3D Ordered Subset Expectation Maximization Research Articles

A Pilot Study of the Striatal Dopamine Transporter Levels in Kratom-Dependent and Normal Subjects Using 99mTc-TRODAT-1 Single Photon Emission Computed Tomography-Computed Tomography (SPECT-CT).

The study aims to elucidate the effects of kratom addiction on dopamine transporter (DAT) using[2-[[2-[[[3-(4-chlorophenyl)-8-methyl-8-azabicyclo[3.2.1]oct-2-yl]methyl](2-mercaptoethyl)amino]ethyl]amino]ethanethiolato(3-)-N2,N20,S2,S20]oxo-[1R-(exo-exo)]-[99mTc] technetium (99mTc-TRODAT-1) brain single photon emission computed tomography-computed tomography (SPECT-CT) in kratom-dependent and healthy subjects. We recruited 12 kratom-dependent subjects and 13 healthy men to participate in this study. Addiction, craving, depression, and cognitive scores were assessed. All subjects received a single bolus injection of 99mTc-TRODAT-1 with 914.1 MBq ± 65.5 of activity (mean ± SD). The brain SPECT-CT images were reconstructed using 3D ordered subset expectation maximization (3D-OSEM) along with attenuation correction (AC), scatter correction (SC), and resolution recovery (RR) with an iteration number of four and a subset of 10. The Cohen's Kappa interrater-reliability between two raters, the standardized uptake value of body weight (SUVBW), and the asymmetrical index percentage (AI%) were evaluated. Kappa statistics showed a fine agreement of abnormal 99mTc-TRODAT-1 uptake in the striatum region for the kratom-dependent group with the κ value of 0.69 (p = 0.0001), and the percentage of agreement for rater 1 and rater 2 was 56% and 64%, respectively. There was a reduction in average SUV in kratom-dependent subjects compared to healthy control subjects in the left caudate and left striatum (0.938 vs. 1.251, p = 0.014, and 1.055 vs. 1.29, p = 0.036, respectively). There was a significant difference in the AI% of the caudate region between the kratom-dependent group and the normal group (33% vs. 14%, p = 0.019). Our findings signify that kratom addiction, may cause a change in DAT level and the results can be confirmed using 99mTc-TRODAT-1 SPECT-CT.

Performance evaluation of SimPET-L and SimPET-XL: MRI-compatible small-animal PET systems with rat-body imaging capability

BackgroundSimPET-L and SimPET-XL have recently been introduced with increased transaxial fields of view (FOV) compared with their predecessors (SimPET™ and SimPET-X), enabling whole-body positron emission tomography (PET) imaging of rats. We conducted performance evaluations of SimPET-L and SimPET-XL and rat-body imaging with SimPET-XL to demonstrate the benefits of increased axial and transaxial FOVs.ProceduresThe detector blocks in SimPET-L and SimPET-XL consist of two 4 × 4 silicon photomultiplier arrays coupled with 20 × 9 array lutetium oxyorthosilicate crystals. SimPET-L and SimPET-XL have an inner diameter (bore size) of 7.6 cm, and they are composed of 40 and 80 detector blocks yielding axial lengths of 5.5 and 11 cm, respectively. Each system was evaluated according to the National Electrical Manufacturers Association NU4-2008 protocol. Rat imaging studies, such as 18F-NaF and 18F-FDG PET, were performed using SimPET-XL.ResultsThe radial resolutions at the axial center measured using the filtered back projection, 3D ordered-subset expectation maximization (OSEM), and 3D OSEM with point spread functions correction were 1.7, 0.82, and 0.82 mm FWHM in SimPET-L and 1.7, 0.91, and 0.91 mm FWHM in SimPET-XL, respectively. The peak sensitivities of SimPET-L and SimPET-XL were 6.30% and 10.4% for an energy window of 100–900 keV and 4.44% and 7.25% for a window of 250–750 keV, respectively. The peak noise equivalent count rate with an energy window of 250–750 keV was 249 kcps at 44.9 MBq for SimPET-L and 349 kcps at 31.3 MBq for SimPET-XL. In SimPET-L, the uniformity was 4.43%, and the spill-over ratios in air- and water-filled chambers were 5.54% and 4.10%, respectively. In SimPET-XL, the uniformity was 3.89%, and the spill-over ratio in the air- and water-filled chambers were 3.56% and 3.60%. Moreover, SimPET-XL provided high-quality images of rats.ConclusionSimPET-L and SimPET-XL show adequate performance compared with other SimPET systems. In addition, their large transaxial and long axial FOVs provide imaging capability for rats with high image quality.

Optimization of 99m Tc whole-body SPECT/CT image quality: A phantom study.

