Quantification and reduction of the collimator-detector response effect in SPECT by applying a system model during iterative image reconstruction

This work is aimed at evaluating the image reconstruction techniques used in single photon emission computed tomography (SPECT/CT) imaging. The reconstruction techniques considered in this work are: the ordered subset expectation maximization (OSEM) and the Filtered Back Projection (FBP). An anthropomorphic torso phantom with lung and liver inserts was injected with 99mTc. The liver and the background were given 0.2 MBq/ml and 0.07 MBq/ml respectively. The lungs inserts were filled with polystyrene beads for humanization. A mimicked 30 ml tumor (27 mm) in the liver insert was given 2 MBq/ml sequential SPECT/CT (step and shot, 10 mins over 180° per head) and CT (120 kVp, 80 mAs) projections were acquired using dual head SPECT/16 slice CT system. The projections were reconstructed using OSEM (10 subsets for 2–10 numbers of iterations, Butterworth post filtering, 10 orders and 0.48 frequencies) and FBP (using Butterworth post filtering at 10 order and cutoff frequencies of 0.38–0.58, 0.05 gaps). Image J software was used for the image analysis. Statistical t-test tested the mean gray values of the tumor and its background. The OSEM and FBP reconstructed images were evaluated from their contrast-to-noise ratio (CNR). The optimal parameter was selected based on 3–5 CNR detection range set by the Rose criterion. The t-test showed the background and the tumors mean values to be statistically significant (P ≪ 0.05). The CNR values for FBP images were all below the detection range, maximum value at the cutoff frequency 0.48 (1.69). In OSEM images at cutoff frequency 0.48, the CNR values were within the detection range for 2–8 numbers of iteration with maximum value (4.89) at 4 numbers of iteration. OSEM was found to be the best for tumor detection and administered activity can be reduced at 4 OSEM’s of iterations (40 MLEM iterations) for patient safety. Keywords: Anthropomorphic torso phantom, 99mTc, SPECT, iterative reconstruction, CNR, P-Value, liver Cite this Article F. Usman, R. Zainon, A. Saidu, A. Bala. Evaluation of image reconstruction techniques in Single photon emission computed tomography (SPECT/CT) imaging. Research & Reviews: Journal of Physics. 2016; 5(2): 13–22p.

Myocardial perfusion single photon emission computed tomography (SPECT) is typically subject to a variation in image quality due to the use of different acquisition protocols, image reconstruction parameters and image display settings by each institution. One of the principal image reconstruction parameters is the Butterworth filter cut-off frequency, a parameter strongly affecting the quality of myocardial images. The objective of this study was to formulate a flowchart for the determination of the optimal parameters of the Butterworth filter for filtered back projection (FBP), ordered subset expectation maximization (OSEM) and collimator-detector response compensation OSEM (CDR-OSEM) methods using the evaluation system of the myocardial image based on technical grounds phantom. SPECT studies were acquired for seven simulated defects where the average counts of the normal myocardial components of 45° left anterior oblique projections were approximately 10-120counts/pixel. These SPECT images were then reconstructed by FBP, OSEM and CDR-OSEM methods. Visual and quantitative assessment of short axis images were performed for the defect and normal parts. Finally, we formulated a flowchart indicating the optimal image processing procedure for SPECT images. Correlation between normal myocardial counts and the optimal cut-off frequency could be represented as a regression expression, which had high or medium coefficient of determination. We formulated the flowchart in order to optimize the image reconstruction parameters based on a comprehensive assessment, which enabled us to perform objectively processing. Furthermore, the usefulness of image reconstruction using the flowchart was demonstrated by a clinical case.

