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

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

Iterative reconstruction with correction of the spatially variant fan-beam collimator response in neurotransmission SPET imaging

The dopamine transporter (DAT) has been shown to be a sensitive indicator of nigrostriatal dopamine function. Although visual inspection is often sufficient to assess DAT imaging, quantification could improve the diagnostic accuracy of single-photon emission tomography (SPET) studies of the dopaminergic system. The aim of this study was to assess the accuracy of quantification of the striatal/background uptake ratio when correction for attenuation, scatter and spatially variant fan-beam collimator response is performed in technetium-99m and iodine-123 SPET imaging. A numerical striatal phantom was implemented, and simulated projections of low-energy photons were obtained by using the SimSET Monte Carlo code. High-energy contamination in ¹²³I studies was modelled from experimental measurements with ^99mTc and ¹²³I. The ordered subsets expectation maximisation (OSEM) algorithm was employed in reconstruction. Mean improvements of 8% and 16% were obtained in the calculated striatal/background uptake ratio in the putamen and the caudate, respectively, when the spatially variant point spread function was included in the transition matrix. Ideal scatter correction resulted in improvements in the putamen and caudate of 9% for ^99mTc agents and 19% for ¹²³I agents. Improvements averaged 31% in the putamen and 43% in the caudate when correction for attenuation, scatter and spatially variant collimator response was included in the reconstruction.     

Reconstruction of gated myocardial perfusion SPET incorporating temporal information during iterative reconstruction

Reconstruction of gated single-photon emission tomography (gSPET) is intrinsically a four-dimensional (4D) problem. In practice, the time frames are reconstructed independently as a sequence of frame-by-frame reconstructions. This approach is not optimal since the strong signal correlations among the individual time frames are not exploited. In this study we propose a simple but efficient algorithm to improve the image quality of myocardial perfusion gSPET by incorporating the cyclic temporal information within the reconstruction using Fourier filtering. The gSPET images were reconstructed using the Ordered Subsets Expectation Maximisation (OSEM) algorithm employing six iterations with eight subsets. Temporal filtering was applied either before (PreOSEM) or after image reconstruction (PostOSEM) or was incorporated within the OSEM algorithm (OSEM4D). The effect of temporal filtering was compared with conventional frame-by-frame OSEM using clinical data. Image quality was evaluated by estimating the systematic and statistical error. The results indicated that temporal filtering introduces a small (<1%) systematic error, while the statistical error was reduced from 15.0%+/-3.1% when conventional frame-by-frame OSEM was applied to 12.6%+/-2.7%, 12.0%+/-2.5% and 9.3%+/-2.4% when PreOSEM, PostOSEM and OSEM4D were used, respectively. It is concluded that temporal filtering incorporated within OSEM reconstruction dramatically reduces noise in gated SPET myocardial images.     

Correction for respiration artefacts in myocardial perfusion SPECT is more effective when reconstructions supporting collimator detector response compensation are applied

Purpose  

To assess the impact of respiration on myocardial perfusion imaging (MPI) SPECT processed with advanced algorithmic reconstructions.     

Comparative analysis of iterative reconstruction algorithms with resolution recovery for cardiac SPECT studies. A multi-center phantom study

Background

This investigation used image data generated by a physical phantom over a wide range of count statistics to evaluate the effectiveness of several of the newer commercially available SPECT reconstruction iterative algorithms (IRR) in improving perfusion defect contrast and spatial resolution, while controlling image noise.

Methods

A cardiac phantom was imaged using four different gamma cameras over a wide range of counts statistics (from 6 to 0.8 Mcounts). Images were reconstructed with FBP, OSEM, and the IRR available on site. IRR were applied without corrections (IRR NC), with attenuation correction (IRR AC), scatter correction (IRR SC), and attenuation + scatter corrections (IRR SCAC). Four image performance indices related to spatial resolution, contrast, and image noise were analyzed.

Results

IRR NC always determined significant improvements in all indices in comparison to FBP or OSEM. Improvements were emphasized with IRR SC and IRR SCAC. Count reduction from 6 to 1.5 Mcounts did not impair the performances of any of the considered indices.