PurposeInvestigate the impact of acquisition time and reconstruction parameters on single‐photon emission computed tomography/computed tomography (SPECT/CT) image quality with the ultimate aim of finding the shortest possible acquisition time for clinical whole‐body SPECT/CT (WB‐SPECT/CT) while maintaining image qualityMethodsThe National Electrical Manufacturers Association (NEMA) image quality measurements were performed on a SPECT/CT imaging system using a NEMA International Electrotechnical Commission (IEC) phantom with spherical inserts of varying diameter (10–37 mm), filled with 99mTc in activity sphere‐to‐background concentration ratio of 8.5:1. A gated acquisition was acquired and binned data were summed to simulate acquisitions of 15, 8, and 3 s per projection angle. Images were reconstructed on a Hermes (HERMES Medical Solutions AB, Stockholm, Sweden) workstation using eight subsets and between 4 and 24 iterations of the three‐dimensional (3D) ordered subset expectation maximization (OSEM) algorithm. Reconstructed images were post‐smoothed with 3D Gaussian filter ranging from 0 to 12 mm full‐width at half maximum (FWHM). Contrast recovery, background variability, and contrast‐to‐noise ratio were evaluatedResultsAs expected, the spheres were more clearly defined as acquisition time and count statistics improved. The optimal iteration number and Gaussian filter were determined from the contrast recovery convergence and level of noise. Convergence of contrast recovery was observed at eight iterations while 12 iterations yielded stabilized values at all acquisition times. In addition, it was observed that applying 3D Gaussian filter of 8–12 mm FWHM suppressed the noise and mitigated Gibbs artifacts. Background variability was larger for small spheres than larger spheres and the noise decreased when acquisition time became longer. A contrast‐to‐noise ratio >5 was reached for the two smallest spheres of 10 and 13 mm at acquisition times of 8 sConclusionOptimized reconstruction parameters preserved image quality with reduce acquisition time in present study. This study suggests an optimal protocol for clinical 99mTc SPECT/CT can be reached at 8 s per projection angle, with data reconstructed using 12 iterations and eight subset of the 3D OSEM algorithm and 8 mm Gaussian post‐filter.

Fast and Accurate Thoracic SPECT Image Reconstruction

In Single-Photon Emission Computed Tomography (SPECT), the reconstructed image has insufficient contrast, poor resolution and inaccurate volume of the tumor size due to physical degradation factors. Generally, nonstationary filtering of the projection or the slice is one of the strategies for correcting the resolution and therefore improving the quality of the reconstructed SPECT images. This paper presents a new 3D algorithm that enhances the quality of reconstructed thoracic SPECT images and reduces the noise level with the best degree of accuracy. The suggested algorithm is composed of three steps. The first one consists of denoising the acquired projections using the benefits of the complementary properties of both the Curvelet transform and the Wavelet transforms to provide the best noise reduction. The second step is a simultaneous reconstruction of the axial slices using the 3D Ordered Subset Expectation Maximization (OSEM) algorithm. The last step is post-processing of the reconstructed axial slices using one of the newest anisotropic diffusion models named Partial Differential Equation (PDE). The method is tested on two digital phantoms and clinical bone SPECT images. A comparative study with four algorithms reviewed on state of the art proves the significance of the proposed method. In simulated data, experimental results show that the plot profile of the proposed model keeps close to the original one compared to the other algorithms. Furthermore, it presents a notable gain in terms of contrast to noise ratio (CNR) and execution time. The proposed model shows better results in the computation of contrast metric with a value of 0.68 ± 7.2 and the highest signal to noise ratio (SNR) with a value of 78.56 ± 6.4 in real data. The experimental results prove that the proposed algorithm is more accurate and robust in reconstructing SPECT images than the other algorithms. It could be considered a valuable candidate to correct the resolution of bone in the SPECT images.

Can a penalized-likelihood estimation algorithm be used to reduce the injected dose or the acquisition time in 68Ga-DOTATATE PET/CT studies?

BackgroundImage quality and quantitative accuracy of positron emission tomography (PET) depend on several factors such as uptake time, scanner characteristics and image reconstruction methods. Ordered subset expectation maximization (OSEM) is considered the gold standard for image reconstruction. Penalized-likelihood estimation (PL) algorithms have been recently developed for PET reconstruction to improve quantitation accuracy while maintaining or even improving image quality. In PL algorithms, a regularization parameter β controls the penalization of relative differences between neighboring pixels and determines image characteristics. In the present study, we aim to compare the performance of Q.Clear (PL algorithm, GE Healthcare) and OSEM (3 iterations, 8 subsets, 6-mm post-processing filter) for 68Ga-DOTATATE (68Ga-DOTA) PET studies, both visually and quantitatively.Thirty consecutive whole-body 68Ga-DOTA studies were included. The data were acquired in list mode and were reconstructed using 3D OSEM and Q.Clear with various values of β and various acquisition times per bed position (bp), thus generating images with reduced injected dose (1.5 min/bp: β = 300–1100; 1.0 min/bp: β = 600–1400 and 0.5 min/bp: β = 800–2200). An additional analysis adding β values up to 1500, 1700 and 3000 for 1.5, 1.0 and 0.5 min/bp, respectively, was performed for a random sample of 8 studies. Evaluation was performed using a phantom and clinical data. Two experienced nuclear medicine physicians blinded to the variables assessed the image quality visually.ResultsClinical images reconstructed with Q.Clear, set at 1.5, 1.0 and 0.5 min/bp using β = 1100, 1300 and 3000, respectively, resulted in images with noise equivalence to 3D OSEM (1.5 min/bp) with a mean increase in SUVmax of 14%, 13% and 4%, an increase in SNR of 30%, 24% and 10%, and an increase in SBR of 13%, 13% and 2%. Visual assessment yielded similar results for β values of 1100–1400 and 1300–1600 for 1.5 and 1.0 min/bp, respectively, although for 0.5 min/bp there was no significant improvement compared to OSEM.Conclusion68Ga-DOTA reconstructions with Q.Clear, 1.5 and 1.0 min/bp, resulted in increased tumor SUVmax and in improved SNR and SBR at a similar level of noise compared to 3D OSEM. Q.Clear with β = 1300–1600 enables one-third reduction of acquisition time or injected dose, with similar image quality compared to 3D OSEM.

