Ordered Subset Expectation Maximization Reconstruction Research Articles

Reduced-count myocardial perfusion SPECT with resolution recovery

The aim of this study was to determine whether resolution recovery (RR) iterative reconstruction algorithms can consistently produce diagnostic quality myocardial perfusion SPECT images for the patient population routinely scanned in this department. Reduced-count data were compared with full-count data without RR according to our established protocol. The desired outcome would be to implement the software to allow a reduction in the administered activity for routine myocardial SPECT. Half-count SPECT data were derived from full-count datasets for 53 stress and rest routine myocardial SPECT scans on a GE Infinia camera. Full-count data were reconstructed using standard non-RR ordered subset expectation maximization reconstruction, whereas half-count data were reconstructed using Evolution RR software. Myocardial functional values, image quality and report outcomes of the full-count and half-count reports were compared. Sequential full-time and half-time myocardial SPECT acquisitions were performed for 15 stress and rest studies on a Siemens c.cam dedicated cardiac camera. Half-count data were reconstructed using Siemens Flash 3D RR. No degradation in image quality was found when comparing full-count and half-count studies from the Infinia. Ten percent of the half-count studies from the c.cam were considered slightly worse than full-count data. Statistically significant differences in some full-count versus half-count functional values were found but the actual mean differences were not considered clinically significant. No difference was found for 44 out of 53 full-count versus half-count reports, a minor difference for seven out of 53 and a significant difference in two cases. RR was found to produce diagnostic image quality for nearly all scans, but it was felt that a reduction of 50% from our standard protocol was too great. A proposed reduction of 33% administered activity was considered acceptable to produce consistently adequate diagnostic images for both manufacturers.

Fully 3D iterative scatter-corrected OSEM for HRRT PET using a GPU

Accurate scatter correction is especially important for high-resolution 3D positron emission tomographies (PETs) such as high-resolution research tomograph (HRRT) due to large scatter fraction in the data. To address this problem, a fully 3D iterative scatter-corrected ordered subset expectation maximization (OSEM) in which a 3D single scatter simulation (SSS) is alternatively performed with a 3D OSEM reconstruction was recently proposed. However, due to the computational complexity of both SSS and OSEM algorithms for a high-resolution 3D PET, it has not been widely used in practice. The main objective of this paper is, therefore, to accelerate the fully 3D iterative scatter-corrected OSEM using a graphics processing unit (GPU) and verify its performance for an HRRT. We show that to exploit the massive thread structures of the GPU, several algorithmic modifications are necessary. For SSS implementation, a sinogram-driven approach is found to be more appropriate compared to a detector-driven approach, as fast linear interpolation can be performed in the sinogram domain through the use of texture memory. Furthermore, a pixel-driven backprojector and a ray-driven projector can be significantly accelerated by assigning threads to voxels and sinograms, respectively. Using Nvidia's GPU and compute unified device architecture (CUDA), the execution time of a SSS is less than 6 s, a single iteration of OSEM with 16 subsets takes 16 s, and a single iteration of the fully 3D scatter-corrected OSEM composed of a SSS and six iterations of OSEM takes under 105 s for the HRRT geometry, which corresponds to acceleration factors of 125× and 141× for OSEM and SSS, respectively. The fully 3D iterative scatter-corrected OSEM algorithm is validated in simulations using Geant4 application for tomographic emission and in actual experiments using an HRRT.

Characterization and Reduction of Noise in Dynamic PET Data Using Masked Volumewise Principal Component Analysis

