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Neuroinflammation has been implicated in amyotrophic lateral sclerosis (ALS) and can be visualized using translocator protein (TSPO) radioligands. To become a reliable pharmacodynamic biomarker for ALS multicenter trials, TSPO radioligands have some challenges to overcome. We aimed to investigate whether multicenter data pooling of different TSPO tracers (11C-PBR28 and 18F-DPA714) is feasible, after validation of an established 11C-PBR28 PET pseudo reference analysis technique for 18F-DPA714. Methods: Seven ALS patients from Belgium (58.9 ± 6.7 y old, 5 men and 2 women), 8 healthy volunteers from Belgium (52.1 ± 15.2 y old, 3 men and 5 women), 7 ALS patients from the United States (53.4 ± 9.8 y old, 5 men and 2 women), and 7 healthy volunteers from the United States (54.6 ± 9.6 y old, 4 men and 3 women) from a previously published study underwent dynamic 18F-DPA714 (Leuven, Belgium) or 11C-PBR28 (Boston, Massachusetts) PET/MRI. For 18F-DPA714, maps of total volume of distribution (VT) were compared with SUV ratio (SUVR) images from 40 to 60 min after injection (SUVR40-60) calculated using the pseudo reference regions cerebellum, occipital cortex, and whole brain (WB) without ventricles. For 11C-PBR28, SUVR images from 60 to 90 min after injection using the WB without ventricles were calculated. Results: In line with previous studies, increased 18F-DPA714 uptake (17.0% ± 5.6%) in primary motor cortices was observed in ALS subjects, as measured by both VT and SUVR40-60 approaches. The highest sensitivity was found for SUVR calculated using the WB without ventricles (average cluster, 21.6% ± 0.1%). 18F-DPA714 VT ratio was highly correlated with the SUVR40-60 (r > 0.8, P < 0.001). A similar pattern of increased uptake (average cluster, 20.5% ± 0.5%) in the primary motor cortices was observed in ALS subjects for 11C-PBR28 SUVR calculated using the WB without ventricles. Analysis of the 18F-DPA714 and 11C-PBR28 data together resulted in a more extensive pattern of significantly increased glial activation bilaterally in the primary motor cortices. Conclusion: The same pseudo reference region analysis technique for 11C-PBR28 PET can be extended toward 18F-DPA714 PET. Therefore, in ALS, standardized analysis across these 2 tracers enables pooling of TSPO PET data across multiple centers and increases the power of TSPO as a biomarker for future therapeutic trials. ispartof: JOURNAL OF NUCLEAR MEDICINE vol:61 issue:11 pages:1621-1627 ispartof: location:United States status: published

Improving sensitivity and spatial resolution in small animal Positron Emission Tomography imaging instrumentation constitutes one of the main goals of nuclear imaging research. These parameters are degraded by the presence of gaps between the detectors. The present manuscript experimentally validates our prototype of an edge-less pre-clinical PET system based on a single LYSO:Ce annulus with an inner diameter of 62 mm and 10 outer facets of 26 × 52 mm(2). Scintillation light is read out by arrays of 8 × 8 SiPMs coupled to the facets, using a projection readout of the rows and columns signals. The readout provides accurate Depth of Interaction (DOI). We have implemented a calibration that mitigates the DOI-dependency of the transaxial and axial impact coordinates, and the energy photopeak gain. An energy resolution of 23.4 ± 1.8% was determined. Average spatial resolution of 1.4 ± 0.2 and 1.3 ± 0.4 mm FWHM were achieved for the radial and axial directions, respectively. We found a peak sensitivity of 3.8% at the system center, and a maximum NECR at 40.6 kcps for 0.27 mCi. The image quality was evaluated using reconstructed images of an array of sources and the NEMA image quality phantom was also studied.

[EN] Several research groups are studying organ-dedicated limited angle positron emission tomography (PET) systems to optimize performance-cost ratio, sensitivity, access to the patient, and/or flexibility. Often open systems are considered, typically consisting of two detector panels of various sizes. Such systems provide incomplete sampling due to limited angular coverage and/or truncation, which leads to artifacts in the reconstructed activity images. In addition, these organ-dedicated PET systems are usually stand-alone systems, and as a result, no attenuation information can be obtained from anatomical images acquired in the same imaging session. It has been shown that the use of time-of-flight (TOF) information reduces incomplete data artifacts and enables the joint estimation of the activity and the attenuation factors. In this work, we explore with simple 2-D simulations the performance and stability of a joint reconstruction algorithm, for imaging with a limited angle PET system. The reconstruction is based on the so-called maximum-likelihood attenuation correction factors (MLACF) algorithm and uses linear attenuation coefficients in a known-tissue-class region to obtain absolute quantification. Different panel sizes and different TOF resolutions are considered. The noise propagation is compared to that of MLEM reconstruction with exact attenuation correction (AC) for the same PET system. The results show that with good TOF resolution, images of good visual quality can be obtained. If also a good scatter correction can be implemented, quantitative PET imaging will be possible. Further research, in particular on scatter correction, is required., This work was supported in part by the European Research Council (ERC) through the European Unions Horizon 2020 Research and Innovation Program under Grant 695536; in part by the Research Foundation Flanders (FWO) under Project 12T7118N and Project G062220N; and in part by the NIH Project under Grant 1P41EB017183-01A1.