A GPU-accelerated fully 3D OSEM image reconstruction for a high-resolution small animal PET scanner using dual-ended readout detectors

In this work, a GPU-accelerated fully 3D ordered-subset expectation maximization (OSEM) image reconstruction with point spread function (PSF) modeling was developed for a small animal PET scanner with a long axial field of view (FOV). Dual-ended readout detectors that provided high depth of interaction (DOI) resolution were used for the small animal PET scanner to simultaneously achieve uniform high spatial resolution and high sensitivity. First, we developed a novel sinogram generation method, in which the dimension of the sinogram was determined first and then an event was assigned to a few neighboring sinogram elements by using weights that are inversely proportional to the distance from the measured line of response (LOR) to the LOR of the sinogram elements. System geometric symmetry, precomputation of LOR-driven ray-tracing and texture memory were applied to accelerate the GPU-based reconstruction. We developed a spatially variant PSF model where the PSF parameters were obtained by using point source images measured at 18 positions in the FOV and a spatial invariant PSF model where the PSF parameters were obtained by using only one image measured at the center FOV. The performance of the image reconstruction method was evaluated by using simulated phantom data as well as phantom and in-vivo mouse data acquired on the scanner. The results showed that the proposed reconstruction method provided better spatial resolution, a higher contrast recovery coefficient and lower noise than the OSEM reconstruction and was more than 1000 times faster than the CPU-based reconstruction. The spatially variant PSF model did not result in any spatial resolution improvement compared to the spatial invariant PSF model, and thus, the latter that is much easier to implement in image reconstruction and can be used in a small animal PET scanner using detectors with very high DOI resolution. A whole body 18F-FDG mouse image with high resolution and a high contrast to noise ratio was obtained by using the proposed reconstruction method.

A study on compensatory scattering correction of industrial γ-photon 3D imaging method

As a non-destructive testing technology, γ-photon imaging technology has a good application prospect in the industrial field. However, due to the γ-photon scattering problem caused by high-density metal and the rapid industrial detection requirement, γ-photon imaging technology has not been effectively applied in industrial detection. Thus, this paper proposed a compensatory single scatter simulation (C-SSS) and combined it with the 3D ordered subset expectation maximization (3D-OSEM) image reconstruction algorithm for optimization to solve the above problems. To verify the effectiveness of the C-SSS algorithm, this paper compared C-SSS with the single scatter simulation by two types of phantoms and the inner cavity detection of industrial components. The comparison results proved that C-SSS can effectively improve the measurement accuracy and reduce the scanning time. In addition, after the algorithm code was optimized and accelerated by the graphic processing unit, the execution time of C-SSS was ∼4 min and a single iteration of 3D-OSEM took ∼3 min, basically satisfying the requirements of rapid industrial detection. Simulation and experiment results show the potential of the proposed algorithm in industrial detection.

Performance evaluation of HiPET, a high sensitivity and high resolution preclinical PET tomograph

HiPET is a recently developed prototype preclinical PET scanner dedicated to high sensitivity and high resolution molecular imaging. The HiPET system employs a phoswich depth of interaction (DOI) detector design, which also allows identification of the large majority of the cross layer crystal scatter (CLCS) events. This work evaluates its performance characteristics following the National Electrical Manufacturers Association (NEMA) NU4-2008 protocol.The HiPET consists of twenty flat panel type detectors arranged in two rings. The inner diameter is 160 mm and the axial field of view (FOV) is 104 mm. Each detector is comprised of two layers of phoswich scintillator crystal arrays, a tapered, pixelated glass lightguide and a multi anode photomultiplier tube (MAPMT). The front (gamma ray entrance) layer is a 48 × 48 pixelated cerium doped lutetium yttrium orthosilicate (LYSO) scintillator array with individual crystals measuring 1.01 × 1.01 × 6.1 mm. The back (towards the PMT) layer is a 32 × 32 pixelated bismuth germanate (BGO) scintillator array with individual crystals measuring 1.55 × 1.55 × 8.9 mm.For energy windows of 250–650 keV and 350–650 keV, the peak absolute sensitivity at the center of the FOV was 13.5% and 10.4% including CLCS events, and 11.8% and 8.9% excluding CLCS events, respectively. The average detector energy resolution derived by averaging the individual crystal spectra was 11.7% ± 1.4% for LYSO and 17.0% ± 1.4% for BGO. The 3D ordered-subsets expectation maximization (OSEM) reconstructed image of a point source in air, ranged from 0.73 mm to 1.19 mm, with an average value of 0.93 ± 0.09 mm at all measured locations. The peak noise equivalent count rate (NECR) and scatter fraction were 179 kcps at 12.4 MBq and 6.9% for the mouse-sized phantom, and 63 kcps at 11.3 MBq and 18.3% for the rat-sized phantom. For the NEMA image quality phantom, the uniformity was 5.8%, and the spillover ratios measured in the water- and air-filled cold region chambers were 0.047 and 0.044, respectively. The recovery coefficients (RC) ranged from 0.31 to 0.92.These results and in vivo evaluation demonstrate that the HiPET can achieve high quality molecular imaging for biomedical applications.