Masked volumewise principal component (PC) analysis (PCA) is used in PET to distinguish structures that display different kinetic behaviors after administration of a tracer. When masked volumewise PCA was introduced, one article proposed noise prenormalization because of temporal and spatial variations of the noise between slices. However, the noise prenormalization proposed in that article was applicable only to datasets reconstructed using filtered backprojection (FBP). The study presented in this article aimed at developing a new noise prenormalization that is applicable to datasets regardless of whether they were reconstructed with FBP or an iterative reconstruction algorithm, such as ordered-subset expectation maximization (OSEM). A phantom study was performed to investigate differences in the expectation values and SDs of datasets reconstructed with FBP and OSEM. A novel method, higher-order PC noise prenormalization, was suggested and evaluated against other prenormalization methods on clinical datasets. Masked volumewise PCA of data reconstructed with FBP was much more dependent on an appropriate prenormalization than was analysis of data reconstructed with OSEM. Higher-order PC noise prenormalization showed an overall good performance with both FBP and OSEM reconstructions, whereas the other prenormalization methods performed well with only 1 of the 2 methods. Higher-order PC noise prenormalization has potential for improving the results from masked volumewise PCA on dynamic PET datasets independent of the type of reconstruction algorithm.

Fully-3D PET Image Reconstruction Using Scanner-Independent, Adaptive Projection Data and Highly Rotation-Symmetric Voxel Assemblies

For iterative, fully 3D positron emission tomography (PET) image reconstruction intrinsic symmetries can be used to significantly reduce the size of the system matrix. The precalculation and beneficial memory-resident storage of all nonzero system matrix elements is possible where sufficient compression exists. Thus, reconstruction times can be minimized independently of the used projector and more elaborate weighting schemes, e.g., volume-of-intersection (VOI), are applicable. A novel organization of scanner-independent, adaptive 3D projection data is presented which can be advantageously combined with highly rotation-symmetric voxel assemblies. In this way, significant system matrix compression is achieved. Applications taking into account all physical lines-of-response (LORs) with individual VOI projectors are presented for the Siemens ECAT HR+ whole-body scanner and the Siemens BrainPET, the PET component of a novel hybrid-MR/PET imaging system. Measured and simulated data were reconstructed using the new method with ordered-subset-expectation-maximization (OSEM). Results are compared to those obtained by the sinogram-based OSEM reconstruction provided by the manufacturer. The higher computational effort due to the more accurate image space sampling provides significantly improved images in terms of resolution and noise.

Optimization of ordered subset expectation maximization reconstruction for reducing urinary bladder artifacts in single-photon emission computed tomography imaging

Bladder artifact during bone single-photon emission computed tomography (SPECT) is a common source of error. The extent and severity of bladder artifacts have been described for filtered back projection (FBP) reconstruction. Ordered subset expectation maximization (OSEM) may help to address this problem of bladder artifacts, which render up to 20% of the SPECT images unreadable. The objective of this study was to evaluate the relationship of the bladder to acetabulum ratio in guiding the choice of the number of iterations and subsets used for OSEM reconstruction, for reducing bladder artifacts found on FBP reconstruction. One hundred five patients with various indications for bone scans were selected and planar and SPECT images were acquired. The SPECT images were reconstructed with both FBP and OSEM using four different combinations of iterations and subsets. The images were given to three experienced nuclear physicians who were blinded to the diagnosis and type of reconstruction used. They then labeled images from the best to the worst after which the data were analyzed. The bladder to acetabulum ratio for each image was determined which was then correlated with the different iterations and subsets used. The study demonstrated that reconstruction using OSEM led to better lesion detectability compared to FBP in 87.62% of cases. It further demonstrated that the iterations and subsets used for reconstruction of an image correlate with the bladder to acetabulum ratio. Four iterations and 8 subsets yielded the best results in 48.5% of the images, whilst 2 iterations and 8 subsets yielded the best results in 33.8%. The number of reconstructed images which yielded the best results with 2 iterations and 8 subsets was the same as or more than those with 4 iterations and 8 subsets when the bladder/acetabulum ratio (A/B) was between 0.2 and 0.39. A ratio below 0.2 or above 0.39 supports the usage of 4 iterations and 8 subsets over 2 iterations and 8 subsets. We conclude that bladder to acetabulum ratio can be used to select the optimum number of iterations and subsets for reconstruction of bone SPECT for accurate characterization of lesions. This study also confirms that reconstruction with OSEM (vs. FBP) leads to better lesion detectability and characterization.