High welding intensity is an integral part of the refinery pressure vessel manufacturing process. Weld defects are also responsible for a substantial part of the rework requirements, waste and operating costs associated with such manufacturing. Seeking ways to reduce welding defects and improve the efficiency of the manufacturing process is therefore critical for profitability and fulfills customer expectations of product reliability. A problem-solving project applying six sigma principles, and specifically its define, measure, analysis, improve and control methodology, successfully identified, quantified and reduced weld defects in pressure vessel manufacture for the Machine Sazi Arak Company leading to ongoing process improvement gains. Failure modes and effect analysis and customized experiments were able to quantify the impacts of identified root causes on the slag inclusion, lack of fusion and porosity weld defects. This lead to improvement solutions being successfully tested and implemented. These improvement initiatives significantly reduced the average number of the welding repairs required, increased the sigma level of weld defects by up to 19% reduced welding process costs by up to 350% and increased process yield by 1.12%. Consequently, the profitability and efficiency of pressure vessel manufacture was much improved by adopting the six-sigma problem-solving approach.

Positron emission tomography (PET) plays an increasingly important role in research and clinical applications, catalysed by remarkable technical advances and a growing appreciation of the need for reliable, sensitive biomarkers of human function in health and disease. Over the last 30 years, a large amount of the physics and engineering effort in PET has been motivated by the dominant clinical application during that period, oncology. This has led to important developments such as PET/CT, whole-body PET, 3D PET, accelerated statistical image reconstruction, and time-of-flight PET. Despite impressive improvements in image quality as a result of these advances, the emphasis on static, semi-quantitative 'hot spot' imaging for oncologic applications has meant that the capability of PET to quantify biologically relevant parameters based on tracer kinetics has not been fully exploited. More recent advances, such as PET/MR and total-body PET, have opened up the ability to address a vast range of new research questions, from which a future expansion of applications and radiotracers appears highly likely. Many of these new applications and tracers will, at least initially, require quantitative analyses that more fully exploit the exquisite sensitivity of PET and the tracer principle on which it is based. It is also expected that they will require more sophisticated quantitative analysis methods than those that are currently available. At the same time, artificial intelligence is revolutionizing data analysis and impacting the relationship between the statistical quality of the acquired data and the information we can extract from the data. In this roadmap, leaders of the key sub-disciplines of the field identify the challenges and opportunities to be addressed over the next ten years that will enable PET to realise its full quantitative potential, initially in research laboratories and, ultimately, in clinical practice. ispartof: PHYSICS IN MEDICINE AND BIOLOGY vol:66 issue:6 ispartof: location:England status: published

Human ageing is associated with a regional reduction in cerebral neuronal activity as assessed by numerous studies on brain glucose metabolism and perfusion, grey matter (GM) density and white matter (WM) integrity. As glucose metabolism may impact energetics to maintain myelin integrity, but changes in functional connectivity may also alter regional metabolism, we conducted a cross-sectional simultaneous FDG PET/MR study in a large cohort of healthy volunteers with a wide age range, to directly assess the underlying associations between reduced glucose metabolism, GM atrophy and decreased WM integrity in a single ageing cohort. In 94 healthy subjects between 19.9 and 82.5 years (mean 50.1 ± 17.1; 47 M/47F, MMSE ≥ 28), simultaneous FDG-PET, structural MR and diffusion tensor imaging (DTI) were performed. Voxel-wise associations between age and grey matter (GM) density, RBV partial-volume corrected (PVC) glucose metabolism, white matter (WM) fractional anisotropy (FA) and mean diffusivity (MD), and age were assessed. Clusters representing changes in glucose metabolism correlating significantly with ageing were used as seed regions for tractography. Both linear and quadratic ageing models were investigated. An expected age-related reduction in GM density was observed bilaterally in the frontal, lateral and medial temporal cortex, striatum and cerebellum. After PVC, relative FDG uptake was negatively correlated with age in the inferior and midfrontal, cingulate and parietal cortex and subcortical regions, bilaterally. FA decreased with age throughout the entire brain WM. Four white matter tracts were identified connecting brain regions with declining glucose metabolism with age. Within these, relative FDG uptake in both origin and target clusters correlated positively with FA (0.32 ≤ r ≤ 0.71) and negatively with MD (− 0.75 ≤ r ≤ − 0.41). After appropriate PVC, we demonstrated that regional cerebral glucose metabolic declines with age and that these changes are related to microstructural changes in the interconnecting WM tracts. The temporal course and potential causality between ageing effects on glucose metabolism and WM integrity should be further investigated in longitudinal cohort PET/MR studies.

A data-driven method is proposed for rigid motion estimation directly from time-of-flight (TOF)-positron emission tomography (PET) emission data. Rigid motion parameters (translations and rotations) are estimated from the first and second moments of the emission data masked in a spherical volume. The accuracy of the method is analyzed on 3D analytical simulations of the PET-SORTEO brain phantom, and subsequently tested on18F-FDG as well as11C-PIB brain datasets acquired on a TOF-PET/CT scanner. The estimated inertia-based motion is later compared to rigid motion parameters obtained by directly registering the short frame backprojections. We find that the method provides sub mm/degree accuracies for the estimated rigid motion parameters for counts corresponding to typical 0.5 s, 1 s, and 2 s18F-FDG brain scans, with the current TOF resolutions clinically available. The method provides robust motion estimation for different types of patient motion, most notably for a continuous patient motion case where conventional frame-based approaches which rely on little to no intra-frame motion of short time intervals could fail. The method relies on the detection of stable eigenvectors for accurate motion estimation, and a monitoring of this condition can reveal time-frames where the motion estimation is less accurate, such as in dynamic PET studies.