Texture analysis in 177Lu SPECT phantom images: Statistical assessment of uniformity requirements using texture features.

The purpose of this study was to apply texture analysis (TA) to evaluate the uniformity of SPECT images reconstructed with the 3D Ordered Subsets Expectation Maximization (3D-OSEM) algorithm. For this purpose, a cylindrical homogeneous phantom filled with 177Lu was used and a total of 24 spherical volumes of interest (VOIs) were considered inside the phantom. The location of the VOIs was chosen in order to define two different configurations, i.e. gravity and radial configuration. The former configuration was used to investigate the uniformity of distribution of 177Lu inside the phantom, while the latter configuration was used to investigate the lack of uniformity from center towards edge of the images. For each VOI, the trend of different texture features considered as a function of 3D-OSEM updates was investigated in order to evaluate the influence of reconstruction parameters. TA was performed using CGITA software. The equality of the average texture feature trends in both spatial configurations was assumed as the null hypothesis and was tested by functional analysis of variance (fANOVA). With regard to the gravity configuration, no texture feature rejected the null hypothesis when the number of subsets increased. For the radial configuration, the statistical analysis revealed that, depending on the 3D-OSEM parameters used, a few texture features were capable of detecting the non-uniformity of 177Lu distribution inside the phantom moving from the center of the image towards its edge. Finally, cross-correlation coefficients were calculated to better identify the features that could play an important role in assessing quality assurance procedures performed on SPECT systems.

Impact of Resolution Recovery in Quantitative 99mTc SPECT/CT Cardiac Phantom Studies

BackgroundThe aim of this study was to validate the quantitative accuracy of single photon emission computed tomography with computed tomography (SPECT/CT) images in cardiac phantom studies. The study was performed by assessing the effect of resolution recovery (RR) when using half-time of imaging acquisition in cardiac phantom. MethodsThe SPECT/CT images of the anthropomorphic phantom with a cardiac insert, liver, lung, and spine were acquired using the GE Discovery (NM/CT 670) SPECT/CT system. Different concentration activity ratios for different organ (10:10:1:0, cardiac:liver:background:lung) regions were acquired by using full- and half-time protocols for 643 and 1283 voxel sizes that were reconstructed using filtered back projection (FBP) method and 3D ordered subset expectation maximization (3D-OSEM). Attenuation correction and scatter correction were applied to both reconstructions, whereas the RR only can be applied for 3D-OSEM. The data were analyzed and reported in terms of absolute recovery coefficient percentage between the cardiac insert and background activity concentration. Another parameter used to assess the quantitative accuracy for defect region was the relative error percentage. ResultsThe result of recovery coefficient percentage shows that the 3D-OSEM reconstruction with the RR gives the highest percentage estimation accuracy of 70% of activity recovery in the cardiac phantom wall compared with FBP (10.6%). The relative error percentage for reconstructed SPECT/CT images using 3D-OSEM reconstruction with RR shows the least error compared with FBP (21% vs. 45.1%) both in the full-and half-time acquisition of images with a larger number of matrix size used. Conclusions3D-OSEM reconstruction with the RR is beneficial in giving better quantitative evaluation with a good resolution myocardial perfusion image. To accomplish this, a larger matrix size is required for 3D-OSEM reconstruction with the RR and it demonstrated an improvement in image resolution and increased quantitative accuracy of the final reconstructed SPECT/CT images.

Evaluation of MR-based PET Images with a Homogeneous μmap by Using Integrated PET/MR

This study intends to obtain magnetic resonance (MR)-based positron emission tomography (PET) images with a relatively uniform μmap by using a National Electrical Manufacturers Association (NEMA) International Electrotechnical Commission (IEC) body phantom and to evaluate the PET phantom images by applying various reconstruction parameters in accordance with the protocol of the NEMA. In order to obtain a uniform MR-based μmap, we set the initial voltage of the RF transmitter adjustment algorithm to 75 V, and we obtained the attenuation-corrected PET image by applying the two-point vibe Dixon MR sequence. The images reconstructed using the 3D ordered subset expectation maximization (OSEM) algorithm with the point spread function (PSF) showed the highest percentage of contrast recovery and the lowest percentage background variability compared to the other 3D reconstruction algorithms like the Filtered backprojection (FBP), 3D OSEM, and 3D OSEM with PSF algorithms. The 3D OSEM with PSF reconstruction algorithm is confirmed to be effective for maintaining the optimum image quality.