Task-oriented quantitative image reconstruction in emission tomography for single- and multi-subject studies

Task-based selection of image reconstruction methodology in emission tomography is a critically important step when designing a PET study. This paper concerns optimizing, given the measured data of the study only, reconstruction performance for a range of quantification tasks: finding the mean radioactivity concentration for different regions of interests (ROIs), different ROI sizes and different group sizes (i.e. the number of subjects in the PET study). At present, the variability of quantification performance of different reconstruction methods, according to both the ROI and group sizes, is largely ignored. In this paper, it is shown that both the ROI and group size have a tremendous impact on the error of the estimator for the task of ROI quantification. A study-specific, task-oriented and space-variant selection rule is proposed that selects a close to optimal estimate drawn from a series of estimates obtained by filtered backprojection (FBP) and different OSEM (ordered subset expectation maximization) iterations. The optimality criterion is to minimize an estimated mean square error (MSE), where the MSE is estimated from the data in the study using the bootstrap resampling technique. The proposed approach is appropriate for both pixel-level estimates and ROI estimates in single- and multi-subject studies. An extensive multi-trial simulation study using a 2D numerical phantom and relevant count levels shows that the proposed selection rule can produce quantitative estimates that are close to the estimates that minimize the true MSE (where the true MSE can only be obtained from many independent Monte-Carlo realizations with knowledge of the ground truth). This indicates that with the proposed selection rule one can obtain a close to optimal estimate while avoiding the critical step of selecting user-defined reconstruction settings (such as an OSEM iteration number or the choice between FBP and OSEM). In this initial 2D study, only FBP and OSEM reconstruction methods are considered but the proposed selection rule should readily generalize to different estimators (i.e. different reconstruction algorithms) and 3D imaging.

Characterization of a Perirectal Artifact in 18F-FDG PET/CT

Assessing tumor involvement in the rectal region can sometimes be complicated by what appears to be an artifact on (18)F-FDG PET/CT images. This artifact manifests as a high-intensity region on the PET image, extending posterior to the bladder in the area around the rectum. The aim of this study was to describe this artifact, which-as far as we are aware-has not been previously reported, and to investigate its cause. One hundred (18)F-FDG PET/CT studies (ordered-subsets expectation maximization reconstruction, CT attenuation correction) of patients with no known malignancy in the pelvis were retrospectively reviewed. Localized regions of apparently high uptake posterior to the bladder were considered an artifact when there was a discrepancy between attenuation-corrected (asymmetric appearance) and non-attenuation-corrected images (symmetric appearance). In addition, an experiment was performed using a body phantom containing 2 cylindric inserts simulating the bladder and a region of low-attenuation rectal gas. Attenuation-corrected images were reconstructed with different amounts of spatial misregistration intentionally introduced between the CT and PET images. The artifact was observed in 15 of 100 patient studies and had a mean maximum standardized uptake value of 4.8 ± 2.7. When fused with sequentially acquired CT images, the artifact always appeared to be in the perirectal region near the bladder and an area of rectal gas. The phantom study indicated this artifact was consistent with an attenuation-correction problem caused by misregistration between CT and PET. Movement of gas within the rectum can cause an air pocket to be present during the PET acquisition at a location where CT indicated soft tissue. The resulting localized overcorrection for attenuation at the margin of the rectum and the extremely high activity concentration in the nearby bladder contributed to the artifact. Movement of gas within the rectum between acquisition of CT and PET images can lead to an artifact in attenuation-corrected PET images in the perirectal region. An awareness of this artifact and reference to non-attenuation-corrected images will aid in the interpretation of (18)F-FDG pelvis studies.