[EN] This study evaluates the performance of the Bruker positron emission tomograph (PET) insert combined with a BioSpec 70/30 USR magnetic resonance imaging (MRI) scanner using the manufacturer acceptance protocol and the NEMA NU 4-2008 for small animal PET. The PET insert is made of 3 rings of 8 monolithic LYSO crystals (50 x 50 x 10 mm(3)) coupled to silicon photomultipliers (SiPM) arrays, conferring an axial and transaxial FOV of 15 cm and 8 cm. The MRI performance was evaluated with and without the insert for the following radiofrequency noise, magnetic field homogeneity and image quality. For the PET performance, we extended the NEMA protocol featuring system sensitivity, count rates, spatial resolution and image quality to homogeneity and accuracy for quantification using several MRI sequences (RARE, FLASH, EPI and UTE). The PET insert does not show any adverse effect on the MRI performances. The MR field homogeneity is well preserved (Diameter Spherical Volume, for 20 mm of 1.98 +/- 4.78 without and -0.96 +/- 5.16 Hz with the PET insert). The PET insert has no major effect on the radiofrequency field. The signal-to-noise ratio measurements also do not show major differences. Image ghosting is well within the manufacturer specifications (, We acknowledge the KU Leuven core facility, Molecular Small Animal Imaging Center (MoSAIC), for their support with obtaining scientific data presented in this paper. This work was supported by Stichting tegen Kanker (2015-145, Christophe M. Deroose) and Hercules foundation (AKUL/13/029, Uwe Himmelreich) for the purchase of the PET and MRI equipment respectively. The work was supported by the following funding organizations: European Commission for the PANA project (H2020-NMP-2015-two-stage, grant 686009) and the European ERA-NET project 'CryptoView' (3rd call of the FP7 program Infect-ERA).

A data-driven method is proposed for rigid motion estimation directly from TOF-PET emission data, and tested on 18F-FDG as well as 11C_PIB brain datasets. We observe the method to be robust against continuous patient motion where conventional frame based approaches would fail. With a postfiltering of the estimated motion trace, sub-second traces of patient motion can be captured.

Importance During a time with the potential for novel treatment strategies, early detection of disease manifestations at an individual level in presymptomatic carriers of a hexanucleotide repeat expansion in the C9orf72 gene (preSxC9) is becoming increasingly relevant. Objectives To evaluate changes in glucose metabolism before symptom onset of amyotrophic lateral sclerosis or frontotemporal dementia in preSxC9 using simultaneous fluorine 18–labeled fluorodeoxyglucose ([18F]FDG positron emission tomographic (PET) and magnetic resonance imaging as well as the mutation’s association with clinical and fluid biomarkers. Design, Setting, and Participants A prospective, case-control study enrolled 46 participants from November 30, 2015, until December 11, 2018. The study was conducted at the neuromuscular reference center of the University Hospitals Leuven, Leuven, Belgium. Main Outcomes and Measures Neuroimaging data were spatially normalized and analyzed at the voxel level at a height threshold of P

BACKGROUND: Yoga is increasingly popular worldwide with several physical and mental benefits, but the underlying neurobiology remains unclear. Whereas many studies have focused on pure meditational aspects, the triad of yoga includes meditation, postures, and breathing. We conducted a cross-sectional study comparing experienced yoga practitioners to yoga-naive healthy subjects using a multiparametric 2 × 2 design with simultaneous positron emission tomography/magnetic resonance (PET/MR) imaging. METHODS: 18F-FDG PET, morphometric and diffusion tensor imaging, resting state fMRI, and MR spectroscopy were acquired in 10 experienced (4.8 ± 2.3 years of regular yoga experience) yoga practitioners and 15 matched controls in rest and after a single practice (yoga practice and physical exercise, respectively). RESULTS: In rest, decreased regional glucose metabolism in the medial temporal cortex, striatum, and brainstem was observed in yoga practitioners compared to controls (p < 0.0001), with a significant inverse correlation of resting parahippocampal and brainstem metabolism with years of regular yoga practice (ρ < - 0.63, p < 0.05). A single yoga practice resulted in significant hypermetabolism in the cerebellum (p < 0.0001). None of the MR measures differed, both at rest and after intervention. CONCLUSIONS: Experienced yoga practitioners show regional long-term decreases in glucose metabolism related to years of practice. To elucidate a potential causality, a prospective longitudinal study in yoga-naive individuals is warranted. ispartof: EJNMMI RESEARCH vol:10 issue:1 ispartof: location:Germany status: published

About six years ago, it was shown with experiments and with mathematical analysis that with the introduction of time-of-flight (TOF), the data acquired with positron emission tomography (PET) were significantly richer than before [1] – [3] . In particular, it was found that if the tracer distribution is wider than the TOF uncertainty, the TOF-PET data provide enough information to jointly estimate the activity image and the attenuation sinogram up to a global scale factor. Since then, many algorithms have been proposed to exploit this feature to perform attenuation correction without additional transmission measurements or to improve available attenuation images or sinograms. An excellent recent review of these methods has been published by Berker and Li [4] . Some of these methods rely on the emission data only, other methods use additional information to determine the scale factor and/or to suppress noise propagation. This additional information can be obtained from an anatomical image acquired with the MR-component in a PET/MR system or with the CT-component in a PET/CT system.