Performance Evaluation of a Dedicated Preclinical PET/CT System for the Assessment of Mineralization Process in a Mouse Model of Atherosclerosis.

The purpose of this study was to assess the impact of positron emission tomography/X-ray computed tomography (PET/CT) acquisition and reconstruction parameters on the assessment of mineralization process in a mouse model of atherosclerosis. All experiments were performed on a dedicated preclinical PET/CT system. CT was evaluated using five acquisition configurations using both a tungsten wire phantom for in-plane resolution assessment and a bar pattern phantom for cross-plane resolution. Furthermore, the radiation dose of these acquisition configurations was calculated. The PET system was assessed using longitudinal line sources to determine the optimal reconstruction parameters by measuring central resolution and its coefficient of variation. An in vivo PET study was performed using uremic ApoE-/-, non-uremic ApoE-/-, and control mice to evaluate optimal PET reconstruction parameters for the detection of sodium [18F]fluoride (Na[18F]F) aortic uptake and for quantitative measurement of Na[18F]F bone influx (Ki) with a Patlak analysis. For CT, the use of 1 × 1 and 2 × 2 binning detector mode increased both in-plane and cross-plane resolution. However, resolution improvement (163 to 62μm for in-plane resolution) was associated with an important radiation dose increase (1.67 to 32.78Gy). With PET, 3D-ordered subset expectation maximization (3D-OSEM) algorithm increased the central resolution compared to filtered back projection (1.42 ± 0.35mm vs. 1.91 ± 0.08, p < 0.001). The use of 3D-OSEM with eight iterations and a zoom factor 2 yielded optimal PET resolution for preclinical study (FWHM = 0.98mm). These PET reconstruction parameters allowed the detection of Na[18F]F aortic uptake in 3/14 ApoE-/- mice and demonstrated a decreased Ki in uremic ApoE-/- compared to non-uremic ApoE-/- and control mice (p < 0.006). Optimizing reconstruction parameters significantly impacted on the assessment of mineralization process in a preclinical model of accelerated atherosclerosis using Na[18F]F PET. In addition, improving the CT resolution was associated with a dramatic radiation dose increase.

Quantitative accuracy of 177Lu SPECT imaging for molecular radiotherapy.

The purpose of this study is to investigate the optimal reference geometry for gamma camera calibration. Yet another question of interest was to assess the influence of the number of 3D Ordered Subsets Expectation Maximization (3D-OSEM) updates on activity quantification for SPECT imaging with 177Lu. The accuracy of 177Lu activity quantification was assessed both in small and in large objects. Two different reference geometries, namely a cylindrical homogeneous phantom and a Jaszczak 16 ml sphere surrounded by cold water, were used to determine the gamma camera calibration factor of a commercial SPECT/CT system. Moreover, the noise level and the concentration recovery coefficient were evaluated as a function of the number of 3D-OSEM updates by using the SPECT/CT images of the reference geometry phantoms and those of a cold Jaszczak phantom with three hot spheres (16ml, 8ml and 4ml), respectively. The optimal choice of the number of 3D-OSEM updates was based on a compromise between the noise level achievable in the reconstructed SPECT images and the concentration recovery coefficients. The quantitative accuracy achievable was finally validated on a test phantom, where a spherical insert composed of two concentric spheres was used to simulate a lesion in a warm background. Our data confirm and extend previous observations. Using the calibration factor obtained with the cylindrical homogeneous phantom and the Jaszczak 16 ml sphere, the recovered activity in the test phantom was underestimated by -16.4% and -24.8%, respectively. Our work has led us to conclude that gamma camera calibration performed with large homogeneous phantom outperforms calibration executed with the Jaszczak 16ml sphere. Furthermore, the results obtained support the assumption that approximately 50 OSEM updates represent a good trade-off to reach convergence in small volumes, meanwhile minimizing the noise level.

The Effect of Misregistration Between CT-Attenuation and PET-Emission Images in 13N-Ammonia Myocardial PET/CT.