High Resolution ${}^{125}$I Pinhole SPECT Imaging of the Mouse Thyroid With the MediSPECT Small Animal CdTe Scanner

The first in vivo tomographic 125I imaging of the mouse thyroid carried out with the new MediSPECT small animal SPECT scanner is presented. The scanner is based on a fine pitch CdTe semiconductor pixel detector (14 × 14 mm2, 256 × 256 square pixel with a 55 m side) and equipped with a set of high resolution collimators. The collimation and detection units of the scanner are mounted on a gantry, rotating around a horizontal axis, along which is placed the small animal housing. In an in vivo test, the mouse was injected with a Na125 I solution having a total activity of 31.8 MBq. The planar projections for SPECT reconstruction were acquired with a 300 m pinhole (magnification 1.47 and field of view of 9.6 × 9.6 mm2). The projections were captured in a step-and-shoot fashion and were processed with an Ordered Subsets-Expectation Maximization reconstruction algorithm in order to obtain the SPECT images. Several 125I imaging tests have been made by using phantoms to assess the detector spatial resolution. The measured spatial resolution with a 300 m pinhole is about 0.5 mm in planar imaging and better than 1 mm in tomographic imaging.

Comparison of Different Types of Commercial Filtered Backprojection and Ordered-Subset Expectation Maximization SPECT Reconstruction Software

The aim of this study was to compare the performance of filtered backprojection (FBP) and ordered-subset expectation maximization (OSEM) reconstruction algorithms available in several types of commercial SPECT software. Numeric simulations of SPECT acquisitions of 2 phantoms were used: the National Electrical Manufacturers Association line phantom used for the assessment of SPECT resolution and a phantom with uniform, hot-rod, and cold-rod compartments. For FBP, no filtering and filtering of the projections with either a Butterworth filter (order 3 or 6) or a Hanning filter at various cutoff frequencies were considered. For OSEM, the number of subsets was 1, 4, 8, or 16, and the number of iterations was chosen to obtain a product number of iterations times the number of subsets equal to 16, 32, 48, or 64. The line phantom enabled us to obtain the reconstructed central, radial, and tangential full width at half maximum. The uniform compartment of the second phantom delivered the reconstructed mean pixel counts and SDs from which the coefficients of variation were calculated. Hot contrast and cold contrast were obtained from its rod compartments. For FBP, the full width at half maximum, mean pixel count, coefficient of variation, and contrast were almost software independent. The only exceptions were a smaller (by 0.5 mm) full width at half maximum for one of the software types, higher mean pixel counts for 2 of the software types, and better contrast for 2 of the software types under some filtering conditions. For OSEM, the full width at half maximum differed by 0.1-2.5 mm with the different types of software but was almost independent of the number of subsets or iterations. There was a marked dependence of the mean pixel count on the type of software used, and there was a moderate dependence of the coefficient of variation. Contrast was almost software independent. The mean pixel count varied greatly with the number of iterations for 2 of the software types, and the coefficient of variation increased with the number of iterations for all types of software. The mean pixel count, coefficient of variation, and contrast were almost constant for a fixed product number of iterations times the number of subsets, whatever the number of subsets or iterations. Most of the types of software were equivalent for FBP or OSEM reconstruction. However, a few differences were observed with some types of software and should be considered when they are used.

SU-FF-J-136: The Impact of Attenuation and Scatter Correction On the SPECT Guided Radiation Therapy for Lung Cancer Patients: Comparison of SPECT Weighted Mean Dose and Functional Lung Segmentation

Purpose: To investigate the impact of different types of image reconstruction and attenuation/scatter (A/S) correction on the calculation of dosimetric indices proposed to be used for Single Photon Emission Computed Tomography (SPECT) guided dose escalation in lung cancer patients. Methods and Materials: SPECT lung perfusion scans were obtained for nine lung cancer patients using 99mTc-macroaggregated albumin. Four image sets were reconstructed from each scan: one using a vendor provided ordered subsets expectation maximization (OSEM) algorithm, two quantitative SPECT reconstructions using OSEM methods with different types of A/S corrections and the fourth an OSEM reconstruction without any A/S correction. SPECT weighted mean dose (SWMD), dose function histogram, and functional lung volume have been calculated from dose distributions and regional perfusion maps. To investigate the dependence of SWMDs on gantry angle, twelve equally spaced co-planar open field radiation beams delivering the same MU were centered on the PTV. Three field sizes, 5×5, 7.5×7.5 and 10×10cm2 were considered. SWMDs were calculated for each field and reconstruction. Functional lung volumes were segmented in each reconstruction using 10, 20, …, 90% of maximum SPECT uptake as a threshold. Results: SWMDs calculated from reconstructions without A/S correction showed more than 5% average difference compared to those with corrections. With A/S corrections, more consistent SWMDs were found in all the three OSEM reconstructions (average difference ∼2%). However, a large variation was observed between segmented functional lung volumes and the V20 of these volumes in all four reconstructions. The difference between the volumes reached over 50% regardless of whether A/S correction was applied in the reconstruction. Conclusion: Functional volume segmentation is sensitive to the type of A/S correction. In contrast, SPECT weighted mean dose calculation produces more consistent results and appears to be a more robust choice for clinical outcome analysis and SPECT guided treatment planning.

