Row-action Maximum Likelihood Algorithm Research Articles

List-Mode PET Image Reconstruction Using Deep Image Prior.

List-mode positron emission tomography (PET) image reconstruction is an important tool for PET scanners with many lines-of-response and additional information such as time-of-flight and depth-of-interaction. Deep learning is one possible solution to enhance the quality of PET image reconstruction. However, the application of deep learning techniques to list-mode PET image reconstruction has not been progressed because list data is a sequence of bit codes and unsuitable for processing by convolutional neural networks (CNN). In this study, we propose a novel list-mode PET image reconstruction method using an unsupervised CNN called deep image prior (DIP) which is the first trial to integrate list-mode PET image reconstruction and CNN. The proposed list-mode DIP reconstruction (LM-DIPRecon) method alternatively iterates the regularized list-mode dynamic row action maximum likelihood algorithm (LM-DRAMA) and magnetic resonance imaging conditioned DIP (MR-DIP) using an alternating direction method of multipliers. We evaluated LM-DIPRecon using both simulation and clinical data, and it achieved sharper images and better tradeoff curves between contrast and noise than the LM-DRAMA, MR-DIP and sinogram-based DIPRecon methods. These results indicated that the LM-DIPRecon is useful for quantitative PET imaging with limited events while keeping accurate raw data information. In addition, as list data has finer temporal information than dynamic sinograms, list-mode deep image prior reconstruction is expected to be useful for 4D PET imaging and motion correction.

Organ-Specific Positron Emission Tomography Scanners for Breast Imaging: Comparison between the Performances of Prior and Novel Models.

The performances of photomultiplier tube (PMT)-based dedicated breast positron emission tomography (PET) and silicon photomultiplier tube (SiPM)-based time-of-flight (TOF) PET, which is applicable not only to breast imaging but also to head imaging, were compared using a phantom study. A cylindrical phantom containing four spheres (3-10 mm in diameter) filled with 18F-FDG at two signal-to-background ratios (SBRs), 4:1 and 8:1, was scanned. The phantom images, which were reconstructed using three-dimensional list-mode dynamic row-action maximum likelihood algorithm with various β-values and post-smoothing filters, were visually and quantitatively compared. Visual evaluation showed that the 3 mm sphere was more clearly visualized with higher β and smaller post-filters, while the background was noisier; SiPM-based TOF-PET was superior to PMT-based dbPET in sharpness, smoothness, and detectability, although the background was noisier at the SBR of 8:1. Quantitative evaluation revealed that the detection index (DI) and recovery coefficient (CRC) of SiPM-based TOF-PET images were higher than those of PMT-based PET images, despite a higher background coefficient of variation (CVBG). The two organ-specific PET systems showed that a 3 mm lesion in the breast could be visualized at the center of the detector, and there was less noise in the SiPM-based TOF-PET image.

Dr. Eiichi Tanaka's Achievement in the Research of Image Reconstruction

In memoriam of Dr. Eiichi Tanaka who passed away on August 21, 2021, I review his achievement in the research of tomographic image reconstruction. Tomographic image reconstruction is an important research area which has wide applications including X-ray CT, nuclear medicine imaging such as PET and SPECT, and electron microscopy. Since 1970's, Dr. Tanaka has worked on numerous important topics in tomographic reconstruction fields aiming at using them in image reconstruction for PET and SPECT. Among them, in this paper, I will introduce his research on Filtered BackProjection (FBP) method, analytical attenuation correction in SPECT, image reconstruction in Time-of-Flight PET, image reconstruction for 3-D PET imaging, and iterative image reconstruction method called Dynamic Row-Action Maximum Likelihood Algorithm (DRAMA).

Optimal relaxation parameters of dynamic row-action maximum likelihood algorithm and post-smoothing filter for image reconstruction of dedicated breast PET.