In 2-dimensional cardiac PET/CT, misregistration between the PET and CT images due to respiratory and cardiac motion causes tracer uptake to appear substantially reduced. The resolution and quality of the images have been considerably improved by the use of 3-dimensional (3D) PET acquisitions. In the current study, we investigated the impact that misregistration between PET and CT images has on myocardial (13)N-ammonia uptake in images reconstructed with 3D ordered-subset expectation maximization combined with time-of-flight and point-spread-function modeling. Eight healthy volunteers (7 men and 1 woman; mean age ± SD, 53 ± 19 y) underwent (13)N-ammonia cardiac PET/CT at rest. First, any misregistration between the PET and CT images was manually corrected to generate reference images. Then, the images were intentionally misregistered by shifting the PET images from the reference images by a degree of 1, 2, 3, 4, 5, 10, and 15 mm along both the x-axis (left) and the z-axis (cranial). For each degree of misregistration, the PET images were reconstructed using the CT-attenuation images. The left ventricular short-axis PET/CT images were divided into 4 segments: anterior wall, inferior wall, lateral wall, and septum. The erroneous decrease in myocardial uptake in basal, mid, and apical slices was visually graded using a 4-point scale (0 = none, 1 = mild, 2 = moderate, and 3 = severe). Wall-to-septum uptake ratios were evaluated for the anterior, inferior, and lateral walls in the basal, mid, and apical slices. A statistically significant reduction in myocardial (13)N-ammonia uptake in the anterior (P < 0.01) and lateral (P < 0.05) walls was observed when misregistration was 10 mm or more. The uptake ratios for the anterior, lateral, and inferior walls in the reference images were 1.00 ± 0.04, 0.96 ± 0.08, and 0.91 ± 0.03, respectively. The ratios for the anterior and lateral walls significantly decreased when misregistration exceeded 10 mm (anterior wall, 0.80 ± 0.06, P < 0.0001; lateral wall, 0.82 ± 0.07, P < 0.01), whereas the ratio for the inferior wall was relatively small at all 7 degrees of misregistration (0.86 ± 0.05 at 15-mm misregistration, P = 0.06). In PET/CT images reconstructed with 3D ordered-subset expectation maximization combined with time-of-flight and point-spread-function modeling, we found a statistically significant artifactual reduction in tracer uptake in heart regions overlapping lung when misregistration between PET and CT exceeded 10 mm.

Accuracy of Resolution Recovery in PSF-based Fully-3D PET Image Reconstruction: Simulation and Phantom Study in Multicenter Trial

Recently, the quality of positron emission tomography (PET) images has rapidly improved using resolution recovery algorithm with point spread function (PSF). The aim of this study was to investigate the accuracy of the resolution recovery algorithm using three different PET systems. Three PET scanner models, the GE Discovery 600 M (D600M), SIEMENS Biograph mCT (mCT), and SHIMADZU SET-3000GCT/X (3000GCT) were used in this study. The radial dependences of spatial resolution (full width at half maximum: FWHM) were obtained by point source measurements (0.9 mmφ). All PET data were acquired in three-dimensional (3D) mode and reconstructed using the filtered back projection (FBP) , 3D-ordered subsets expectation maximization (3D-OSEM or dynamic row-action maximum likelihood algorithm) , and 3D-OSEM+PSF (PSF) algorithms. Two indicators, aspect ratio (ASR) and resolution recovery ratio (RRR), were calculated from measured FWHMs and compared among the three PET scanners. In D600 and 3000GCT, distortions of the radial direction were slightly increased at circumference of field of view (FOV). On the other hand, random distortions were occurred in both radial and tangential direction in mCT. ASRs calculated from 3D-OSEM images at circumference of FOV were 2.06, 1.22, and 2.04 on D600M, mCT, and 3000GCT, respectively. ASR improved with PSF in all PET scanners. On the other hand, RRR with PSF were calculated 57.6%, 61.4%, and 31.6%, respectively. Our results suggest that the spatial resolutions of PET images could be improved with PSF algorithm in all PET systems; however, effect of PSF was different depending on PET systems. Furthermore, PSF algorithm could not completely improve spatial resolutions in circumference of FOV.

Performance of 3DOSEM and MAP algorithms for reconstructing low count SPECT acquisitions