SU‐GG‐I‐112: PET Imaging of Heterogeneous Tumors: An Investigation of the Influence of Motion On Recovered Activity

Purpose: As multi‐day PET studies become part of targeted therapy planning and treatment assessment, it is important to characterize how positioning errors affect observed tumor heterogeneity. We have characterized the uncertainty in recovered‐activity in PET‐imaging of heterogeneous tumors as a function of axial position. Method and Materials: Recovery coefficient (RC) is ratio of maximum activity‐concentration to the true specific activity in an object. The uncertainty in RC was quantified by RCerror: the quotient . We measured RCerrors for a GE Discovery LS PET/CT scanner with an axial detector width of 4.25mm. A Heterogeneous‐tumor phantom, containing three spheres (15mm, 10mm, 5mm diameter), was scanned as the phantom was moved axially in 1mm intervals. RCerror of the spheres were determined in images reconstructed by iterative ordered subset expectation maximization (OSEM) and filtered backprojection (FBP) algorithms. The clinical effect was investigated using head and neck cancer (HN) patients imaged on this scanner. 18FLT‐PET images of patients were thresholded into three levels of relative uptake, and segmented into connected sub‐regions. We simulated multi‐scan studies and calculated the changes in SUV that result from repositioning the patient. Results: OSEM reconstruction provided more accurate recovery of activity in the spheres when compared to FBP. However, uncertainty of these OSEM values was larger, as RCerrors were 27%, 8% and 4% for the 5mm, 10mm and 15mm spheres respectively. In contrast, RCerrors were 10%, 8% and 3% for FBP. The effects of RCerrors were examined in clinical images; a positioning error of 5‐degree tilt caused 23% decrease in correlation within the tumor region of patient 1 and 12% in patient 2. Conclusion: Uncertainty in the RC depends on object diameter, reconstruction algorithm, and axial‐displacement. However, heterogeneities in FBP images of consecutive PET studies would be less susceptible to errors related to the axial positioning of tumors.

Clinical evaluation of iterative reconstruction (ordered-subset expectation maximization) in dynamic positron emission tomography: Quantitative effects on kinetic modeling with N-13 ammonia in healthy subjects

The purpose of this study was to investigate the quantitative properties of ordered-subset expectation maximization (OSEM) on kinetic modeling with nitrogen 13 ammonia compared with filtered backprojection (FBP) in healthy subjects. Cardiac N-13 ammonia positron emission tomography (PET) studies from 20 normal volunteers at rest and during dipyridamole stimulation were analyzed. Image data were reconstructed with either FBP or OSEM. FBP- and OSEM-derived input functions and tissue curves were compared together with the myocardial blood flow and spillover values. The late area under the OSEM input functions during dipyridamole is overestimated by 30% (P < .0001) relative to FBP. Conversely, the area under the late part of the OSEM tissue curves is underestimated by 20% (P < .0001) compared with FBP during both rest and dipyridamole. These differences in tissue and input functions cause the resting myocardial blood flow to be underestimated by 15% (P < .0001). During dipyridamole, the OSEM flow is underestimated by 25% (P < .0001) relative to FBP, causing the myocardial flow reserve to be underestimated by 10% (P < .0001). Large inter-regional differences in FBP and OSEM flow values were observed with a flow underestimation of 45% (rest/dipyridamole) in the septum and of 5% (rest) and 15% (dipyridamole) in the lateral myocardial wall. OSEM reconstruction of myocardial perfusion images with N-13 ammonia and PET produces high-quality images for visual interpretation. However, compared with FBP, OSEM is associated with substantial underestimation of perfusion on quantitative imaging. Our findings indicate that OSEM should be used with precaution in clinical PET studies.