This study aimed to determine the optimal β value of the relaxation control parameter and the post-smoothing filter in the list-mode dynamic row-action maximum likelihood algorithm (LM-DRAMA) to detect early stage breast cancer with high-resolution dedicated breast positron emission tomography (dbPET) in phantom and clinical studies. A breast phantom containing four spheres (5, 7.5, 10, and 16mm in diameter) was filled with 18F-fluorodeoxyglucose solution (sphere-to-background ratio, 8:1) and scanned on a dbPET scanner. The images were reconstructed using LM-DRAMA with different β values (5, 20, or 100) and Gaussian post-filters (0, 0.78, 1.17, 1.56, 1.95, or 2.34mm). Other conditions were according to those routinely used (1 iteration and 128 subsets including attenuation and scatter correction). Image quality was evaluated visually and by computing the coefficient of variation of the background (CVBG), detectability index (DI), and contrast recovery coefficient. Parameters optimized in these phantom studies were applied to 25 clinical data sets. Variabilities for different reconstruction methods in visual scores, the maximum standardized uptake value of breast cancer, and the tumor-to-background uptake ratio were estimated. The reconstruction images of the phantom with higher β values and smaller post-filters yielded higher visual scores for detectability and DI and lower smoothness and CVBG scores. Based on the phantom study, the β values and post-filter were optimized for clinical dbPET images except for β5 and 2.34mm post-filter. Applying the other reconstructions to clinical studies showed that β100 provided higher quantitative parameter values. The detectability of lesions was similar for β100 and β20 and decreased with larger post-filters. The lesion detection rate was similar for β100 and β20 and decreased with larger post-filter. The relaxation coefficient factor β20 and a 0.78- or 1.17-mm post-filter were optimal for dbPET image reconstruction with balanced spatial resolution and noise. However, they should be selected according to the impact on the dbPET image and the purpose of the examination.

Qualitative and Quantitative Assessment of Nonlocal Means Reconstruction Algorithm in a Flexible PET Scanner.

OBJECTIVE. Flexible PET (fxPET) was designed to fit existing MRI systems. The newly modified nonlocal means (NLM) algorithm is combined with the 3D dynamic row-action maximum likelihood algorithm (DRAMA). We investigated qualitative and quantitative acceptability of fxPET images reconstructed by modified NLM compared with whole-body (WB) PET/CT images and conventional 3D DRAMA reconstruction alone. MATERIALS AND METHODS. Fifty-nine patients with known or suspected malignancies underwent WB PET/CT scanning approximately 1 hour after the injection of 18F-FDG, after which they underwent fxPET scanning. Two readers rated the quality of fxPET images by consensus. Detection rate (the proportion of lesions found on PET), maximal standardized uptake value (SUVmax), metabolic tumor volume (MTV), total lesion glycolysis (TLG), tumor-to-normal liver ratio (TNR), and background liver signal-to-noise ratio (SNR) were compared among the three datasets. RESULTS. Higher image quality was obtained by modified NLM reconstruction than by conventional reconstruction without statistical significance. The detection rate was comparable among three datasets. SUVmax was significantly higher, and MTV and TLG were significantly lower in the modified NLM dataset (p < 0.002) than in the other two datasets, with significantly positive correlations (p < 0.001; Spearman rank correlation coefficient, 0.87-0.99). The TNRs in modified NLM images were significantly larger than in the other datasets (p < 0.05). The background SNRs in modified NLM images were comparable with those in WB PET/CT images, and significantly higher than in the conventional fxPET images (p < 0.005). CONCLUSION. The modified NLM algorithm was clinically acceptable, yielding higher TNR and background SNR compared with conventional reconstruction. Image quality and the lesion detection rate were comparable in this population.

Noninvasive Quantification of Myocardial 11C-Meta-Hydroxyephedrine Kinetics.

(11)C-meta-hydroxyephedrine ((11)C-HED) kinetics in the myocardium can be quantified using a single-tissue-compartment model together with a metabolite-corrected arterial blood sampler input function (BSIF). The need for arterial blood sampling, however, limits clinical applicability. The purpose of this study was to investigate the feasibility of replacing arterial sampling with imaging-derived input function (IDIF) and venous blood samples. Twenty patients underwent 60-min dynamic (11)C-HED PET/CT scans with online arterial blood sampling. Thirteen of these patients also underwent venous blood sampling. Data were reconstructed using both 3-dimensional row-action maximum-likelihood algorithm (3DR) and a time-of-flight (TF) list-mode reconstruction algorithm. For each reconstruction, IDIF results were compared with BSIF results. In addition, IDIF results obtained with venous blood samples and with a transformed venous-to-arterial metabolite correction were compared with results obtained with arterial metabolite corrections. Correlations between IDIF- and BSIF-derived K1 and VT were high (r(2) > =0.89 for 3DR and TF). Slopes of the linear fits were significantly different from 1 for K1, for both 3DR (slope = 0.94) and TF (slope = 1.06). For VT, the slope of the linear fit was different from 1 for TF (slope = 0.93) but not for 3DR (slope = 0.98). Use of venous blood data introduced a large bias in VT (r(2) = 0.96, slope = 0.84) and a small bias in K1 (r(2) = 0.99, slope = 0.98). Use of a second-order polynomial venous-to-arterial transformation was robust and greatly reduced bias in VT (r(2) = 0.97, slope = 0.99) with no effect on K1 CONCLUSION: IDIF yielded precise results for both 3DR and TF. Venous blood samples can be used for absolute quantification of (11)C-HED studies, provided a venous-to-arterial transformation is applied. A venous-to-arterial transformation enables noninvasive, absolute quantification of (11)C-HED studies.