PurposeLow count single photon emission computed tomography (SPECT) is becoming more important in view of whole body SPECT and reduction of radiation dose. In this study, we investigated the performance of several 3D ordered subset expectation maximization (3DOSEM) and maximum a posteriori (MAP) algorithms for reconstructing low count SPECT images. Materials and MethodsPhantom experiments were conducted using the National Electrical Manufacturers Association (NEMA) NU2 image quality (IQ) phantom. The background compartment of the phantom was filled with varying concentrations of pertechnetate and indiumchloride, simulating various clinical imaging conditions. Images were acquired using a hybrid SPECT/CT scanner and reconstructed with 3DOSEM and MAP reconstruction algorithms implemented in Siemens Syngo MI.SPECT (Flash3D) and Hermes Hybrid Recon Oncology (Hyrid Recon 3DOSEM and MAP). Image analysis was performed by calculating the contrast recovery coefficient (CRC),percentage background variability (N%), and contrast-to-noise ratio (CNR), defined as the ratio between CRC and N%. Furthermore, image distortion is characterized by calculating the aspect ratio (AR) of ellipses fitted to the hot spheres. Additionally, the performance of these algorithms to reconstruct clinical images was investigated. ResultsImages reconstructed with 3DOSEM algorithms demonstrated superior image quality in terms of contrast and resolution recovery when compared to images reconstructed with filtered-back-projection (FBP), OSEM and 2DOSEM. However, occurrence of correlated noise patterns and image distortions significantly deteriorated the quality of 3DOSEM reconstructed images. The mean AR for the 37, 28, 22, and 17mm spheres was 1.3, 1.3, 1.6, and 1.7 respectively. The mean N% increase in high and low count Flash3D and Hybrid Recon 3DOSEM from 5.9% and 4.0% to 11.1% and 9.0%, respectively. Similarly, the mean CNR decreased in high and low count Flash3D and Hybrid Recon 3DOSEM from 8.7 and 8.8 to 3.6 and 4.2, respectively. Regularization with smoothing priors could suppress these noise patterns at the cost of reduced image contrast. The mean N% was 6.4% and 6.8% for low count QSP and MRP MAP reconstructed images. Alternatively, regularization with an anatomical Bowhser prior resulted in sharp images with high contrast, limited image distortion, and low N% of 8.3% in low count images, although some image artifacts did occur. Analysis of clinical images suggested that the same effects occur in clinical imaging. ConclusionImage quality of low count SPECT acquisitions reconstructed with modern 3DOSEM algorithms is deteriorated by the occurrence of correlated noise patterns and image distortions. The artifacts observed in the phantom experiments can also occur in clinical imaging.

The association of tumor-to-background ratios and SUVmax deviations related to point spread function and time-of-flight F18-FDG-PET/CT reconstruction in colorectal liver metastases.

BackgroundThe maximum standardized uptake value (SUVmax) is a common clinical parameter for quantification in F18-fluorodeoxyglucose positron emission tomography/computed tomography (FDG-PET/CT), but it is influenced by image reconstruction. The aim of this study was to analyze the association of SUVmax deviations related to point spread function (PSF) and time-of-flight (TOF) reconstruction with tumor-to-background ratios (TBR) in colorectal liver metastases (CRLM).MethodsFifteen patients (f, 6; m, 9; median age, 59 years; range, 32 to 72 years) with 28 liver metastases were included retrospectively. FDG-PET/CT imaging (median activity, 237 MBq; range, 231 to 252 MBq; median uptake, 61 min; range, 55 to 67 min) was performed on a Siemens Biograph mCT 64 followed by image reconstruction using 3D-ordered subset expectation maximization (3D-OSEM) or 3D-OSEM with PSF modeling - both with and without TOF information. Differences in SUVmax were analyzed using the Friedman test and Wilcoxon test for paired non-parametric data. The correlation of inter-method differences with the lesions’ TBR was studied using Spearman’s rank correlation coefficient (rho). Differences between lesions with low (<4.8) and high (>4.8) TBR were analyzed using the Mann-Whitney U test (TBR measured with 3D-OSEM; binarized by its median).ResultsThere was a significant correlation of the lesions’ TBR with relative SUVmax differences related to PSF (PSF + TOF vs. 3D-OSEM + TOF, rho = 0.61; PSF vs. 3D-OSEM, rho = 0.52) or TOF (PSF + TOF vs. PSF, rho = −0.58; 3D-OSEM + TOF vs. 3D-OSEM, rho = −0.61). Accordingly, PSF algorithms only showed higher SUVmax than non-PSF algorithms in lesions with a high TBR (median differences at low/high TBR, +2.6%/+9.1% [PSF + TOF vs. 3D-OSEM + TOF]; +0.7%/+6.4% [PSF vs. 3D-OSEM]). TOF integration also led to higher SUVmax but mainly at low TBR (low/high TBR, +10.4%/+1.8% [PSF + TOF vs. PSF]; +8.6%/−0.1% [3D-OSEM + TOF vs. 3D-OSEM]).ConclusionsBoth PSF and TOF reconstruction resulted in a substantial alteration of SUVmax in CRLM. TOF provided the highest SUVmax increase in low-contrast lesions while - vice versa - PSF showed the most relevant increase in high-contrast lesions. Thus, one should be aware that quantitative analyses of lesions with varying TBR, e.g., in radiotherapy or follow-up studies, may be mainly affected by either PSF or TOF reconstruction, respectively.

A Monte Carlo study of the dependence of early frame sampling on uncertainty and bias in pharmacokinetic parameters from dynamic PET.