Evaluation of reconstruction techniques for lung single photon emission tomography: A Monte Carlo study

In studies of the distribution of lung function, the image quality of lung single photon emission computed tomography (SPECT) is important and one factor influencing it is the reconstruction algorithm. To systematically evaluate ordered subsets expectation maximization (OSEM) and compare it with filtered back-projection (FBP) for lung SPECT with Tc. The evaluation of the number of iterations used in OSEM was based on the image quality parameter contrast. The comparison between OSEM and FBP was based on trade-off plots between statistical noise and spatial resolution for different filter parameters, collimators and count-levels. A Monte Carlo technique was used to simulate SPECT studies of a digital thorax phantom containing two sets of activity: one with a homogeneous activity distribution within the lungs and the other with superposed high- and low-activity objects. Statistical noise in the reconstructed images was calculated as the coefficient of variation (CV) and spatial resolution as full width at half-maximum (FWHM). For the configuration studied, the OSEM reconstruction in combination with post-filtering should be used in lung SPECT studies with at least 60 MLEM equivalent iterations. Compared to FBP the spatial resolution was improved by about 1 mm. For a constant level of CV, a four-fold increase in count level resulted in an increased resolution of about 2 mm. Spatial resolution and cut-off frequency depends on what value of noise in the image is acceptable also increased by using a low-energy, high-resolution collimator for CV values above 3%. The choice of noise-reducing filter and cut-off frequency depends on what value of noise in the image is acceptable.

Evaluation of reconstruction techniques in regional cerebral blood flow SPECT using trade-off plots: A Monte Carlo study

The image quality of single photon emission computed tomography (SPECT) depends on the reconstruction algorithm used. The purpose of the present study was to evaluate parameters in ordered subset expectation maximization (OSEM) and to compare systematically with filtered back-projection (FBP) for reconstruction of regional cerebral blood flow (rCBF) SPECT, incorporating attenuation and scatter correction. The evaluation was based on the trade-off between contrast recovery and statistical noise using different sizes of subsets, number of iterations and filter parameters. Monte Carlo simulated SPECT studies of a digital human brain phantom were used. The contrast recovery was calculated as measured contrast divided by true contrast. Statistical noise in the reconstructed images was calculated as the coefficient of variation in pixel values. A constant contrast level was reached above 195 equivalent maximum likelihood expectation maximization iterations. The choice of subset size was not crucial as long as there were > or = 2 projections per subset. The OSEM reconstruction was found to give 5-14% higher contrast recovery than FBP for all clinically relevant noise levels in rCBF SPECT. The Butterworth filter, power 6, achieved the highest stable contrast recovery level at all clinically relevant noise levels. The cut-off frequency should be chosen according to the noise level accepted in the image. Trade-off plots are shown to be a practical way of deciding the number of iterations and subset size for the OSEM reconstruction and can be used for other examination types in nuclear medicine.

Comparison of multi-ray and point-spread function based resolution recovery methods in pinhole SPECT reconstruction

Statistical reconstruction methods allow resolution recovery in tomographic reconstruction. Even though resolution recovery has the potential to improve overall image quality, pinhole SPECT images are still often reconstructed using simplified models of the acquisition geometry in order to reduce reconstruction time. This paper investigates the benefits of two resolution recovery methods, multi-ray and point-spread function based, in pinhole SPECT by comparing them to uncorrected reconstruction. Resolution recovery was incorporated into ordered subsets expectation maximization reconstruction algorithm. The first of the correction methods used a simple but very fast multiple projection ray approach, whereas the second, much slower, method modelled the acquisition geometry more accurately using the analytical point-spread function of the pinhole collimator. Line source, Jaszczak and contrast phantom studies were performed and used for comparison. Resolution recovery improved resolution, contrast and visual quality of the images when compared to reconstructions without it. The method based on the point-spread function performed slightly better, but was almost 50 times slower than the much simpler multi-ray approach. The multiple projection ray approach is a promising method for very fast and easy resolution recovery in pinhole SPECT. It has a profound effect on image quality and can markedly improve the resolution-sensitivity trade-off.

