDCSGauss) demonstrated to be superior from our Monte Carlo simulations. Signal to noise ratio (S/N) and accuracy were investigated in cylindrical phantoms and a chest phantom. Results from each method were compared to the true primary counts (simulations), or known activity concentrations (phantom studies). 99mTc was used in all cases. The optimized TDCS(Gauss) method overall performed best, with an accuracy of better than 4% for all simulations and physical phantom studies. Maximum errors for TEW and TDCS(mono) of -30 and -22%, respectively, were observed in the heart chamber of the simulated chest phantom. TEW had the worst S/N ratio of the three techniques. The S/N ratios of the two TDCS methods were similar and only slightly lower than those of simulated true primary data. Thus, accurate quantitation can be obtained with TDCS(Gauss), with a relatively small reduction in S/N ratio.

Minimum cross-entropy reconstruction of PET images using prior anatomical information.

An algorithm is presented for the reconstruction of PET images using prior anatomical information derived from MR images of the same subject. The cross-entropy or Kullback-Leiber distance is a measure of dissimilarity between two images. We propose to reconstruct PET images by minimizing a weighted sum of two cross-entropy terms. The first is the cross-entropy between the measured emission data and the forward projection of the current estimate of the PET image. Minimizing this term alone is equivalent to the ML-EM reconstruction. The second term is the cross-entropy between the current estimate of the PET image and a prior image model which incorporates anatomical information derived from registered MR images. A weighting parameter determines the relative emphasis given to the emission data and the prior model in the reconstruction. Details of this algorithm are presented as well as test reconstructions for real and simulated data. The performance of the algorithm was evaluated with respect to errors in prior anatomical information. The algorithm provided significant improvement in the quality of reconstructed images as compared with the ML-EM reconstruction technique. The reconstructed images had higher resolution as compared with the images obtained from MAP-like reconstructions which do not utilize anatomical information. The algorithm displayed robustness with respect to errors in prior anatomical information.