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.

Impact of time-of-flight on qualitative and quantitative analyses of myocardial perfusion PET studies using 13N-ammonia

BackgroundThe impact of time-of-flight (TOF) in myocardial perfusion 13N-ammonia positron emission tomography (PET) is unclear. Methods and ResultsTwenty consecutive subjects underwent rest and adenosine stress 13N-ammonia myocardial perfusion PET. Two sets of images were reconstructed using TOF-ordered subset expectation maximization (TOF-OSEM) and 3-dimensional row-action maximum likelihood algorithm (3D-RAMLA). Qualitative and quantitative analyses from the TOF-OSEM and 3D-RAMLA reconstructions were compared. Count profile curves revealed that TOF relatively increased the uptake of 13N-ammonia at the lateral walls, and apical thinning was emphasized on the TOF images. Both segmental rest and stress myocardial blood flow (MBF) values were higher with TOF-OSEM use than with 3D-RAMLA use (rest MBF: 0.955 ± 0.201 vs 0.836 ± 0.185, P < .001; stress MBF: 2.149 ± 0.697 vs 2.058 ± 0.721, P < .001). The differentiation of MBF between reconstructions was more enhanced under rest conditions. Thus, segmental myocardial flow reserve (MFR) observed using TOF-OSEM reconstruction was lower than that observed using 3D-RAMLA (2.25 ± 0.57 vs 2.46 ± 0.75, P < .001). No remarkable differences were observed between segmental and territorial results. ConclusionsTOF increased lateral wall counts and emphasized apical thinning. Quantitatively, TOF reconstruction showed increased MBF, especially under relatively low perfusion conditions.

String-averaging expectation-maximization for maximum likelihood estimation in emission tomography

We study the maximum likelihood model in emission tomography and propose a new family of algorithms for its solution, called string-averaging expectation-maximization (SAEM). In the string-averaging algorithmic regime, the index set of all underlying equations is split into subsets, called ‘strings’, and the algorithm separately proceeds along each string, possibly in parallel. Then, the end-points of all strings are averaged to form the next iterate. SAEM algorithms with several strings present better practical merits than the classical row-action maximum-likelihood algorithm. We present numerical experiments showing the effectiveness of the algorithmic scheme, using data of image reconstruction problems. Performance is evaluated from the computational cost and reconstruction quality viewpoints. A complete convergence theory is also provided.

Bootstrap methods for estimating PET image noise: experimental validation and an application to evaluation of image reconstruction algorithms

Accurate and validated methods for estimating regional PET image noise are helpful for optimizing image processing. The bootstrap is a data-based simulation method for statistical inference, which can be used to estimate the PET image noise without repeated measurements. The aim of this study was to experimentally validate bootstrap-based methods as a tool for estimating PET image noise and demonstrate its usefulness for evaluating image reconstruction algorithms. Two bootstrap-based method, the list-mode data bootstrap (LMBS) and the sinogram bootstrap (SNBS), were implemented on a clinical PET scanner. A uniform cylindrical phantom filled with (18)F solution was scanned using list-mode acquisition. A reference standard deviation (SD) map was calculated from 60 statistically independent measured list-mode data. Using one of the 60 list-mode data, 60 bootstrap replicates were generated and used to calculate bootstrap SD maps. Brain (18)F-FDG data from a healthy volunteer were also processed as an example of the bootstrap application. Three reconstruction algorithms, FBP 2D and both 2D and 3D versions of dynamic row-action maximum likelihood algorithm (DRAMA), were assessed. For all the reconstruction algorithms used, the bootstrap SD maps agreed well with the reference SD map, confirming the validity of the bootstrap methods for assessing image noise. The two bootstrap methods were equivalent with respect to the performance of image noise estimation. The bootstrap analysis of the FDG data showed the better contrast-noise relation curve for DRAMA 3D compared to DRAMA 2D and FBP 2D. The bootstrap methods provide the estimates of image noise for various reconstruction algorithms with reasonable accuracy, require only a single measurement, not repeated measures, and are, therefore, applicable for a human PET study.