Single photon emission computed tomography (SPECT) has limited ability to identify multivessel and microvascular coronary artery disease. Gamma cameras with cadmium zinc telluride detectors allow the quantification of absolute myocardial blood flow (MBF) and myocardial flow reserve (MFR). However, evidence of its accuracy is limited, and of its reproducibility is lacking. We aimed to validate 99mTc-sestamibi SPECT MBF and MFR using standard and spline-fitted reconstruction algorithms compared with 13N-ammonia positron emission tomography in a cohort of patients with known or suspected coronary artery disease and to evaluate the reproducibility of this technique. Accuracy was assessed in 34 participants who underwent dynamic 99mTc-sestamibi SPECT and 13N-ammonia positron emission tomography and reproducibility in 14 participants who underwent 2 99mTc-sestamibi SPECT studies, all within 2 weeks. A rest/pharmacological stress single-day SPECT protocol was performed. SPECT images were reconstructed using a standard ordered subset expectation maximization (OSEM) algorithm with (N=21) and without (N=30) application of spline fitting. SPECT MBF was quantified using a net retention kinetic model' and MFR was derived as the stress/rest MBF ratio. SPECT global MBF with splines showed good correlation with 13N-ammonia positron emission tomography (r=0.81, P<0.001) and MFR estimates (r=0.74, P<0.001). Correlations were substantially weaker for standard reconstruction without splines (r=0.61, P<0.001 and r=0.34, P=0.07, for MBF and MFR, respectively). Reproducibility of global MBF estimates with splines in paired SPECT scans was good (r=0.77, P<0.001), while ordered subset expectation maximization without splines led to decreased MBF (r=0.68, P<0.001) and MFR correlations (r=0.33, P=0.3). There were no significant differences in MBF or MFR between the 2 reproducibility scans independently of the reconstruction algorithm (P>0.05 for all). MBF and MFR quantification using 99mTc-sestamibi cadmium zinc telluride SPECT with spatiotemporal spline fitting improved the correlation with 13N-ammonia positron emission tomography flow estimates and test/retest reproducibility. The use of splines may represent an important step toward the standardization of SPECT flow estimation.

BackgroundRespiratory motion compromises image quality in myocardial perfusion (MP) single-photon emission computed tomography (SPECT) imaging and may affect analysis of left ventricular (LV) functional parameters, including phase analysis-quantified mechanical dyssynchrony parameters. In this paper, we investigate the performance of two algorithms, respiratory blur modeling (RBM) and joint motion-compensated (JMC) ordered-subsets expectation maximization (OSEM), and the effects of motion compensation on cardiac-gated MP-SPECT studies.MethodsImage acquisitions were carried out with a dual-detector SPECT/CT system in list-mode format. A cardiac phantom was imaged as stationary and under respiratory motion. The images were reconstructed with OSEM, RBM-OSEM, and JMC-OSEM algorithms, and compared in terms of mean squared error (MSE). Subsequently, MP-SPECT data of 19 patients were binned into dual-gated (respiratory and cardiac gating) projection images. The images of the patients were analyzed with Quantitative Gated SPECT (QGS) 2012 program (Cedars-Sinai Medical Center, USA). The parameters of interest were LV volumes, ejection fraction, wall motion, wall thickening, phase analysis, and perfusion parameters.ResultsIn phantom experiment, compared to the stationary OSEM reconstruction, the MSE values for OSEM, RBM-OSEM, and JMC-OSEM were 8.5406·10−5,2.7190·10−5, and 2.0795·10−5, respectively. In the analysis of LV function, use of JMC had a small but statistically significant (p < 0.05) effect on several parameters: it increased LV volumes and standard deviation of phase angle histogram, and it decreased ejection fraction, global wall motion, and lateral, septal, and apical perfusion.ConclusionsCompared to standard OSEM algorithm, RBM-OSEM and JMC-OSEM both improve image quality under motion. Motion compensation has a minor effect on LV functional parameters.