WE-D-ValB-01: Effects of PET Reconstruction Parameters On the Delineation of Heterogeneous Target Volumes

Purpose As emerging radiotherapy techniques incorporate biological targeting of sub‐tumor volumes, steps must be taken to ensure the validity of the assumed substructures. This study measures the effects of PET image reconstruction on heterogeneous target definitions both in vivo and in a phantom. Method and Materials: A known heterogeneous phantom composed of Y‐86 and Ge‐68 spheres with an F‐18 background altering signal‐to‐background ratios tested the accuracy of reconstructions using ordered subset expectation maximization (OSEM) with varying numbers of iterations and filtered backprojection (FBP) with Hanning, Shepp‐Logan, and ramp filters. In vivo measurements used heterogeneously proliferating tumorimages obtained from a canine tumorimaged using [F‐18]FLT at three stages of treatment using the same reconstruction methods. Difference images and standard deviations were used to assess the reconstruction differences. A three‐dimensional form of the Moran I(d) spatial statistic was used to assess global heterogeneity at various correlation distances. Results: Absolute difference images from FBP and 2 iteration OSEM reconstructions showed internal tumor voxel clusters deviating by more than 10% of the maximum SUV of the reference image (OSEM20) and relative voxel values varying by as much as 40% in tumor periphery. Image differences in OSEM reconstructions significantly decreased after 10 iterations, accompanied by decreases in the standard deviation of differences and slight increases in heterogeneity as global I(d) values decreased. FBP reconstructions both underestimated (Hanning, Shepp‐Logan) and overestimated (ramp) global heterogeneity I(d) relative to reference values, but large standard deviations of absolute difference indicated images compared poorly to the reference. Conclusion:Tumor heterogeneity obtained through PET may vary by at least 10% internally with larger variability at the periphery, greatly affecting both tumor volume delineation and internal heterogeneity. Prescriptions for dose painting based on proliferation measures can vary widely with the reconstruction algorithm.

Noise reduction for low-dose single-slice helical CT sinograms

Helical computed tomography (HCT) has several advantages over conventional step-and-shoot CT for imaging a relatively large object, especially for dynamic studies. However, HCT may increase X-ray exposure significantly. This work aims to reduce the radiation by lowering X-ray tube current (mA) and filtering low-mA (or dose) sinogram noise of HCT. The noise reduction method is based on three observations on HCT: (1) the axial sampling of HCT projections is nearly continuous as detection system rotates; (2) the noise distribution in sinogram space is nearly a Gaussian after system calibration (including logarithmic transform); and (3) the relationship between the calibrated data mean and variance can be expressed as an exponential functional across the field-of-view. Based on the second and third observations, a penalized weighted least-squares (PWLS) solution is an optimal choice, where the weight is given by the mean-variance relationship. The first observation encourages the use of Karhunen-Loève (KL) transform along the axial direction because of the associated correlation. In the KL domain, the eigenvalue of each principal component and the derived data variance provide the signal-to-noise ratio (SNR) information, resulting in a SNR-adaptive noise reduction. The KL-PWLS noise-reduction method was implemented analytically for efficient restoration of large volume HCT sinograms. Simulation studies showed a noticeable improvement, in terms of image quality and defect detectability, of the proposed noise-reduction method over the Ordered-Subsets Expectation-Maximization reconstruction and the conventional low-pass noise filtering with optimal cutoff frequency and/or other filter parameters.

