Reconstructed spatial resolution and contrast recovery with Bayesian penalized likelihood reconstruction (Q.Clear) for FDG-PET compared to time-of-flight (TOF) with point spread function (PSF)

BACKGROUND: Bayesian penalized likelihood reconstruction for PET (e.g., GE Q.Clear) aims at improving convergence of lesion activity while ensuring sufficient signal-to-noise ratio (SNR). This study evaluated reconstructed spatial resolution, maximum/peak contrast recovery (CRmax/CRpeak) and SNR of Q.Clear compared to time-of-flight (TOF) OSEM with and without point spread function (PSF) modeling. METHODS: The NEMA IEC Body phantom was scanned five times (3 min scan duration, 30 min between scans, background, 1.5-3.9 kBq/ml F18) with a GE Discovery MI PET/CT (3-ring detector) with spheres filled with 8-, 4-, or 2-fold the background activity concentration (SBR 8:1, 4:1, 2:1). Reconstruction included Q.Clear (beta, 150/300/450), "PSF+TOF4/16" (iterations, 4; subsets, 16; in-plane filter, 2.0 mm), "OSEM+TOF4/16" (identical parameters), "PSF+TOF2/17" (2 it, 17 ss, 2.0 mm filter), "OSEM+TOF2/17" (identical), "PSF+TOF4/8" (4 it, 8 ss, 6.4 mm), and "OSEM+TOF2/8" (2 it, 8 ss, 6.4 mm). Spatial resolution was derived from 3D sphere activity profiles. RC as (sphere activity concentration [AC]/true AC). SNR as (background mean AC/background AC standard deviation). RESULTS: Spatial resolution of Q.Clear150 was significantly better than all conventional algorithms at SBR 8:1 and 4:1 (Wilcoxon, each p < 0.05). At SBR 4:1 and 2:1, the spatial resolution of Q.Clear300/450 was similar or inferior to PSF+TOF4/16 and OSEM+TOF4/16. Small sphere CRpeak generally underestimated true AC, and it was similar for Q.Clear150/300/450 as with PSF+TOF4/16 or PSF+TOF2/17 (i.e., relative differences < 10%). Q.Clear provided similar or higher CRpeak as OSEM+TOF4/16 and OSEM+TOF2/17 resulting in a consistently better tradeoff between CRpeak and SNR with Q.Clear. Compared to PSF+TOF4/8/OSEM+TOF2/8, Q.Clear150/300/450 showed lower SNR but higher CRpeak. CONCLUSIONS: Q.Clear consistently improved reconstructed spatial resolution at high and medium SBR compared to PSF+TOF and OSEM+TOF, but only with beta = 150. However, this is at the cost of inferior SNR with Q.Clear150 compared to Q.Clear300/450 and PSF+TOF4/16/PSF+TOF2/17 while CRpeak for the small spheres did not improve considerably. This suggests that Q.Clear300/450 may be advantageous for the 3-ring detector configuration because the tradeoff between CR and SNR with Q.Clear300/450 was superior to PSF+TOF4/16, OSEM+TOF4/16, and OSEM+TOF2/17. However, it requires validation by systematic evaluation in patients at different activity and acquisition protocols

Fast and accurate X-ray fluorescence computed tomography imaging with the ordered-subsets expectation maximization algorithm.

The ordered-subsets expectation maximization algorithm (OSEM) is introduced to X-ray fluorescence computed tomography (XFCT) and studied; here, simulations and experimental results are presented. The simulation results indicate that OSEM is more accurate than the filtered back-projection algorithm, and it can efficiently suppress the deterioration of image quality within a large range of angular sampling intervals. Experimental results of both an artificial phantom and cirrhotic liver show that with a satisfying image quality the angular sampling interval could be improved to save on the data-acquisition time when OSEM is employed. In addition, with an optimum number of subsets, the image reconstruction time of OSEM could be reduced to about half of the time required for one subset. Accordingly, it can be concluded that OSEM is a potential method for fast and accurate XFCT imaging

Efficient Bayesian-based Multi-View Deconvolution

Light sheet fluorescence microscopy is able to image large specimen with high resolution by imaging the sam- ples from multiple angles. Multi-view deconvolution can significantly improve the resolution and contrast of the images, but its application has been limited due to the large size of the datasets. Here we present a Bayesian- based derivation of multi-view deconvolution that drastically improves the convergence time and provide a fast implementation utilizing graphics hardware.Comment: 48 pages, 20 figures, 1 table, under review at Nature Method

Impact of Bayesian penalized likelihood reconstruction on quantitative and qualitative aspects for pulmonary nodule detection in digital 2-[18F]FDG-PET/CT