Due to low counts in an 111In single photon emission computed tomography (SPECT) scan, a large part of the head was missing in the reconstructed images on Philips Extended Brilliance Workspace (EBW) and IntelliSpace Portal (ISP) workstations. This problem occurred for the ordered subsets expectation maximization (OSEM) algorithm with and without resolution recovery (Astonish), but not for filtered backprojection (FBP) or maximum likelihood expectation maximization (MLEM). There were also underflow problems because the images are stored as integers resulting in a loss of intensity resolution and color banding.Philips EBW2.0 and ISP5.02 workstations upscale low-count images, but the result is not always optimal, for example, in the case of low counts in one part and more counts in another part of an image. On these workstations, the missing head artefact problem could be resolved by applying a Hann pre-filter (with a cutoff at the Nyquist frequency, which only influences the filtering) in the reconstruction process. Upscaling of the projection data prior to reconstruction did not recover the head in the images, neither did limiting the reconstructed volume to the low-count part of interest.Underflow problems were partially solved by the new version 2.0 of the Philips EBW and ISP stations, although situations could arise where underflow still poses a problem. A solution for the underflow problems is to upscale the raw projection data before reconstruction. While this results in a pure upscaling of the FBP reconstruction, the effect in iterative statistical reconstruction is not only upscaling of the intensities because the assumption of Poisson statistics of the data is violated. However, the influence of this last matter seems limited.Reconstruction of studies with low counts in relevant areas should be performed with care. Reconstruction artefacts and scaling issues can easily arise.Electronic supplementary materialThe online version of this article (doi:10.1186/2197-7364-1-10) contains supplementary material, which is available to authorized users.

The purpose of this study was to evaluate the diagnostic value of attenuation-corrected single photon emission computed tomography (SPECT) myocardial perfusion imaging (MPI) on the inferior wall compared to uncorrected (NC) SPECT MPI between obese and nonobese patients. A total of 157 consecutive patients (122 males and 35 females, with median age: 57.4 ± 11 years) who underwent AC technetium 99m-methoxyisobutylisonitrile (AC Tc99m-sestamibi) SPECT MPI were included to the study. A hybrid SPECT and transmission computed tomography (CT) system was used for the diagnosis with 1-day protocol, and stress imaging was performed first. During attenuation correction (AC) processing on a Xeleris Workstation using Myovation cardiac software with ordered subset expectation maximization (OSEM), iterative reconstruction with attenuation correction (IRAC) and NC images filtered back projection (FBP) were used. For statistical purposes, P < 0.05 was considered significant. This study included 73 patients with body mass index (BMI) <30 and 84 patients with BMI ≥ 30. In patients with higher BMI, increased amount of both visual and semiquantitative attenuation of the inferior wall was detected. IRAC reconstruction corrects the diaphragm attenuation of the inferior wall better than FBP. AC with OSEM iterative reconstruction significantly improves the diagnostic value of stress-only SPECT MPI in patients with normal weight and those who are obese, but the improvements are significantly greater in obese patients. Stress-only SPECT imaging with AC provides shorter and lower radiation exposure.

The degradation of image quality caused by respiration is a major impediment to accurate lesion detection in single photon emission computed tomography (SPECT) imaging. This study was performed to evaluate the effects of lung motion on image quantification. A small animal SPECT system with NaI(Tl) was modeled in the Geant4 application for tomographic emission (GATE) simulation for a lung lesion using a 4D mouse whole-body phantom. SPECT images were obtained using 120 projection views acquired from 0o to 360o with a 3o step. Slices were reconstructed using ordered subsets expectation maximization (OS-EM) without attenuation correction with five iterations and four subsets. Image quality was compared between the static mode without respiratory motion, and dynamic mode with respiratory motion in terms of spatial resolution was measured by the full width at half maximum (FWHM), signal-to-noise ratio (SNR), and contrast-to-noise ratio (CNR). The FWHM of the non-gated image and the respiratory gated image were also compared. Spatial resolution improved as activity increased and lesion diameter decreased in the static and dynamic modes. The SNR and CNR increased significantly as lesion activity increased and lesion diameter decreased. Our results show that respiratory motion leads to reduced contrast and quantitative accuracy and that image quantification depends on both the amplitude and the pattern of the respiratory motion. We verified that respiratory motion can have a major effect on the accuracy of measurement of lung lesions and that respiratory gating can reduce activity smearing on SPECT images.