Conclusions

This is the first study comparing the relative performance of different, commercially available, IRR software, over a wide range of count statistics; the additional effect of scatter and attenuation corrections, alone or in combination, was also evaluated. Our results confirm that IRR algorithms produce substantial benefits with respect to conventional FBP or OSEM reconstruction methods, as assessed through different figures of merit, in particular when SC and/or SCAC are also included.     

The influence of resolution recovery by using collimator detector response during 3D OSEM image reconstruction on (99m)Tc-ECD brain SPET images

Partial volume effect, due to the poor spatial resolution of single photon emission tomography (SPET), significantly restricts the absolute quantification of the regional brain uptake and limits the accuracy of the absolute measurement of blood flow. In this study the importance of compensation for the collimator-detector response (CDR) in the technetium-99m ethyl cysteinate dimer ((99m)Tc-ECD) brain SPET was assessed, by incorporating system response in the ordered-subsets expectation maximization (OSEM) reconstruction algorithm. By placing a point source of (99m)Tc at different distances from the face of the collimator, CDR were found and modeled using Gaussian functions. A fillable slice of the brain phantom was designed and filled by (99m)Tc. Projections acquired from the phantom and also 4 patients who underwent the (99m)Tc-ECD brain SPET were used in this study. To reconstruct the images, 3D OSEM algorithm was used. System blurring functions were modeled, during the reconstruction in both projection and backprojection steps. Our results were compared with the conventional resolution recovery using Metz filter in filtered backprojection (FBP). Visual inspection of the images was performed by six nuclear medicine specialists. Quantitative analysis was also studied by calculating the contrast and the count density of the reconstructed images. For the phantom images, background counts and noise were decreased by 3D OSEM compared to the FBP-Metz method. Quantitatively, the ratio of the counts of the occupied hot region to that of the cold region of the reconstructed by FBP-Metz images was 1.14. This value was decreased from 1.12 to 0.86 for 3D OSEM of 2 and 30 iterations respectively. The reference value was 0.85 for the planar image. For clinical images, hot to cold regions (grey to white matter), the count ratio was increased from 1.44 in FBP-Metz to 3.2 and 4 in 3D OSEM with 10 and 20 iterations respectively. Based on the interpretability of images, the best scores (3.79±0.51) by the physicians were given to the images reconstructed by 3D OSEM and 10 iterations. This value was 0.63±0.77 for FBP-Metz images. In conclusion, by incorporating the distance dependent CDR during 3D OSEM, it was possible to reconstruct the brain images with much higher resolution and contrast as compared to the conventional resolution recovery method, which used FBP-Metz. It was however important to make a trade-off between noise and resolution by determining an optimum iterations number.     

Improvement of brain perfusion SPET using iterative reconstruction with scatter and non-uniform attenuation correction

Filtered back-projection (FBP) is generally used as the reconstruction method for single-photon emission tomography although it produces noisy images with apparent streak artefacts. It is possible to improve the image quality by using an algorithm with iterative correction steps. The iterative reconstruction technique also has an additional benefit in that computation of attenuation correction can be included in the process. A commonly used iterative method, maximum-likelihood expectation maximisation (ML-EM), can be accelerated using ordered subsets (OS-EM). We have applied to the OS-EM algorithm a Bayesian one-step late correction method utilising median root prior (MRP). Methodological comparison was performed by means of measurements obtained with a brain perfusion phantom and using patient data. The aim of this work was to quantitate the accuracy of iterative reconstruction with scatter and non-uniform attenuation corrections and post-filtering in SPET brain perfusion imaging. SPET imaging was performed using a triple-head gamma camera with fan-beam collimators. Transmission and emission scans were acquired simultaneously. The brain phantom used was a high-resolution three-dimensional anthropomorphic JB003 phantom. Patient studies were performed in ten chronic pain syndrome patients. The images were reconstructed using conventional FBP and iterative OS-EM and MRP techniques including scatter and non-uniform attenuation corrections. Iterative reconstructions were individually post-filtered. The quantitative results obtained with the brain perfusion phantom were compared with the known actual contrast ratios. The calculated difference from the true values was largest with the FBP method; iteratively reconstructed images proved closer to the reality. Similar findings were obtained in the patient studies. The plain OS-EM method improved the contrast whereas in the case of the MRP technique the improvement in contrast was not so evident with post-filtering.     