Joint activity and attenuation reconstruction methods from time of flight (TOF) positron emission tomography (PET) data provide an effective solution to attenuation correction when no (or incomplete/inaccurate) information on the attenuation is available. One of the main barriers limiting their use in clinical practice is the lack of validation of these methods on a relatively large patient database. In this contribution, we aim at validating the activity reconstructions of the maximum likelihood activity reconstruction and attenuation registration (MLRR) algorithm on a whole-body patient data set. Furthermore, a partial validation (since the scale problem of the algorithm is avoided for now) of the maximum likelihood activity and attenuation reconstruction (MLAA) algorithm is also provided. We present a quantitative comparison of the joint reconstructions to the current clinical gold-standard maximum likelihood expectation maximization (MLEM) reconstruction with CT-based attenuation correction. Methods: The whole-body TOF-PET emission data of each patient data set is processed as a whole to reconstruct an activity volume covering all the acquired bed positions, which helps to reduce the problem of a scale per bed position in MLAA to a global scale for the entire activity volume. Three reconstruction algorithms are used: MLEM, MLRR and MLAA. A maximum likelihood (ML) scaling of the single scatter simulation (SSS) estimate to the emission data is used for scatter correction. The reconstruction results are then analyzed in different regions of interest. Results: The joint reconstructions of the whole-body patient data set provide better quantification in case of PET and CT misalignments caused by patient and organ motion. Our quantitative analysis shows a difference of -4.2% (±2.3%) and -7.5% (±4.6%) between the joint reconstructions of MLRR and MLAA compared to MLEM, averaged over all regions of interest, respectively. Conclusion: Joint activity and attenuation estimation methods provide a useful means to estimate the tracer distribution in cases where CT-based attenuation images are subject to misalignments or are not available. With an accurate estimate of the scatter contribution in the emission measurements, the joint TOF-PET reconstructions are within clinical acceptable accuracy.

Scatter correction is typically done using a simulation of the single scatter, which is then scaled to account for multiple scatters and other possible model mismatches. This scaling factor is determined by fitting the simulated scatter sinogram to the measured sinogram, using only counts measured along LORs that do not intersect the patient body, i.e. 'scatter-tails'. Extending previous work, we propose to scale the scatter with a plane dependent factor, which is determined as an additional unknown in the maximum likelihood (ML) reconstructions, using counts in the entire sinogram rather than only the 'scatter-tails'. The ML-scaled scatter estimates are validated using a Monte-Carlo simulation of a NEMA-like phantom, a phantom scan with typical contrast ratios of a (68)Ga-PSMA scan, and 23 whole-body (18)F-FDG patient scans. On average, we observe a 12.2% change in the total amount of tracer activity of the MLEM reconstructions of our whole-body patient database when the proposed ML scatter scales are used. Furthermore, reconstructions using the ML-scaled scatter estimates are found to eliminate the typical 'halo' artifacts that are often observed in the vicinity of high focal uptake regions. ispartof: Physics in Medicine and Biology vol:62 issue:16 pages:6515-6531 ispartof: location:England status: published

Additional file 1:. Supplementary Material and Methods. Supplementary Results. Figure S1 Average normalized FDG uptake for the control and yoga group, at rest and post intervention. Supplementary TABLE 1. Statistical parametric mapping analysis for decreased relative glucose metabolism in the yoga group compared to controls, at rest. Contrast: yoga < controls. Supplementary TABLE 2. Statistical parametric mapping analysis for differences in glucose metabolism at rest and after a single yoga practice in the yoga group. Contrast: after yoga > at rest .

In this work, we propose a maximum likelihood method to compute geometric and efficiency related corrections from PET emission data. In order to reduce the number of unknowns being estimated, a component and crystal based model is used for the geometric and efficiency based corrections, respectively. In a long acquisition of a uniform phantom scan, we show how inaccuracies in the projector or the scanner geometry can create observable artefacts in the reconstructions. Once the geometric and efficiency related corrections are re-estimated with our in-house projector the artifacts are eliminated.

With increasing improvements in the time of flight (TOF) resolution of positron emission tomography (PET) scanners, an accurate model of the TOF measurements is becoming increasingly important. This work considers two parameters of the TOF kernel; the relative positioning of the timing data-bins and the timing resolution along each line of response (LOR). Similar to an existing data-driven method, we assume that any shifts of data-bins along lines of response can be modelled as differences between crystal timing offsets. Inspired by this, timing resolutions of all LORs are modelled as the hypotenuse of timing resolutions of the crystal-pairs in coincidence. Furthermore, in order to mitigate the influence of potential inaccuracies of detector-pair sensitivities on crystal timing resolutions, relative LOR sensitivities are modelled as the product of efficiency factors for the two crystals in coincidence. We validate estimating maps of crystal timing offsets, timing resolutions and efficiencies from the emission data using noisy simulations of a brain phantom. Results are shown for phantom and patient data scanned on clinically available TOF-PET scanners. We find that the estimation of crystal timing resolutions is more sensitive to the data statistics than the estimation of crystal timing offsets. As a result, estimation of crystal timing properties could either be limited to high count emission data, or be obtained utilizing additional regularizations on the estimates. Using a more accurate model of the TOF acquisition, improvements are observed in standard activity reconstructions as well as joint reconstructions of activity and attenuation. ispartof: IEEE TRANSACTIONS ON MEDICAL IMAGING vol:37 issue:2 pages:590-603 ispartof: location:United States status: Published online