Single-photon emission computed tomography (SPECT) is a method of choice for imaging spatial distributions of radioisotopes. Applications of this method are found in medicine, biomedical research and nuclear industry. This paper deals with improving spatial resolution in SPECT by applying correction for the point-spread function (PSF) in the reconstruction algorithm and optimizing the collimator. Several approaches are considered: the use of a depth-dependent PSF model for a parallel-beam collimator derived from experimental data, the extension of this model to a fan-beam collimator, a triangular approximation of the PSF for reconstruction acceleration, and a method for optimal fan-beam collimator design. An unmatched projector/backprojector ordered subsets expectation maximization (OSEM) algorithm is used for image reconstruction. Experimental results with simulated and physical phantom data of a micro-SPECT system show a significant improvement of spatial resolution with the proposed methods.

Although xSPECT Bone (xB) provides quantitative single-photon emission computed tomography (SPECT) high-resolution images, patients' burden remains high due to long acquisition time; therefore, this study aimed to investigate the feasibility of shortening the xB acquisition time using a custom-designed phantom. A custom-designed xSPECT bone-specific (xSB) phantom with simulated cortical and spongious bones was developed based on the thoracic bone phantom. Both standard- and ultra-high-speed (UHS) xB acquisitions were performed in a male patient with lung cancer. In this phantom study, SPECT was acquired for 3, 6, 9, 12, and 30min. The clinical SPECT acquisition time per rotation was 9 and 3min for standard and UHS, respectively. SPECT images were reconstructed using ordered subset expectation maximization with three-dimensional resolution recovery (Flash3D; F3D) and xB algorithms. Quantitative SPECT value (QSV) and coefficient of variation (CV) were measured using the volume of interests (VOIs) placed at the center of the vertebral body and hot sphere. A linear profile was plotted on the spinous process at the center of the xSB phantom; then, the full width at half maximum (FWHM) was measured. The standardized uptake value (SUV) and standard deviation from the first thoracic to the fifth lumbar vertebrae in clinical standard- and UHS-xB images were measured using a 1-cm3 VOI. The QSV of F3D images was underestimated even in large regions, whereas those of xB images were close to actual radioactivity concentration. The CV was similar or lower for xB images than that for F3D images but was not decreased with increasing acquisition time for both reconstruction images. The FWHM of xB images was lower than those of F3D images at all acquisition times. The mean SUV values from the first thoracic to fifth lumbar vertebrae for standard- and UHS-xB images were 6.73 ± 0.64 and 6.19 ± 0.87, respectively, showing a strong positive correlation. Results of this phantom study suggest that xB imaging can be obtained in only one-third of the acquisition time without compromising the image quality. The SUV of UHS-xB images can be similar to that of standard-xB images in terms of clinical interpretation.

PurposeA 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.MethodsThe 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‐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.ResultsThe 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.ConclusionsWe 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.