To evaluate the impact of block sequential regularized expectation maximization (BSREM) reconstruction on quantitative and qualitative aspects of 2-[18F]FDG-avid pulmonary nodules compared to conventional ordered subset expectation maximization (OSEM) reconstruction method. Ninety-one patients with 144 2-[18F]FDG-avid pulmonary nodules (all ≤ 20 mm) undergoing PET/CT for oncological (re-)staging were retrospectively included. Quantitative parameters in BSREM and OSEM (including point spread function modelling) were measured, including maximum standardized uptake value (SUVmax). Nodule conspicuity in BSREM and OSEM images was evaluated by two readers. Wilcoxon matched pairs signed-rank test was used to compare quantitative and qualitative parameters in BSREM and OSEM. Pulmonary nodule SUVmax was significantly higher in BSREM images compared to OSEM images [BSREM 5.4 (1.2–20.7), OSEM 3.6 (0.7–17.4); p = 0.0001]. In a size-based analysis, the relative increase in SUVmax was more pronounced in smaller nodules (≤ 7 mm) as compared to larger nodules (8–10 mm, or > 10 mm). Lesion conspicuity was higher in BSREM than in OSEM (p < 0.0001). BSREM reconstruction results in a significant increase in SUVmax and a significantly improved conspicuity of small 2-[18F]FDG-avid pulmonary nodules compared to OSEM reconstruction. Digital 2-[18F]FDG-PET/CT reading may be enhanced with BSREM as small lesion conspicuity is improved

Noise reduction using a Bayesian penalized-likelihood reconstruction algorithm on a time-of-flight PET-CT scanner

Purpose: Q.Clear is a block sequential regularized expectation maximization (BSREM) penalized-likelihood reconstruction algorithm for PET. It tries to improve image quality by controlling noise amplification during image reconstruction. In this study, the noise properties of this BSREM were compared to the ordered-subset expectation maximization (OSEM) algorithm for both phantom and patient data acquired on a state-of-the-art PET/CT. Methods: The NEMA IQ phantom and a whole-body patient study were acquired on a GE DMI 3-rings system in list mode and different datasets with varying noise levels were generated. Phantom data was evaluated using four different contrast ratios. These were reconstructed using BSREM with different beta-factors of 300-3000 and with a clinical setting used for OSEM including point spread function (PSF) and time-of-flight (TOF) information. Contrast recovery (CR), background noise levels (coefficient of variation, COV), and contrast-to-noise ratio (CNR) were used to determine the performance in the phantom data. Findings based on the phantom data were compared with clinical data. For the patient study, the SUV ratio, metabolic active tumor volumes (MATVs), and the signal-to-noise ratio (SNR) were evaluated using the liver as the background region. Results: Based on the phantom data for the same count statistics, BSREM resulted in higher CR and CNR and lower COV than OSEM. The CR of OSEM matches to the CR of BSREM with beta = 750 at high count statistics for 8:1. A similar trend was observed for the ratios 6:1 and 4:1. A dependence on sphere size, counting statistics, and contrast ratio was confirmed by the CNR of the ratio 2:1. BSREM with beta = 750 for 2.5 and 1.0 min acquisition has comparable COV to the 10 and 5.0 min acquisitions using OSEM. This resulted in a noise reduction by a factor of 2-4 when using BSREM instead of OSEM. For the patient data, a similar trend was observed, and SNR was reduced by at least a factor of 2 while preserving contrast. Conclusion: The BSREM reconstruction algorithm allowed a noise reduction without a loss of contrast by a factor of 2-4 compared to OSEM reconstructions for all data evaluated. This reduction can be used to lower the injected dose or shorten the acquisition time

NEMA NU 2-2007 performance characteristics of GE Signa integrated PET/MR for different PET isotopes

BackgroundFully integrated PET/MR systems are being used frequently in clinical research and routine. National Electrical Manufacturers Association (NEMA) characterization of these systems is generally done with F-18 which is clinically the most relevant PET isotope. However, other PET isotopes, such as Ga-68 and Y-90, are gaining clinical importance as they are of specific interest for oncological applications and for follow-up of Y-90-based radionuclide therapy. These isotopes have a complex decay scheme with a variety of prompt gammas in coincidence. Ga-68 and Y-90 have higher positron energy and, because of the larger positron range, there may be interference with the magnetic field of the MR compared to F-18. Therefore, it is relevant to determine the performance of PET/MR for these clinically relevant and commercially available isotopes.MethodsNEMA NU 2-2007 performance measurements were performed for characterizing the spatial resolution, sensitivity, image quality, and the accuracy of attenuation and scatter corrections for F-18, Ga-68, and Y-90. Scatter fraction and noise equivalent count rate (NECR) tests were performed using F-18 and Ga-68. All phantom data were acquired on the GE Signa integrated PET/MR system, installed in UZ Leuven, Belgium.Results(18)F, Ga-68, and Y-90 NEMA performance tests resulted in substantially different system characteristics. In comparison with F-18, the spatial resolution is about 1mm larger in the axial direction for Ga-68 and no significative effect was found for Y-90. The impact of this lower resolution is also visible in the recovery coefficients of the smallest spheres of Ga-68 in image quality measurements, where clearly lower values are obtained. For Y-90, the low number of counts leads to a large variability in the image quality measurements. The primary factor for the sensitivity change is the scale factor related to the positron emission fraction. There is also an impact on the peak NECR, which is lower for Ga-68 than for F-18 and appears at higher activities.ConclusionsThe system performance of GE Signa integrated PET/MR was substantially different, in terms of NEMA spatial resolution, image quality, and NECR for Ga-68 and Y-90 compared to F-18. But these differences are compensated by the PET/MR scanner technologies and reconstructions methods