In this work, we present a new reconstruction-based approach to derive the whole-blood arterial input function (RDIF) directly from PET raw data of PET/MRI acquisitions. The approach is evaluated based on 3D simulations and two dynamic [18F]FDG data sets, acquired on a SIGNA PET/MRI, where arterial blood sampling was available.

In this work, we propose a method to compute TOF resolutions from TOF-PET emission data using a crystal model. For each line of response, the TOF resolutions were computed as the hypotenuse of crystal timing resolutions of the crystals in coincidence. We find that the accuracy of the crystal timing resolutions highly depends on the average count per crystal. In the phantom study, we observe a small global shift in the TOF-resolution, which we believe to be due to the scans being performed at different count rates. However, the whole body patient study shows that the count rate possibly is not the only factor influencing the crystal timing properties. The effect of the TOF resolution on joint reconstructions (and more so on standard reconstructions) seems to be limited as long as the mean crystal TOF resolution is modelled during reconstruction.

Time-of-flight (TOF) PET data provide an effective means for attenuation correction (AC) when no (or incomplete or inaccurate) attenuation information is available. Since MR scanners provide little information on photon attenuation of different tissue types, AC in hybrid PET/MR scanners has always been challenging. In this contribution, we aim at validating the activity reconstructions of the maximum-likelihood ordered-subsets activity and attenuation (OSAA) reconstruction algorithm on a patient brain data set. We present a quantitative comparison of joint reconstructions with the current clinical gold standard-ordered-subsets expectation maximization-using CT-based AC in PET/CT, as well as the current state of the art in PET/MR, that is, zero time echo (ZTE)-based AC. Methods: The TOF PET emission data were initially used in a preprocessing stage to estimate crystal maps of efficiencies, timing offsets, and timing resolutions. Applying these additional corrections during reconstructions, OSAA, ZTE-based, and the vendor-provided atlas-based AC techniques were analyzed and compared with CT-based AC. In our initial study, we used the CT-based estimate of the expected scatter and later used the ZTE-based and OSAA attenuation estimates to compute the expected scatter contribution of the data during reconstructions. In all reconstructions, a maximum-likelihood scaling of the single-scatter simulation estimate to the emission data was used for scatter correction. The reconstruction results were analyzed in the 86 segmented regions of interest of the Hammers atlas. Results: Our quantitative analysis showed that, in practice, a tracer activity difference of +0.5% (±2.1%) and +0.1% (±2.3%) could be expected for the state-of-the-art ZTE-based and OSAA AC methods, respectively, in PET/MR compared with the clinical gold standard in PET/CT. Conclusion: Joint activity and attenuation estimation methods can provide an effective solution to the challenging AC problem for brain studies in hybrid TOF PET/MR scanners. With an accurate TOF-based (timing offsets and timing resolutions) calibration, and similar to the results of the state-of-the-art method in PET/MR, regional errors of joint TOF PET reconstructions are within a few percentage points. ispartof: JOURNAL OF NUCLEAR MEDICINE vol:60 issue:11 pages:1649-1655 ispartof: location:United States status: published

This paper presents new data driven methods for the time of flight (TOF) calibration of positron emission tomography (PET) scanners. These methods are derived from the consistency condition for TOF PET, they can be applied to data measured with an arbitrary tracer distribution and are numerically efficient because they do not require a preliminary image reconstruction from the non-TOF data. Two-dimensional simulations are presented for one of the methods, which only involves the two first moments of the data with respect to the TOF variable. The numerical results show that this method estimates the detector timing offsets with errors that are larger than those obtained via an initial non-TOF reconstruction, but remain smaller than [Formula: see text] of the TOF resolution and thereby have a limited impact on the quantitative accuracy of the activity image estimated with standard maximum likelihood reconstruction algorithms.

In this article, we evaluate Parallel Level Sets (PLS) and Bowsher's method as segmentation-free anatomical priors for regularized brain positron emission tomography (PET) reconstruction. We derive the proximity operators for two PLS priors and use the EM-TV algorithm in combination with the first order primal-dual algorithm by Chambolle and Pock to solve the non-smooth optimization problem for PET reconstruction with PLS regularization. In addition, we compare the performance of two PLS versions against the symmetric and asymmetric Bowsher priors with quadratic and relative difference penalty function. For this aim, we first evaluate reconstructions of 30 noise realizations of simulated PET data derived from a real hybrid positron emission tomography/magnetic resonance imaging (PET/MR) acquisition in terms of regional bias and noise. Second, we evaluate reconstructions of a real brain PET/MR data set acquired on a GE Signa time-of-flight PET/MR in a similar way. The reconstructions of simulated and real 3D PET/MR data show that all priors were superior to post-smoothed maximum likelihood expectation maximization with ordered subsets (OSEM) in terms of bias-noise characteristics in different regions of interest where the PET uptake follows anatomical boundaries. Our implementation of the asymmetric Bowsher prior showed slightly superior performance compared with the two versions of PLS and the symmetric Bowsher prior. At very high regularization weights, all investigated anatomical priors suffer from the transfer of non-shared gradients. ispartof: IEEE Transactions on Medical Imaging vol:37 issue:2 pages:590-603 ispartof: location:United States status: published