BackgroundHybrid imaging combines nuclear medicine imaging such as single photon emission computed tomography (SPECT) or positron emission tomography (PET) with computed tomography (CT). Through this hybrid design, scanned patients accumulate radiation exposure from both applications. Imaging modalities have been the subject of long-term optimization efforts, focusing on diagnostic applications. It was the aim of this study to investigate the influence of an iterative CT image reconstruction algorithm (ASIR) on the image quality of the low-dose CT images.Methodology/Principal FindingsExaminations were performed with a SPECT-CT scanner with standardized CT and SPECT-phantom geometries and CT protocols with systematically reduced X-ray tube currents. Analyses included image quality with respect to photon flux. Results were compared to the standard FBP reconstructed images. The general impact of the CT-based attenuation maps used during SPECT reconstruction was examined for two SPECT phantoms. Using ASIR for image reconstructions, image noise was reduced compared to FBP reconstructions for the same X-ray tube current. The Hounsfield unit (HU) values reconstructed by ASIR were correlated to the FBP HU values(R2 ≥ 0.88) and the contrast-to-noise ratio (CNR) was improved by ASIR. However, for a phantom with increased attenuation, the HU values shifted for low X-ray tube currents I ≤ 60 mA (p ≤ 0.04). In addition, the shift of the HU values was observed within the attenuation corrected SPECT images for very low X-ray tube currents (I ≤ 20 mA, p ≤ 0.001).Conclusion/SignificanceIn general, the decrease in X-ray tube current up to 30 mA in combination with ASIR led to a reduction of CT-related radiation exposure without a significant decrease in image quality.

A single photon emission computed tomography (SPECT) system with a co-registered X-y computed tomography (CT) system allows the convergence of functional information and morphologic information. The localization of radiopharmaceuticals on a SPECT can be enhanced by combining the SPECT with an anatomical modality, such as X-ray CT. Gamma-ray imaging for nuclear medicine devices and X-ray imaging systems for diagnostics has recently been developed based on semiconductor detectors, and semiconductor detector materials such as cadmium telluride (CdTe) or cadmium zinc telluride (CZT) are available for both X-ray and gamma-ray systems for small-animal imaging. CdTe or CZT detectors provide strong absorption and high detection efficiency of high energy X-ray and gamma-ray photons because of their large atomic numbers. In this study, a pinhole collimator SPECT system sharing a cadmium telluride (CdTe) detector with a CT was designed. The GEANT4 application for tomographic emission (GATE) v.6.1 was used for the simulation. The pinhole collimator was designed to obtain a high spatial resolution of the SPECT system. The acquisition time for each projection was 40 seconds, and 60 projections were obtained for tomographic image acquisition. The reconstruction was performed using ordered subset expectation maximization (OS-EM) algorithms. The sensitivity and the spatial resolution were measured on the GATE simulation to evaluate the system characteristics. The spatial resolution of the system calculated from the FWHM of Gaussian fitted PSF curve was 0.69 mm, and the sensitivity of the system was measured to be 0.354 cps/kBq by using a Tc-99m point source of 1 MBq for 800 seconds. A phantom study was performed to verify the design of the dual imaging modality system. The system will be built as designed, and it can be applied as a pre-clinical imaging system.

The Bayesian penalized likelihood (BPL) reconstruction algorithm, Q.Clear, can achieve a higher signal-to-noise ratio on images and more accurate quantitation than ordered subset-expectation maximization (OSEM). The reconstruction parameter (β) in BPL requires optimization according to the radiopharmaceutical tracer. The present study aimed to define the optimal β value in BPL required to diagnose Alzheimer disease from brain positron emission tomography (PET) images acquired using 18 F-fluoro-2-deoxy-D-glucose ([18 F]FDG) and 11 C-labeled Pittsburg compound B ([11 C]PiB). Images generated from Hoffman 3D brain and cylindrical phantoms were acquired using a Discovery PET/computed tomography (CT) 710 and reconstructed using OSEM+time-of-flight (TOF) under clinical conditions and BPL+TOF (β=20-1000). Contrast was calculated from images generated by the Hoffman 3D brain phantom, and noise and uniformity were calculated from those generated by the cylindrical phantom. Five cognitively healthy controls and five patients with Alzheimer disease were assessed using [18 F]FDG and [11 C]PiB PET to validate the findings from the phantom study. The β values were restricted by the findings of the phantom study, then one certified nuclear medicine physician and two certified nuclear medicine technologists visually determined optimal β values by scoring the quality parameters of image contrast, image noise, cerebellar stability, and overall image quality of PET images from 1 (poor) to 5 (excellent). The contrast in BPL satisfied the Japanese Society of Nuclear Medicine (JSNM) criterion of ≥55% and exceeded that of OSEM at ranges of β=20-450 and 20-600 for [18 F]FDG and [11 C]PiB, respectively. The image noise in BPL satisfied the JSNM criterion of ≤15% and was below that in OSEM when β=150-1000 and 400-1000 for [18 F]FDG and [11 C]PiB, respectively. The phantom study restricted the ranges of β values to 100-300 and 300-500 for [18 F]FDG and [11 C]PiB, respectively. The BPL scores for gray-white matter contrast and image noise, exceeded those of OSEM in [18 F]FDG and [11 C]PiB images regardless of β values. Visual evaluation confirmed that the optimal β values were 200 and 450 for [18 F]FDG and [11 C]PiB, respectively. The BPL achieved better image contrast and less image noise than OSEM, while maintaining quantitative standardized uptake value ratios (SUVR) due to full convergence, more rigorous noise control, and edge preservation. The optimal β values for [18 F]FDG and [11 C]PiB brain PET were apparently 200 and 450, respectively. The present study provides useful information about how to determine optimal β values in BPL for brain PET imaging.