Improvement of brain perfusion SPET using iterative reconstruction with scatter and non-uniform attenuation correction

Filtered back-projection (FBP) is generally used as the reconstruction method for single-photon emission tomography although it produces noisy images with apparent streak artefacts. It is possible to improve the image quality by using an algorithm with iterative correction steps. The iterative reconstruction technique also has an additional benefit in that computation of attenuation correction can be included in the process. A commonly used iterative method, maximum-likelihood expectation maximisation (ML-EM), can be accelerated using ordered subsets (OS-EM). We have applied to the OS-EM algorithm a Bayesian one-step late correction method utilising median root prior (MRP). Methodological comparison was performed by means of measurements obtained with a brain perfusion phantom and using patient data. The aim of this work was to quantitate the accuracy of iterative reconstruction with scatter and non-uniform attenuation corrections and post-filtering in SPET brain perfusion imaging. SPET imaging was performed using a triple-head gamma camera with fan-beam collimators. Transmission and emission scans were acquired simultaneously. The brain phantom used was a high-resolution three-dimensional anthropomorphic JB003 phantom. Patient studies were performed in ten chronic pain syndrome patients. The images were reconstructed using conventional FBP and iterative OS-EM and MRP techniques including scatter and nonuniform attenuation corrections. Iterative reconstructions were individually post-filtered. The quantitative results obtained with the brain perfusion phantom were compared with the known actual contrast ratios. The calculated difference from the true values was largest with the FBP method; iteratively reconstructed images proved closer to the reality. Similar findings were obtained in the patient studies. The plain OS-EM method improved the contrast whereas in the case of the MRP technique the improvement in contrast was not so evident with post-filtering.     

Spatial resolution measurement for iterative reconstruction by use of image-averaging techniques in computed tomography

The purpose of our study was to investigate the validity of a spatial resolution measuring method that uses a combination of a bar-pattern phantom and an image-averaging technique, and to evaluate the spatial resolution property of iterative reconstruction (IR) images with middle-contrast (50 HU) objects. We used computed tomography (CT) images of the bar-pattern phantom reconstructed by the IR technology Adaptive Iterative Dose Reduction 3D (AIDR 3D), which was installed in the multidetector CT system Aquilion ONE (Toshiba Medical Systems, Otawara, Japan). The contrast of the bar-pattern image was set to 50 HU, which is considered to be a middle contrast that requires higher spatial resolution clinically. We employed an image-averaging technique to eliminate the influence of image noise, and we obtained averaged images of the bar-pattern phantom with sufficiently low noise. Modulation transfer functions (MTFs) were measured from the images. The conventional wire method was also used for comparison; in this method, AIDR 3D showed MTF values equivalent to those of filtered back projection. For the middle-contrast condition, the results showed that the MTF of AIDR 3D decreased with the strength of IR processing. Further, the MTF of AIDR 3D decreased with dose reduction. The image-averaging technique used was effective for correct evaluation of the spatial resolution for middle-contrast objects in IR images. The results obtained by our method clarified that the resolution preservation of AIDR 3D was not sufficient for middle-contrast objects.     