Effect of Type 2 Diabetes Mellitus on Epicardial Adipose Tissue Volume and Coronary Vasomotor Function

Patients with coronary artery disease and/or type 2 diabetes mellitus (DM) generally exhibit more epicardial adipose tissue (EAT) than healthy controls. Recently, it has been proposed that EAT affects vascular function and structure by secreting proinflammatory and vasoactive substances, thereby potentially contributing to the development of cardiovascular disease. In the present study, the interrelation of EAT, coronary vasomotor function, and coronary artery calcium was investigated in patients with and without DM, who were evaluated for coronary artery disease. Myocardial blood flow (MBF) was assessed at rest and during adenosine-induced hyperemia using [(15)O]-water positron emission tomography combined with computed tomography to quantify coronary artery calcium and EAT in 199 patients (46 with DM). In this cohort (mean age 58 ± 10 years), the patients with DM had a greater body mass index, heart rate, and systolic blood pressure at rest (all p <0.05). Coronary artery calcium and the EAT volumes were comparable between those with and without DM. Both patient groups showed comparable MBF at rest and coronary vascular resistance. A lower hyperemic MBF and coronary flow reserve (CFR) and greater hyperemic coronary vascular resistance (all p <0.05) was observed in the patients with DM. A pooled analysis showed a positive association of EAT volume with hyperemic coronary vascular resistance but not with the MBF at rest, hyperemic MBF, or coronary vascular resistance at rest. In the group analysis, the EAT volume was inversely associated with hyperemic MBF (r = -0.16, p = 0.05) and CFR (r = -0.17, p = 0.04) and positively with hyperemic coronary vascular resistance (r = 0.26, p = 0.002) only in patients without DM. Multivariate regression analysis, adjusted for age, gender, and body mass index, showed an independent association between the EAT volume and hyperemic MBF (β = -0.16, p = 0.02), CFR (β = -0.16, p = 0.04), and hyperemic coronary vascular resistance (β = 0.25, p <0.001) in the non-DM group. In conclusion, these results suggest a role for EAT in myocardial microvascular dysfunction; however, once DM has developed, other factors might be more dominant in contributing to impaired myocardial microvascular dysfunction.

GPU-Based PET Image Reconstruction Using an Accurate Geometrical System Model

In positron emission tomography (PET), 3D iterative image reconstruction methods have a huge computational burden. In this paper, we developed a list-mode image reconstruction method using graphics processing units (GPUs). Efficiency of acceleration for GPU implementation largely depends on the method chosen, where a reduced number of conditional statements and a reduced memory size are required. On the other hand, accurate system models are required to improve the quality of reconstructed images. Various accurate system models for conventional CPU implementation have been proposed, but these models basically require many conditional statements and huge memory size. Therefore, we developed a new system model which matches GPU implementation better. In this model, the detector response functions, which vary depending on each line of response (LOR), are pre-computed in CPUs and modeled by sixth-order polynomial functions in order to reduce the memory size occupied in GPUs. Each element of a system matrix is obtained on-the-fly in GPUs by calculating the distance between an LOR and a voxel. Therefore the developed system model enables efficient GPU implementation of the accurate system modeling with a reduced number of conditional statements and a reduced memory size. We applied the developed method to a small OpenPET prototype, in which 4-layered depth-of-interaction (DOI) detectors were used. For image reconstruction, we used the dynamic row-action maximum likelihood algorithm (DRAMA). Compared with a conventional model for GPU implementation, in which DRFs are given as a Gaussian function of fixed width, we saw no remarkable difference for DOI data, but for non-DOI data the proposed model outperformed the conventional at the peripheral region of the field-of-view. The proposed model had almost the same calculation time as the conventional model did. For further acceleration, we tried parallel GPU implementation, and we obtained 3.8-fold acceleration by using 4 GPUs.