Introduction: PET/CT and PET/MRI are valuable multimodality imaging techniques for visualizing both functional and anatomical information. The most used PET reconstruction algorithm is Ordered Subset Expectation Maximization (OSEM). In OSEM, the image noise increases with increased number of iterations, and the reconstruction needs to be stopped before complete convergence. The Bayesian penalized likelihood (BPL) algorithm, recently introduced, uses a noise penalty factor (β) to achieve full convergence while controlling noise. This study aims to evaluate how reconstruction algorithms and lesion radioactivity levels affect PET image quality and quantitative accuracy across three different PET systems. Materials and Methods: A NEMA phantom was filled with 18F and scanned by one PET/MRI and two PET/CT systems with sphere-to-background concentration ratio (SBR) of 2:1, 4:1, or 10:1. PET images were reconstructed with OSEM or BPL with TOF. The number of iterations and β-values were varied, while the matrix size, number of subsets, and filter size remained constant. Contrast recovery (CR) and background variability (BV) were measured in images. Results: CR increased with increased sphere size and SBR. CR and BV decreased with increased β for the 10mm sphere. Increased number of iterations in OSEM showed increased BV with limited variation in CR. BPL gave higher CR and lower BV values than OSEM. The optimal reconstruction was BPL with β between 150 and 350, where BPL was available, and OSEM with two iterations and 21 subsets for the PET/CT without BPL. Conclusion: BPL outperforms OSEM, and SBR significantly influences tracer uptake quantification in small lesions. Future studies should explore the clinical implications of these findings on diagnosis, staging, prognosis, and treatment follow-up.

Low spatial resolution and the related partial volume effects limit the diagnostic potential of brain single photon emission computed tomography (SPECT) imaging. As a possible remedy for this problem we propose a technique for the fusion of SPECT and MR images, which requires for a given patient the SPECT data and the T1-weighted MR image. Basically, after the reconstruction and coregistration steps, the high-frequency part of the MR, which would be unrecoverable by the set SPECT acquisition system + reconstruction algorithm, is extracted and added to the SPECT image. The tuning of the weight of the MR on the resulting fused image can be performed very quickly, any iterative reconstruction algorithm can be used and, in the case that the SPECT projections are not available, the proposed technique can also be applied directly to the SPECT image, provided that the performance of the scanner is known. The procedure has the potential of increasing the diagnostic value of a SPECT image. Even in the locations of SPECT-MR mismatch it does not significantly affect quantitation over regions of interest (ROIs) whose dimensions are decidedly larger than the SPECT resolution distance. On the other hand, appreciable corrections for partial volume effects are expected in the locations where the contrast in the structural MR matches the corresponding contrast in functional activity.