The accuracy of joint reconstruction methods using time of flight (TOF) positron emission tomography (PET) data, highly depends on an accurate model of the TOF measurements. In this contribution we consider the relative positioning of the TOF data-bins along each line of response (LOR) from TOF-PET emission data. Similar to an existing data-driven method, we assume that any shifts of TOF data-bins along lines of response can be modelled as differences between crystal timing offsets. Results are shown with and without accounting for the estimated TOF shifts for phantom and patient brain scans.

In positron emission tomography (PET), attenuation correction is typically done based on information obtained from transmission tomography. Recently, it has been shown that stable maximum-likelihood reconstruction of both the attenuation and the activity from time-of-flight (TOF) PET emission data is possible. Mathematical analysis revealed that the TOF-PET data determine the attenuation correction factors uniquely except for a scale factor. Here, we propose a maximum likelihood algorithm (called MLACF) that jointly estimates the image of the activity distribution and the sinogram with the attenuation factors. This method avoids the reconstruction of the attenuation image. If additive contributions (such as scatter and randoms) can be ignored, the algorithm even does not require storage of the attenuation correction factors. However, in contrast, this algorithm does not impose the consistency of the attenuation sinogram, which may result in increased noise propagation. This paper presents the derivation of the algorithm, an (incomplete) theoretical analysis of the corresponding likelihood function, and first results on 2D and 3D simulations.

The maximum likelihood attenuation correction factors (MLACF) algorithm has been developed to calculate the maximum-likelihood estimate of the activity image and the attenuation sinogram in time-of-flight (TOF) positron emission tomography, using only emission data without prior information on the attenuation. We consider the case of a Poisson model of the data, in the absence of scatter or random background. In this case the maximization with respect to the attenuation factors can be achieved in a closed form and the MLACF algorithm works by updating the activity. Despite promising numerical results, the convergence of this algorithm has not been analysed. In this paper we derive the algorithm and demonstrate that the MLACF algorithm monotonically increases the likelihood, is asymptotically regular, and that the limit points of the iteration are stationary points of the likelihood. Because the problem is not convex, however, the limit points might be saddle points or local maxima. To obtain some empirical insight into the latter question, we present data obtained by applying MLACF to 2D simulated TOF data, using a large number of iterations and different initializations. ispartof: Physics in Medicine and Biology vol:59 issue:4 pages:1073-95 ispartof: location:England status: published

For quantitative tracer distribution in positron emission tomography, attenuation correction is essential. In a hybrid PET/CT system the CT images serve as a basis for generation of the attenuation map, but in PET/MR, the MR images do not have a similarly simple relationship with the attenuation map. Hence attenuation correction in PET/MR systems is more challenging. Typically either of two MR sequences are used: the Dixon or the ultra-short time echo (UTE) techniques. However these sequences have some well-known limitations. In this study, a reconstruction technique based on a modified and optimized non-TOF MLAA is proposed for PET/MR brain imaging. The idea is to tune the parameters of the MLTR applying some information from an attenuation image computed from the UTE sequences and a T1w MR image. In this MLTR algorithm, an [Formula: see text] parameter is introduced and optimized in order to drive the algorithm to a final attenuation map most consistent with the emission data. Because the non-TOF MLAA is used, a technique to reduce the cross-talk effect is proposed. In this study, the proposed algorithm is compared to the common reconstruction methods such as OSEM using a CT attenuation map, considered as the reference, and OSEM using the Dixon and UTE attenuation maps. To show the robustness and the reproducibility of the proposed algorithm, a set of 204 [(18)F]FDG patients, 35 [(11)C]PiB patients and 1 [(18)F]FET patient are used. The results show that by choosing an optimized value of [Formula: see text] in MLTR, the proposed algorithm improves the results compared to the standard MR-based attenuation correction methods (i.e. OSEM using the Dixon or the UTE attenuation maps), and the cross-talk and the scale problem are limited. journal_title: Physics in Medicine and Biology article_type: paper article_title: Optimized MLAA for quantitative non-TOF PET/MR of the brain copyright_information: © 2016 Institute of Physics and Engineering in Medicine license_information: cc-by Original content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. date_received: 2016-05-13 date_accepted: 2016-11-03 date_epub: 2016-12-02 ispartof: Physics in Medicine and Biology vol:61 issue:24 pages:8854-8874 ispartof: location:England status: published

In this work, we propose a plane-dependent maximum likelihood (ML) scatter scale estimation from the emission measurements. The scatter scales obtained are validated using a Monte Carlo simulation of a NEMA-like phantom, and results are shown from two whole-body patient scans.

