[en] PET scanner design and exploitation may result in only partial information in sinogram azimuthal and radial content. Gaps between the detector blocks or malfunctioning hardware are typical causes for such incomplete data sampling. The iterative reconstruction algorithms straightforwardly use the available portion of data. Contrary to this, the commonly used analytical algorithms such as FORE + FBP require all data. In TOF, data are transaxially redundant and the exact interpolation of data can be achieved. In previous work we used transaxial TOF consistency conditions to restore fine azimuthal sampling of mashed sinograms of high count data to evaluate resolution performance. In this work we explore block structure related missing data and consider low count scans. Here not all radial information is available for a given azimuthal view and vice versa. The usage of John's equation based Consistency Conditions (CC) can then be advantageous due to locality. (orig.)

[en] LSO scintillators (Lu_2Sio_5:Ce) have a background radiation which originates from the isotope Lu-176 that is present in natural occurring lutetium. The decay that occurs in this isotope is a beta decay that is in coincidence with cascade gamma emissions with energies of 307,202 and 88 keV. The coincidental nature of the beta decay with the gamma emissions allow for separation of emission data originating from a positron annihilation event from transmission type data from the Lu-176 beta decay. By using the time of flight information, and information of the chord length between two LSO pixels in coincidence as a result of a beta emission and emitted gamma, a second time window can be set to observe transmission events simultaneously to emission events. Using the time when the PET scanner is not actively acquiring positron emission data, a continuous blank can be acquired and used to reconstruct a transmission image. With this blank and the measured transmission data, a transmission image can be reconstructed. This reconstructed transmission image can be used to perform emission data corrections such as attenuation correction and scatter corrections or starting images for algorithms that estimate emission and attenuation simultaneously. It is observed that the flux of the background activity is high enough to create useful transmission images with an acquisition time of 10 min. (paper)

[en] A new data handling method is presented for improving the image noise distribution and reducing bias when reconstructing very short frames from low count dynamic PET acquisition. The new method termed ‘Complementary Frame Reconstruction’ (CFR) involves the indirect formation of a count-limited emission image in a short frame through subtraction of two frames with longer acquisition time, where the short time frame data is excluded from the second long frame data before the reconstruction. This approach can be regarded as an alternative to the AML algorithm recently proposed by Nuyts et al, as a method to reduce the bias for the maximum likelihood expectation maximization (MLEM) reconstruction of count limited data. CFR uses long scan emission data to stabilize the reconstruction and avoids modification of algorithms such as MLEM. The subtraction between two long frame images, naturally allows negative voxel values and significantly reduces bias introduced in the final image. Simulations based on phantom and clinical data were used to evaluate the accuracy of the reconstructed images to represent the true activity distribution. Applicability to determine the arterial input function in human and small animal studies is also explored. In situations with limited count rate, e.g. pediatric applications, gated abdominal, cardiac studies, etc., or when using limited doses of short-lived isotopes such as "1"5O-water, the proposed method will likely be preferred over independent frame reconstruction to address bias and noise issues. (paper)

[en] This paper explores fast reconstruction strategies for 3D time-of-flight (TOF) positron emission tomography (PET), based on 2D data rebinning. Starting from pre-corrected 3D TOF data, a rebinning algorithm estimates for each transaxial slice the 2D TOF sinogram that would have been acquired by a single-ring scanner. The rebinned sinograms can then be reconstructed using any algorithm for 2D TOF reconstruction. We introduce TOF-FORE, an approximate rebinning algorithm obtained by extending the Fourier rebinning method for non-TOF data. In addition, we identify two partial differential equations that must be satisfied by consistent 3D TOF data, and use them to derive exact rebinning algorithms and to characterize the degree of the approximation in TOF-FORE. Numerical simulations demonstrate that TOF-FORE is more accurate than two different TOF extensions of the single-slice rebinning method, and suggest that TOF-FORE will be a valuable tool for practical TOF PET in the range of axial apertures and time resolutions typical of current scanners

[en] 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. (paper)

[en] Non-proportionality between energy deposition and scintillation light production in a scintillator and transport of scintillation photons in the detector have been introduced in a Geant4-based simulation code. Simulation and experimental results were compared for samples of LSO detectors: absolute detector efficiency and energy resolution obtained from simulation are consistent with the experimental data. We also studied the average path length of scintillation photons in the detector and its contribution to the time resolution