Simultaneous assessment of cardiac perfusion and function using 5-dimensional imaging with Tc-99m teboroxime

Dynamic single photon emission computed tomography (SPECT) acquisition and reconstruction of early poststress technetium 99m teboroxime washout images has been shown to be useful in the detection of coronary disease. Assessment of poststress regional wall motion may offer additional use in assessing coronary disease. Our goal was to investigate the feasibility of simultaneously imaging myocardial ischemia and transient poststress akinesis using gated-dynamic SPECT. A gated-dynamic mathematical cardiac torso (MCAT) phantom was developed to model both teboroxime kinetics and cardiac regional wall motion. A lesion was simulated as having delayed poststress teboroxime washout together with a transient poststress wall motion abnormality. Gated projection data were created to represent a 3-headed SPECT system undergoing a total rotation of 480 degrees . The dynamic expectation-maximization reconstruction algorithm with postsmoothing across gating intervals by Wiener filtering, and the ordered-subset expectation maximization reconstruction algorithm with 3-point smoothing across gating intervals were compared. Compared with the ordered-subset expectation maximization with 3-point smoothing, the dynamic expectation-maximization algorithm with Wiener filtering was able to produce visually higher-quality images and more accurate left ventricular ejection fraction estimates. From simulations, we conclude that changing cardiac function and tracer localization possibly can be assessed by using a gated-dynamic acquisition protocol combined with a 5-dimensional reconstruction strategy.

Non-isotropic noise correlation in PET data reconstructed by FBP but not by OSEM demonstrated using auto-correlation function

BackgroundPositron emission tomography (PET) is a powerful imaging technique with the potential of obtaining functional or biochemical information by measuring distribution and kinetics of radiolabelled molecules in a biological system, both in vitro and in vivo. PET images can be used directly or after kinetic modelling to extract quantitative values of a desired physiological, biochemical or pharmacological entity. Because such images are generally noisy, it is essential to understand how noise affects the derived quantitative values. A pre-requisite for this understanding is that the properties of noise such as variance (magnitude) and texture (correlation) are known.MethodsIn this paper we explored the pattern of noise correlation in experimentally generated PET images, with emphasis on the angular dependence of correlation, using the autocorrelation function (ACF). Experimental PET data were acquired in 2D and 3D acquisition mode and reconstructed by analytical filtered back projection (FBP) and iterative ordered subsets expectation maximisation (OSEM) methods. The 3D data was rebinned to a 2D dataset using FOurier REbinning (FORE) followed by 2D reconstruction using either FBP or OSEM. In synthetic images we compared the ACF results with those from covariance matrix. The results were illustrated as 1D profiles and also visualized as 2D ACF images.ResultsWe found that the autocorrelation images from PET data obtained after FBP were not fully rotationally symmetric or isotropic if the object deviated from a uniform cylindrical radioactivity distribution. In contrast, similar autocorrelation images obtained after OSEM reconstruction were isotropic even when the phantom was not circular. Simulations indicated that the noise autocorrelation is non-isotropic in images created by FBP when the level of noise in projections is angularly variable. Comparison between 1D cross profiles on autocorrelation images obtained by FBP reconstruction and covariance matrices produced almost identical results in a simulation study.ConclusionWith asymmetric radioactivity distribution in PET, reconstruction using FBP, in contrast to OSEM, generates images in which the noise correlation is non-isotropic when the noise magnitude is angular dependent, such as in objects with asymmetric radioactivity distribution. In this respect, iterative reconstruction is superior since it creates isotropic noise correlations in the images.

Evaluation of the number of sampling step angles in SPECT Images: comparison between FBP and OS-EM reconstruction algorithms

We compared filtered back projection (FBP) and ordered subset expectation maximization (OS-EM) reconstruction algorithms to examine the effects of sampling step angle on SPECT image reconstruction. Image sampling was compared between conditions of constant total sampling time (16 min) and constant sampling time (40 sec) for each step with angles of 3, 5, 7.5, and 10 degrees. Generally, OS-EM was superior to FBP in terms of image reconstruction. Changes in the sampling step angles did not significantly affect the quality of the reconstructed images with OS-EM insofar as acquisition counts were sufficient for evaluation. On the other hand, the quality of FBP images deteriorated with larger angles such as 7.5 and 10 degrees, and it was difficult to obtain stable results. In conclusion, OS-EM improves the quality of images required for examination.