In positron emission tomography (PET), a quantitative reconstruction of the tracer distribution requires accurate attenuation correction. We consider situations where a direct measurement of the attenuation coefficient of the tissues is not available or is unreliable, and where one attempts to estimate the attenuation sinogram directly from the emission data by exploiting the consistency conditions that must be satisfied by the non-attenuated data. We show that in time-of-flight PET, the attenuation sinogram is determined by the emission data except for a constant and that its gradient can be estimated efficiently using a simple analytic algorithm. The stability of the method is illustrated numerically by means of a 2D simulation. ispartof: Physics in Medicine and Biology vol:57 issue:4 pages:885-99 ispartof: location:England status: published

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image or the attenuation sinogram from time-of-flight (TOF) positron emission tomography (PET) data. In this contribution, we propose a method that addresses the possible alignment problem of the TOF-PET emission data and the computed tomography (CT) attenuation data, by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximise the likelihood of the TOF emission sinogram. The algorithm is slow to converge, but some acceleration could be achieved by using Nesterov's momentum method and by applying a multi-resolution scheme for the non-rigid displacement estimation. The latter also helps to avoid local optima, although convergence to the global optimum cannot be guaranteed. The results are evaluated on 2D and 3D simulations as well as a respiratory gated clinical scan. Our experiments indicate that the proposed method is able to correct for possible misalignment of the CT-based attenuation image, and is therefore a very promising approach to suppressing attenuation artefacts in clinical PET/CT. When applied to respiratory gated data of a patient scan, it produced deformations that are compatible with breathing motion and which reduced the well known attenuation artefact near the dome of the liver. Since the method makes use of the energy-converted CT attenuation image, the scale problem of joint reconstruction is automatically solved.

A rigid motion correction technique is applied to both PET and CT data from the Siemens mCT PET/CT scanner. Motion was applied to a Hoffman brain phantom during both the CT and PET scans, as well as between them. The motion data, which was tracked by an external motion tracker, was used to correct the motion corrupted tomographic data during reconstruction. The motion corrected CT reconstruction was used for attenuation correction in the PET reconstruction. The subsequent reconstructions are compared to scans taken without motion to show the effectiveness of the motion correction.

Positron emission tomography (PET) is a valuable clinical tool for cancer staging and monitoring response to treatment, but it is limited by its relatively poor resolution and high noise level. In this study, we investigated the impact of using anatomical information, either during or post reconstruction, for PET imaging of sub-cm lung nodules. The XCAT phantom with four inserted lung lesions (diameter: 6–12 mm, contrast: 4:1) was used to simulate twenty 3-minute [18F]-FDG PET thorax scans on a Siemens mCT. Maximum a posteriori reconstruction with an anatomical prior was compared to ordered-subsets expectation-maximization with resolution recovery (with and without the use of time-of-flight (TOF) information). Furthermore, an anatomy-guided partial volume correction (PVC) technique was applied to each of these reconstructions. Adding TOF information improved both the convergence and the contrast-to-noise ratio (CNR). The anatomical prior further improved the CNR at the cost of a systematic bias. The template-based PVC method improved the quantitative accuracy for all reconstructions, within a clinically acceptable number of iterations. By combining the anatomical prior with the anatomy-guided PVC technique, quantitatively accurate, high-contrast PET imaging could be achieved even for the smallest lung nodule (6 mm), provided that the nodule was visible on CT and accurate respiratory motion correction has been performed.

In positron emission tomography a scatter estimate is calculated prior to image reconstruction and is then added at each MLEM iteration to the estimated true counts to yield the estimated prompts. The absolute scale of the scatter is usually estimated by matching the scatter estimate to the data for those lines of response that do not intersect the patient. The goal of this work is to explore alternatives to this tail fitting method. Pursuing the method introduced by V. Panin at the 2012 IEEE Medical Imaging Conference for the case with known attenuation, we estimate the scatter scaling factor as an additional voxel, which is updated at each iteration at the same time as the activity. This method is extended for applications with unknown attenuation. This preliminary study uses a single-scatter estimate and simulated 2D data.

In this work, we demonstrate a framework in which the gated TOF-PET emission data are used to reconstruct a single activity image (which is corrected for attenuation), together with motion parameters that deform the activity reconstruction (of the reference frame) to each of the frames. We compare the reconstructions to independent and registered (post-reconstruction) MLACF reconstructions of each frame. We propose a joint estimation method that avoids selecting a reference frame and provides low bias and variance compared to methods that select a reference frame from among the gated frames. Reconstruction results are also shown for the 3D breathing XCAT phantom.

Previously, methods have been proposed for the direct reconstruction of the activity in a set of regions-of-interest (ROI), given the raw emission data and the locations of these ROIs in image space. These methods work well if the ROIs are well aligned, but artifacts may result if the alignment is poor. In this contribution, we propose a maximum likelihood reconstruction algorithm that estimates ROI-values where ROIs are available, and that applies standard voxel-based ML-reconstruction elsewhere. In addition, it jointly estimates the alignment of the ROIs to the image being reconstructed. The activity is updated with the standard MLEM update, the alignment with a least squares registration algorithm. A preliminary evaluation with simple 2D simulations and two microPET rat brain scans yielded promising results.

To date, attenuation correction of gated PET emission data remains a challenge. Joint activity and attenuation estimation methods may contribute to solving this challenge. In this work, we demonstrate a framework in which the gated PET activity and attenuation images are jointly reconstructed and then registered to a reference frame by a joint registration approach. The method is studied and compared to common approaches by means of 2D and 3D simulations.