Properties of Noise in Positron Emission Tomography Images Reconstructed with Filtered-Backprojection and Row-Action Maximum Likelihood Algorithm

Noise levels observed in positron emission tomography (PET) images complicate their geometric interpretation. Post-processing techniques aimed at noise reduction may be employed to overcome this problem. The detailed characteristics of the noise affecting PET images are, however, often not well known. Typically, it is assumed that overall the noise may be characterized as Gaussian. Other PET-imaging-related studies have been specifically aimed at the reduction of noise represented by a Poisson or mixed Poisson + Gaussian model. The effectiveness of any approach to noise reduction greatly depends on a proper quantification of the characteristics of the noise present. This work examines the statistical properties of noise in PET images acquired with a GEMINI PET/CT scanner. Noise measurements have been performed with a cylindrical phantom injected with (11)C and well mixed to provide a uniform activity distribution. Images were acquired using standard clinical protocols and reconstructed with filtered-backprojection (FBP) and row-action maximum likelihood algorithm (RAMLA). Statistical properties of the acquired data were evaluated and compared to five noise models (Poisson, normal, negative binomial, log-normal, and gamma). Histograms of the experimental data were used to calculate cumulative distribution functions and produce maximum likelihood estimates for the parameters of the model distributions. Results obtained confirm the poor representation of both RAMLA- and FBP-reconstructed PET data by the Poisson distribution. We demonstrate that the noise in RAMLA-reconstructed PET images is very well characterized by gamma distribution followed closely by normal distribution, while FBP produces comparable conformity with both normal and gamma statistics.

Real-Time Imaging System for the OpenPET

The OpenPET and its real-time imaging capability have great potential for real-time tumor tracking in medical procedures such as biopsy and radiation therapy. For the real-time imaging system, we intend to use the one-pass list-mode dynamic row-action maximum likelihood algorithm (DRAMA) and implement it using general-purpose computing on graphics processing units (GPGPU) techniques. However, it is difficult to make consistent reconstructions in real-time because the amount of list-mode data acquired in PET scans may be large depending on the level of radioactivity, and the reconstruction speed depends on the amount of the list-mode data. In this study, we developed a system to control the data used in the reconstruction step while retaining quantitative performance. In the proposed system, the data transfer control system limits the event counts to be used in the reconstruction step according to the reconstruction speed, and the reconstructed images are properly intensified by using the ratio of the used counts to the total counts. We implemented the system on a small OpenPET prototype system and evaluated the performance in terms of the real-time tracking ability by displaying reconstructed images in which the intensity was compensated. The intensity of the displayed images correlated properly with the original count rate and a frame rate of 2 frames per second was achieved with average delay time of 2.1 s.

Optimal relaxation parameters of DRAMA (dynamic RAMLA) aiming at one-pass image reconstruction for 3D-PET

We have reported a block-iterative algorithm named DRAMA for image reconstruction for emission tomography (Tanaka and Kudo 2003 Phys. Med. Biol. 48 1405–22). DRAMA is a modified version of the row-action maximum likelihood algorithm (RAMLA), in which the relaxation parameter is subset dependent and is changed in such a way that the noise propagation from subsets to the reconstructed image is substantially independent of the access order of the subsets. The algorithm provides fast convergence with a reasonable signal-to-noise ratio. The optimal relaxation parameter has been derived assuming a two-dimensional (2D)-PET model, and detailed performance in three-dimensional (3D) reconstruction has not been clear enough. We have developed the new version ‘DRAMA-3D’, based on the 3D-PET model. The optimal relaxation parameter is a function of the access order of the subsets and the ring difference, and its value is determined by simple formulas from the design parameters of the PET scanner, the operating conditions and the post-smoothing resolution. In this paper, we present the theory of DRAMA-3D, the results of simulation studies on the performance of DRAMA-3D and the comparative studies of the related algorithms. It is shown that DRAMA-3D is robust for various access orders of subsets and is suitable to realize one-pass (single-iteration) reconstruction.