Compartmental modeling of dynamic PET data enables quantification of tracer kinetics in vivo, through the calculated model parameters. In this study, we aimed to investigate the effect of early frame sampling and reconstruction method on pharmacokinetic parameters obtained from a 2-tissue model, in terms of bias and uncertainty (SD). The GATE Monte Carlo software was used to simulate 2 × 15 dynamic 3'-deoxy-3'-(18)F-fluorothymidine ((18)F-FLT) brain PET studies, typical in terms of noise level and kinetic parameters. The data were reconstructed by both 3-dimensional (3D) filtered backprojection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM) into 6 dynamic image sets with different early frame durations of 1, 2, 4, 6, 10, and 15 s. Bias and SD were evaluated for fitted parameter estimates, calculated from regions of interest. The 2-tissue-model parameter estimates K1, k2, and fraction of arterial blood in tissue depended on early frame sampling, and a sampling of 6-15 s generally minimized bias and SD. The shortest sampling of 1 s yielded a 25% and 42% larger bias than the other schemes, for 3DRP and OSEM, respectively, and a parameter uncertainty that was 10%-70% higher. The schemes from 4 to 15 s were generally not significantly different in regards to bias and SD. Typically, the reconstruction method 3DRP yielded less frame-sampling dependence and less uncertain results, compared with OSEM, but was on average more biased. Of the 6 sampling schemes investigated in this study, an early frame duration of 6-15 s generally kept both bias and uncertainty to a minimum, for both 3DRP and OSEM reconstructions. Very-short frames of 1 s should be avoided because they typically resulted in the largest parameter bias and uncertainty. Furthermore, 3DRP may be preferred over OSEM for short frames with poor statistics.

Quantitative and qualitative assessment of Yttrium-90 PET/CT imaging.

Yttrium-90 is known to have a low positron emission decay of 32 ppm that may allow for personalized dosimetry of liver cancer therapy with 90Y labeled microspheres. The aim of this work was to image and quantify 90Y so that accurate predictions of the absorbed dose can be made. The measurements were performed within the QUEST study (University of Sydney, and Sirtex Medical, Australia). A NEMA IEC body phantom containing 6 fillable spheres (10–37 mm ∅) was used to measure the 90Y distribution with a Biograph mCT PET/CT (Siemens, Erlangen, Germany) with time-of-flight (TOF) acquisition. A sphere to background ratio of 8∶1, with a total 90Y activity of 3 GBq was used. Measurements were performed for one week (0, 3, 5 and 7 d). he acquisition protocol consisted of 30 min-2 bed positions and 120 min-single bed position. mages were reconstructed with 3D ordered subset expectation maximization (OSEM) and point spread function (PSF) for iteration numbers of 1–12 with 21 (TOF) and 24 (non-TOF) subsets and CT based attenuation and scatter correction. Convergence of algorithms and activity recovery was assessed based on regions-of-interest (ROI) analysis of the background (100 voxels), spheres (4 voxels) and the central low density insert (25 voxels). For the largest sphere, the recovery coefficient (RC) values for the 30 min –2-bed position, 30 min-single bed and 120 min-single bed were 1.12±0.20, 1.14±0.13, 0.97±0.07 respectively. For the smaller diameter spheres, the PSF algorithm with TOF and single bed acquisition provided a comparatively better activity recovery. Quantification of Y-90 using Biograph mCT PET/CT is possible with a reasonable accuracy, the limitations being the size of the lesion and the activity concentration present. At this stage, based on our study, it seems advantageous to use different protocols depending on the size of the lesion.

Compartment modeling of dynamic brain PET--the impact of scatter corrections on parameter errors.

The aim of this study was to investigate the effect of scatter and its correction on kinetic parameters in dynamic brain positron emission tomography (PET) tumor imaging. The 2-tissue compartment model was used, and two different reconstruction methods and two scatter correction (SC) schemes were investigated. The gate Monte Carlo (MC) software was used to perform 2 × 15 full PET scan simulations of a voxelized head phantom with inserted tumor regions. The two sets of kinetic parameters of all tissues were chosen to represent the 2-tissue compartment model for the tracer 3'-deoxy-3'-((18)F)fluorothymidine (FLT), and were denoted FLT1 and FLT2. PET data were reconstructed with both 3D filtered back-projection with reprojection (3DRP) and 3D ordered-subset expectation maximization (OSEM). Images including true coincidences with attenuation correction (AC) and true+scattered coincidences with AC and with and without one of two applied SC schemes were reconstructed. Kinetic parameters were estimated by weighted nonlinear least squares fitting of image derived time-activity curves. Calculated parameters were compared to the true input to the MC simulations. The relative parameter biases for scatter-eliminated data were 15%, 16%, 4%, 30%, 9%, and 7% (FLT1) and 13%, 6%, 1%, 46%, 12%, and 8% (FLT2) for K1, k2, k3, k4, Va, and Ki, respectively. As expected, SC was essential for most parameters since omitting it increased biases by 10 percentage points on average. SC was not found necessary for the estimation of Ki and k3, however. There was no significant difference in parameter biases between the two investigated SC schemes or from parameter biases from scatter-eliminated PET data. Furthermore, neither 3DRP nor OSEM yielded the smallest parameter biases consistently although there was a slight favor for 3DRP which produced less biased k3 and Ki estimates while OSEM resulted in a less biased Va. The uncertainty in OSEM parameters was about 26% (FLT1) and 12% (FLT2) larger than for 3DRP although identical postfilters were applied. SC was important for good parameter estimations. Both investigated SC schemes performed equally well on average and properly corrected for the scattered radiation, without introducing further bias. Furthermore, 3DRP was slightly favorable over OSEM in terms of kinetic parameter biases and SDs.