Identification of myocardial infarction (MI) by imaging is critical for clinical management of ischemic heart disease. Iodine-123-labeled hypericin (¹²³I-Hyp) is a new potent infarct avid agent. We sought to compare target selectivity and organ distribution between ¹²³I-Hyp and the myocardial perfusion agent, technetium-99m-labeled hexakis [2-methoxy isobutyl isonitrile] ((99m)Tc-Sestamibi) in rabbits with acute MI. Hypericin was radiolabeled with I using iodogen as oxidant, and (99m)Tc-Sestamibi was prepared from a commercial kit and radioactive sodium pertechnetate. Rabbits (n = 6) with 24-hour-old MI received ¹²³I-Hyp intravenously and received (99m)Tc-Sestamibi 9 hours later. They were studied by dual-isotope simultaneous acquisition micro single photon emission computed tomography/computed tomography (DISA-μSPECT/CT), tissue gamma counting (TGC), autoradiography, and histology. After purification, ¹²³I-Hyp was obtained with radiochemical purity around 99%. DISA-μSPECT/CT images showed ¹²³I-Hyp retention in infarcted but not in normal myocardium. By TGC, accumulation values reached 1.175 ± 0.096 percentage of injected dose per gram (%ID/g) and 0.028 ± 0.007%ID/g in infarcted myocardium and normal myocardium with high tracer concentration in liver, intestines, and gallbladder. (99m)Tc-Sestamibi was prepared with radiochemical purity over 95%. DISA-μSPECT/CT showed no accumulation in MI and high initial radioactivity levels in normal myocardium that were rapidly cleared as confirmed by TGC (0.011 ± 0.003%ID/g). Liver and intestines were clearly visualized. By TGC, gallbladder and kidneys show moderate (99m)Tc-Sestamibi uptake. The selectivity of ¹²³I-Hyp for infarcted myocardium and (99m)Tc-Sestamibi for normal myocardium was confirmed. ¹²³I-Hyp distribution in rabbits is characterized by hepatobiliary excretion. (99m)Tc-Sestamibi undergoes hepatorenal elimination.

Previously, maximum-likelihood methods have been proposed to jointly estimate the activity image and the attenuation image (or the attenuation sinogram) from TOF-PET data. In this contribution, we propose a method that addresses the same problem for TOF-PET/CT by combining reconstruction and registration. The method, called MLRR, iteratively reconstructs the activity image while registering the available CT-based attenuation image, so that the pair of activity and attenuation images maximize the likelihood of the TOF emission sinogram. The algorithm is evaluated on 2D and 3D simulations. © 2013 IEEE. ispartof: 2013 IEEE NUCLEAR SCIENCE SYMPOSIUM AND MEDICAL IMAGING CONFERENCE (NSS/MIC) ispartof: 60th IEEE Nuclear Science Symposium (NSS) / Medical Imaging Conference (MIC) / 20th International Workshop on Room-Temperature Semiconductor X-ray and Gamma-ray Detectors location:Seoul: SOUTH KOREA date:27 Oct - 2 Nov 2013 status: published

In PET-CT the axial length of image reconstruction is defined by the CT scan, which delivers an axial extend-dependent radiation dose. The beginning and end scanning points for CT and therefore PET scans are typically chosen in such a way that the PET scan is performed with a particular number of beds. While PET bed overlapping is optimized to achieve uniform image sensitivity, the whole volume edge planes suffer from low sensitivity, since only direct plane LORs are available from the acquisition. This problem can be solved through object over scanning by additional bed acquisitions. This does not result in an additional PET radiation dose. Still, the edge planes will have lower sensitivity due to the absence of oblique LOR attenuation factors. ACFs are necessary for sensitivity restoration of oblique LORs and are accumulated over the attenuation map image beyond CT scanning points. Recent theoretical investigations concluded that both activity and attenuation distributions can be obtained from PET emission TOF data alone with knowledge of the sinogram scaling parameter. In this work we consider an easier problem for the above-mentioned application. ACFs, converted to 511 energy units, are partially known and scatter distribution is already estimated based on direct plane LORs. The iterative algorithm to reconstruct only the emission image, with estimation of partially unknown ACFs, is presented. The estimation of ACFs is a sub-product of emission activity reconstruction. The algorithm is of a similar complexity to commonly used ML-EM. Initial investigations of experimental data show that partial ACF knowledge restores attenuation information necessary for the uniform sensitivity of PET reconstructed volume edge planes.

In positron emission tomography (PET), an accurate quantitative reconstruction of the tracer distribution requires taking into account the attenuation of the photons by the tissues. The spatial distribution of the attenuation coefficient (the attenuation image) is usually estimated by means of a CT scan, extrapolated to the required photon energy of 511 keV, and forward projected to obtain the attenuation sinogram. We consider applications where this external information about the attenuation is unavailable, or inaccurate due for instance to patient motion between the transmission scan and the emission scan. In such a case the attenuation must be estimated from the emission data only. Previous studies have shown that time-of flight (TOF) data contain significant information on the attenuation. Recently, we gave an accurate characterization of this property by proving that the attenuation sinogram is determined, up to a constant multiplicative factor, by the 2D TOF data and that it can be calculated using an efficient analytic algorithm. The present paper extends this work to 3D TOF PET. I