Low-Dose Quantitative Myocardial Blood Flow Imaging Using 15O-Water and PET Without Attenuation Correction

Misalignment between PET and low-dose CT (LD-CT) can cause severe artifacts in cardiac PET/CT because of attenuation-correction errors, even when using slow or cine LD-CT. Myocardial blood flow (MBF), as measured by (15)O-water, can be determined from the rate of (15)O-water washout from myocardial tissue, which is independent of tissue attenuation. The purpose of the present study was to assess the accuracy of these MBF measurements in the absence of attenuation correction. Twenty-five patients referred for evaluation of myocardial perfusion underwent 6-min rest and adenosine stress PET scans after the administration of 370 MBq of (15)O-water; both scans were followed by slow LD-CT. Data were acquired on a PET/CT scanner and reconstructed by a 3-dimensional row-action maximum likelihood algorithm both with (CTAC) and without (NAC) attenuation correction. An ascending aorta volume of interest was used as input function. MBF and coronary flow reserve (CFR) were calculated for 17 myocardial segments using nonlinear regression of the standard single-tissue-compartment model with corrections for left and right ventricular spillover and perfusable tissue fraction. High correlation (r(2) = 0.99 and 0.97, with slopes of 0.96 and 0.91 for rest and stress, respectively) and excellent agreement (intraclass correlation coefficient [ICC], 1.00 and 0.98) between NAC- and CTAC-based MBF values were found. Absolute rest and stress MBF values were 3% and 8%, respectively, lower for NAC scans. The correlation coefficient between all NAC and CTAC CFR values was 0.95 (ICC, 0.95; slope, 0.92) and 0.97 (ICC, 0.99; slope, 1.01) when only CFR values below 2 were considered. Deviations between CTAC and NAC values were smallest for basal segments and increased toward the apex. MBF and CFR can be measured accurately using (15)O-water and PET without correcting for attenuation, reducing the effective dose to the patient to 0.8 mSv for a complete rest-stress protocol. This dose is an order of magnitude lower than typical values for (82)Rb, (99m)Tc-methoxyisobutylisonitrile, or CT perfusion scans.

Effect of variation in relaxation parameter value on LOR-RAMLA reconstruction of 18F-FDG PET studies

We tested the impact of different values of the relaxation parameter lambda (lambda) on contrast and noise in line-of-response row-action maximum likelihood algorithm (LOR-RAMLA) in 18F-fluorodeoxyglucose positron emission tomography (PET)/computed tomography (CT) imaging. Phantom studies were performed on a Gemini XL PET/CT scanner. The NEMA/IEC (National Electrical Manufacturers Association/International Electro technical Commission) torso phantom was used and acquisition data were reconstructed with lambda values ranging from 0.025 to 0.1. Quality of the reconstructed images was evaluated by contrast recovery coefficients and background variability values according to the NEMA NU 2-2001 procedures. Contrast recovery coefficients and background variability increased significantly when lambda increased. The best noise-versus-resolution trade-off was obtained with lambda in the 0.04-0.06 range. For LOR-RAMLA reconstruction, the manufacturer allows a possible lambda choice from 0.025 to 0.1. We would not advise too small (0.025) or too large (0.1) lambda values which result in too smooth or too noisy images. We determined optimal lambda values in LOR-RAMLA on a Gemini XL PET/CT scanner. Caution is needed when using lambda values out of that range.

Evaluation of dynamic row-action maximum likelihood algorithm reconstruction for quantitative 15O brain PET

A modified version of row-action maximum likelihood algorithm (RAMLA) using a 'subset-dependent' relaxation parameter for noise suppression, or dynamic RAMLA (DRAMA), has been proposed. The aim of this study was to assess the capability of DRAMA reconstruction for quantitative (15)O brain positron emission tomography (PET). Seventeen healthy volunteers were studied using a 3D PET scanner. The PET study included 3 sequential PET scans for C(15)O, (15)O(2) and H (2) (15) O. First, the number of main iterations (N (it)) in DRAMA was optimized in relation to image convergence and statistical image noise. To estimate the statistical variance of reconstructed images on a pixel-by-pixel basis, a sinogram bootstrap method was applied using list-mode PET data. Once the optimal N (it) was determined, statistical image noise and quantitative parameters, i.e., cerebral blood flow (CBF), cerebral blood volume (CBV), cerebral metabolic rate of oxygen (CMRO(2)) and oxygen extraction fraction (OEF) were compared between DRAMA and conventional FBP. DRAMA images were post-filtered so that their spatial resolutions were matched with FBP images with a 6-mm FWHM Gaussian filter. Based on the count recovery data, N (it) = 3 was determined as an optimal parameter for (15)O PET data. The sinogram bootstrap analysis revealed that DRAMA reconstruction resulted in less statistical noise, especially in a low-activity region compared to FBP. Agreement of quantitative values between FBP and DRAMA was excellent. For DRAMA images, average gray matter values of CBF, CBV, CMRO(2) and OEF were 46.1 +/- 4.5 (mL/100 mL/min), 3.35 +/- 0.40 (mL/100 mL), 3.42 +/- 0.35 (mL/100 mL/min) and 42.1 +/- 3.8 (%), respectively. These values were comparable to corresponding values with FBP images: 46.6 +/- 4.6 (mL/100 mL/min), 3.34 +/- 0.39 (mL/100 mL), 3.48 +/- 0.34 (mL/100 mL/min) and 42.4 +/- 3.8 (%), respectively. DRAMA reconstruction is applicable to quantitative (15)O PET study and is superior to conventional FBP in terms of image quality.