A Bayesian iterative transmission gradient reconstruction algorithm for cardiac SPECT attenuation correction

Background  High-quality attenuation maps are critical for attenuation correction of myocardial perfusion single photon emission computed tomography studies. The filtered backprojection (FBP) approach can introduce errors, especially with low-count transmission data. We present a new method for attenuation map reconstruction and examine its performance in phantom and patient data. Methods and Results  The Bayesian iterative transmission gradient algorithm incorporates a spatially varying gamma prior function that preferentially weights estimated attenuation coefficients toward the soft-tissue value while allowing data-driven solutions for lung and bone regions. The performance with attenuation-corrected technetium 99m sestamibi clinical images was evaluated in phantom studies and in 50 low-likelihood patients grouped by body mass index (BMI). The algorithm converged in 15 iterations in the phantom studies. For the clinical studies, soft-tissue estimates had significantly greater uniformity of mediastinal coefficients (mean SD, 0.005 cm⁻¹ vs 0.011 cm⁻¹; P<.0001). The accuracy and uniformity of the Bayesian iterative transmission gradient algorithm were independent of BMI, whereas both declined at higher BMI values with FBP. Attenuation-corrected perfusion images showed improvement in myocardial wall variability (4.8% to 4.1%, P=.02) for all BMI groups with the new method compared with FBP. Conclusion  This new method for attenuation map reconstruction provides rapidly converging and accurate attenuation maps over a wide spectrum of patient BMI values and significantly improves attenuation-corrected perfusion images.     

Comparative analysis of iterative reconstruction algorithms with resolution recovery and time of flight modeling for 18F-FDG cardiac PET: A multi-center phantom study

Journal of Nuclear Cardiology - The purpose of this study was to evaluate the image quality in cardiac 18F-FDG PET using the time of flight (TOF) and/or point spread function (PSF) modeling in the...     

Motion compensated iterative reconstruction of a region of interest in cardiac cone-beam CT

A method for motion compensated iterative CT reconstruction of a cardiac region-of-interest is presented. The algorithm is an ordered subset maximum likelihood approach with spherically symmetric basis functions, and it uses an ECG for gating. Since the straightforward application of iterative methods to CT data has the drawback that a field-of-view has to be reconstructed, which covers the complete volume contributing to the absorption, region-of-interest reconstruction is applied here. Despite gating, residual object motion within the reconstructed gating window leads to motion blurring in the reconstructed image. To limit this effect, motion compensation is applied. Hereto, a gated 4D reconstruction at multiple phases is generated for the region-of-interest, and a limited set of vascular landmarks are manually annotated throughout the cardiac phases. A dense motion vector field is obtained from these landmarks by scattered data interpolation. The method is applied to two clinical data sets at strongest motion phases. Comparing the method to standard gated iterative reconstruction results shows that motion compensation strongly improved reconstruction quality.     

Statistical iterative reconstruction for streak artefact reduction when using multidetector CT to image the dento-alveolar structures

Objectives:

When metallic prosthetic appliances and dental fillings exist in the oral cavity, the appearance of metal-induced streak artefacts is not avoidable in CT images. The aim of this study was to develop a method for artefact reduction using the statistical reconstruction on multidetector row CT images.

Methods:

Adjacent CT images often depict similar anatomical structures. Therefore, reconstructed images with weak artefacts were attempted using projection data of an artefact-free image in a neighbouring thin slice. Images with moderate and strong artefacts were continuously processed in sequence by successive iterative restoration where the projection data was generated from the adjacent reconstructed slice. First, the basic maximum likelihood–expectation maximization algorithm was applied. Next, the ordered subset–expectation maximization algorithm was examined. Alternatively, a small region of interest setting was designated. Finally, the general purpose graphic processing unit machine was applied in both situations.

Results:

The algorithms reduced the metal-induced streak artefacts on multidetector row CT images when the sequential processing method was applied. The ordered subset–expectation maximization and small region of interest reduced the processing duration without apparent detriments. A general-purpose graphic processing unit realized the high performance.

Conclusions:

A statistical reconstruction method was applied for the streak artefact reduction. The alternative algorithms applied were effective. Both software and hardware tools, such as ordered subset–expectation maximization, small region of interest and general-purpose graphic processing unit achieved fast artefact correction.     