Optimization of image reconstruction method for SPECT studies performed using [99mTc-EDDA/HYNIC] octreotate in patients with neuroendocrine tumors

BACKGROUND: Somatostatin receptor scintigraphy (SRS)is a useful tool in the assessment of GEP-NET (gastroenteropancreaticneuroendocrine tumor) patients. The choiceof appropriate settings of image reconstruction parameters iscrucial in interpretation of these images. The aim of the studywas to investigate how the GEP NET lesion signal to noise ratio(TCS/TCB) depends on different reconstruction settings for Flash3D software (Siemens).METHODS: SRS results of 76 randomly selected patients withconfirmed GEP-NET were analyzed. For SPECT studies the datawere acquired using standard clinical settings 3–4 h after theinjection of 740 MBq 99mTc-[EDDA/HYNIC] octreotate. To obtainfinal images the OSEM 3D Flash reconstruction with differentsettings and FBP reconstruction were used. First, the TCS/TCBratio in voxels was analyzed for different combinations of thenumber of subsets and the number of iterations of the OSEM3D Flash reconstruction. Secondly, the same ratio was analyzed for different parameters of the Gaussian filter (with FWHM = 2–4times greater from the pixel size). Also the influence of scattercorrection on the TCS/TCB ratio was investigated.RESULTS: With increasing number of subsets and iterations, theincrease of TCS/TCB ratio was observed. With increasing settingsof Gauss [FWHM coefficient] filter, the decrease of TCS/TCB ratiowas reported. The use of scatter correction slightly decreasesthe values of this ratio.CONCLUSIONS: OSEM algorithm provides a meaningfullybetter reconstruction of the SRS SPECT study as compared tothe FBP technique. A high number of subsets improves imagequality (images are smoother). Increasing number of iterationsgives a better contrast and the shapes of lesions and organs aresharper. The choice of reconstruction parameters is a compromisebetween image qualitative appearance and its quantitativeaccuracy and should not be modified when comparing multiplestudies of the same patient

Regularized Image Reconstruction Algorithms for Dual-Isotope Myocardial Perfusion SPECT (MPS) Imaging Using a Cross-Tracer Prior

In simultaneous dual-isotope myocardial perfusion SPECT (MPS) imaging, data are simultaneously acquired to determine the distributions of two radioactive isotopes. The goal of this work was to develop penalized maximum likelihood (PML) algorithms for a novel cross-tracer prior that exploits the fact that the two images reconstructed from simultaneous dual-isotope MPS projection data are perfectly registered in space. We first formulated the simultaneous dual-isotope MPS reconstruction problem as a joint estimation problem. A cross-tracer prior that couples voxel values on both images was then proposed. We developed an iterative algorithm to reconstruct the MPS images that converges to the maximum a posteriori solution for this prior based on separable surrogate functions. To accelerate the convergence, we developed a fast algorithm for the cross-tracer prior based on the complete data OS-EM (COSEM) framework. The proposed algorithm was compared qualitatively and quantitatively to a single-tracer version of the prior that did not include the cross-tracer term. Quantitative evaluations included comparisons of mean and standard deviation images as well as assessment of image fidelity using the mean square error. We also evaluated the cross tracer prior using a three-class observer study with respect to the three-class MPS diagnostic task, i.e., classifying patients as having either no defect, reversible defect, or fixed defects. For this study, a comparison with conventional ordered subsets-expectation maximization (OS-EM) reconstruction with postfiltering was performed. The comparisons to the single-tracer prior demonstrated similar resolution for areas of the image with large intensity changes and reduced noise in uniform regions. The cross-tracer prior was also superior to the single-tracer version in terms of restoring image fidelity. Results of the three-class observer study showed that the proposed cross-tracer prior and the convergent algorithms improved the ima- - ge quality of dual-isotope MPS images compared to OS-EM.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85873/1/Fessler3.pd