Efficient 3-D TOF PET reconstruction using view-grouped histo-images: DIRECT-direct image reconstruction for TOF.

For modern time-of-flight (TOF) positron emission tomography (PET) systems, in which the number of possible lines of response and TOF bins is much larger than the number of acquired events, the most appropriate reconstruction approaches are considered to be list-mode methods. However, their shortcomings are relatively high computational costs for reconstruction and for sensitivity matrix calculation. Efficient treatment of TOF data within the proposed DIRECT approach is obtained by 1) angular (azimuthal and co-polar) grouping of TOF events to a set of views as given by the angular sampling requirements for the TOF resolution, and 2) deposition (weighted-histogramming) of these grouped events, and correction data, into a set of "histo-images," one histo-image per view. The histo-images have the same geometry (voxel grid, size and orientation) as the reconstructed image. The concept is similar to the approach involving binning of the TOF data into angularly subsampled histo-projections-projections expanded in the TOF directions. However, unlike binning into histo-projections, the deposition of TOF events directly into the image voxels eliminates the need for tracing and/or interpolation operations during the reconstruction. Together with the performance of reconstruction operations directly in image space, this leads to a very efficient implementation of TOF reconstruction algorithms. Furthermore, the resolution properties are not compromised either, since events are placed into the image elements of the desired size from the beginning. Concepts and efficiency of the proposed data partitioning scheme are demonstrated in this work by using the DIRECT approach in conjunction with the row-action maximum-likelihood (RAMLA) algorithm.

Validation of fast-RAMLA in clinical PET

Images using the fast row action maximum likelihood algorithm (fast-RAMLA), which employs half-interpolated sinograms of conventional 3DRAMLA, are immediately generated following positron emission tomography (PET) scanning and are invariably produced in the process of line-of-response RAMLA (LOR-RAMLA) reconstruction. We quantitatively and visually compared the clinical validity of dual time point [(18)F]-FDG imaging with fast-RAMLA and LOR-RAMLA. An International Electrotechnical Commission (IEC) phantom was established in which the ratio of the activities in the hot sphere was set up and a background of 3.8:1 was scanned and reconstructed using both algorithms. The contrast recovery coefficient was then calculated. The clinical study retrospectively analyzed 35 patients (25 men and 10 women; age range 30-84 years; mean age 63.9 years) with confirmed specific pathological lesions or clinical follow-up; 21 of the patients had 51 malignant lesions and 15 had 23 benign lesions. The maximum standard uptake value (SUV(max)) was measured in all lesions using LOR-RAMLA. The maximal counts of all lesions determined manually were divided by the average count of bilateral ventricles and the aortic arch for standardization on fast-RAMLA, and the values were compared with the SUV(max) of LORRAMLA. Inter-observer variation in detection was determined among three radiologists who blindly reviewed and scored 70 maximum intensity projection images from 35 patients reconstructed using LORRAMLA and fast-RAMLA. We identified a quantitative correlation and determined the visual quality of lesion detection between fast-RAMLA and LOR-RAMLA and indicated usefulness and improvement point on fast-RAMLA. Fast-RAMLA can improve the strategy for using dual time point [(18)F] fluorodeoxyglucose positron emission tomography ([(18)F]-FDG-PET) and increase the efficiency of the [(18)F]-FDG-PET scanner.