Evaluation of time resolution in cardiac synchronized image reconstruction using multi-slice CT

One of the newest CT application technologies is cardiac synchronized image reconstruction. In this technology, evaluation of time-resolution is very important. We developed a method of measuring time-resolution in cardiac synchronized reconstruction, and evaluated various scanning protocols. In our experiment, ECG-gated scanning was done by multi-slice CT (Aquilion16 Super Heart Edition, Toshiba Medical Systems Co., Ltd., Japan). The nominal slice thickness was 0.5 mm, and rotation time was 0.5 sec. Input heart rate was set at 40, 45, 50, 55, 60, 70, 75, 80, and 90 bpm, and helical pitch at 3.2, 4.0, and 4.8 (beam-pitch: 0.200, 0.250 and 0.300). We measured FWTM of the obtained sensitivity distribution and compared at each scanning protocol. Time resolution improved as helical pitch decreased and heart rate increased. However, phase-time resolution deteriorated as heart rate increased. The results of our experiment indicated that a segment center was determined by X-ray tube rotation time and heart rate, and the number of segments was determined by heart rate, helical pitch, and reconstruction position. Time resolution changed with X-ray tube rotation time, heart rate, helical pitch, and reconstruction position. In this report, we provide a reference for an optimal scanning protocol in cardiac synchronized image reconstruction.     

Quantification and reduction of attenuation related artifacts in SPET by applying attenuation model during iterative image reconstruction: a Monte Carlo study

Photon attenuation is one of the main causes of the quantitative errors and artifacts in SPET. A transmission or CT based attenuation map is necessary to correct for the effects of attenuation accurately. In this research, some important attenuation related artifacts are described. A fast and memory efficient iterative algorithm is proposed for attenuation correction. Ordered subset expectation maximization (OSEM) algorithm with attenuation model was applied for image reconstruction. Monte Carlo simulation was used to create the projections in this study. Different voxel based phantoms with uniform and non-uniform activity distributions and attenuation maps were employed to evaluate the accuracy of this algorithm. The NCAT digital phantom was also used to investigate the attenuation effects on myocardial perfusion SPET in men and women. Projections free from the effect of attenuation were also simulated. The reconstructed image from these attenuation-free projections was considered as reference image. Our attenuation correction algorithm was evaluated by its ability to recover activity and to remove attenuation related artifacts. The mean-square-error (MSE) between reference and corrected image and image contrast were calculated for quantitative evaluation of this algorithm. A variety of attenuation related artifacts were observed. Moreover anterior wall of myocardial perfusion images of female phantom and inferior wall in male phantom were affected by attenuation. All of the attenuation related artifacts were removed after attenuation correction. Quantitatively, the MSE values between reference images and corrected images were reduced by about 900% for all phantoms. In conclusion, by applying our new method for incorporating attenuation model during OSEM, we were able to eliminate a variety of artifacts and errors, which is a necessary step for quantitative SPET.     

Retrospective reconstruction of high temporal resolution cine images from real-time MRI using iterative motion correction

Cardiac function has traditionally been evaluated using breath-hold cine acquisitions. However, there is a great need for free breathing techniques in patients who have difficulty in holding their breath. Real-time cardiac MRI is a valuable alternative to the traditional breath-hold imaging approach, but the real-time images are often inferior in spatial and temporal resolution. This article presents a general method for reconstruction of high spatial and temporal resolution cine images from a real-time acquisition acquired over multiple cardiac cycles. The method combines parallel imaging and motion correction based on nonrigid registration and can be applied to arbitrary k-space trajectories. The method is demonstrated with real-time Cartesian imaging and Golden Angle radial acquisitions, and the motion-corrected acquisitions are compared with raw real-time images and breath-hold cine acquisitions in 10 (N = 10) subjects. Acceptable image quality was obtained in all motion-corrected reconstructions, and the resulting mean image quality score was (a) Cartesian real-time: 2.48, (b) Golden Angle real-time: 1.90 (1.00-2.50), (c) Cartesian motion correction: 3.92, (d) Radial motion correction: 4.58, and (e) Breath-hold cine: 5.00. The proposed method provides a flexible way to obtain high-quality, high-resolution cine images in patients with difficulty holding their breath.