[en] Whole-body PET/CT scanners are important clinical and research tools to study tracer distribution throughout the body. In whole-body studies, respiratory motion results in image artifacts. We have previously demonstrated for brain imaging that, when provided with accurate motion data, event-by-event correction has better accuracy than frame-based methods. Therefore, the goal of this work was to develop a list-mode reconstruction with novel physics modeling for the Siemens Biograph mCT with event-by-event motion correction, based on the MOLAR platform (Motion-compensation OSEM List-mode Algorithm for Resolution-Recovery Reconstruction). Application of MOLAR for the mCT required two algorithmic developments. First, in routine studies, the mCT collects list-mode data in 32 bit packets, where averaging of lines-of-response (LORs) by axial span and angular mashing reduced the number of LORs so that 32 bits are sufficient to address all sinogram bins. This degrades spatial resolution. In this work, we proposed a probabilistic LOR (pLOR) position technique that addresses axial and transaxial LOR grouping in 32 bit data. Second, two simplified approaches for 3D time-of-flight (TOF) scatter estimation were developed to accelerate the computationally intensive calculation without compromising accuracy. The proposed list-mode reconstruction algorithm was compared to the manufacturer's point spread function + TOF (PSF+TOF) algorithm. Phantom, animal, and human studies demonstrated that MOLAR with pLOR gives slightly faster contrast recovery than the PSF+TOF algorithm that uses the average 32 bit LOR sinogram positioning. Moving phantom and a whole-body human study suggested that event-by-event motion correction reduces image blurring caused by respiratory motion. We conclude that list-mode reconstruction with pLOR positioning provides a platform to generate high quality images for the mCT, and to recover fine structures in whole-body PET scans through event-by-event motion correction. (paper)

[en] Calculating attenuation correction for brain PET imaging rather than using CT presents opportunities for low radiation dose applications such as pediatric imaging and serial scans to monitor disease progression. Our goal is to evaluate the iterative time-of-flight based maximum-likelihood activity and attenuation correction factors estimation (MLACF) method for clinical FDG brain PET imaging. FDG PET/CT brain studies were performed in 57 patients using the Biograph mCT (Siemens) four-ring scanner. The time-of-flight PET sinograms were acquired using the standard clinical protocol consisting of a CT scan followed by 10 min of single-bed PET acquisition. Images were reconstructed using CT-based attenuation correction (CTAC) and used as a gold standard for comparison. Two methods were compared with respect to CTAC: a calculated brain attenuation correction (CBAC) and MLACF based PET reconstruction. Plane-by-plane scaling was performed for MLACF images in order to fix the variable axial scaling observed. The noise structure of the MLACF images was different compared to those obtained using CTAC and the reconstruction required a higher number of iterations to obtain comparable image quality. To analyze the pooled data, each dataset was registered to a standard template and standard regions of interest were extracted. An SUVr analysis of the brain regions of interest showed that CBAC and MLACF were each well correlated with CTAC SUVrs. A plane-by-plane error analysis indicated that there were local differences for both CBAC and MLACF images with respect to CTAC. Mean relative error in the standard regions of interest was less than 5% for both methods and the mean absolute relative errors for both methods were similar (3.4%  ±  3.1% for CBAC and 3.5%  ±  3.1% for MLACF). However, the MLACF method recovered activity adjoining the frontal sinus regions more accurately than CBAC method. The use of plane-by-plane scaling of MLACF images was found to be a crucial step in order to obtain improved activity estimates. Presence of local errors in both MLACF and CBAC based reconstructions would require the use of a normal database for clinical assessment. However, further work is required in order to assess the clinical advantage of MLACF over CBAC based method. (paper)

[en] 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 ⁶⁸Ga-PSMA scan, and 23 whole-body ¹⁸F-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. (paper)

[en] Monte Carlo simulation provides a valuable tool in performance assessment and optimization of system design parameters for PET scanners. SimSET is a popular Monte Carlo simulation toolkit that features fast simulation time, as well as variance reduction tools to further enhance computational efficiency. However, SimSET has lacked the ability to simulate block detectors until its most recent release. Our goal is to validate new features of SimSET by developing a simulation model of the Siemens Biograph mCT PET scanner and comparing the results to a simulation model developed in the GATE simulation suite and to experimental results. We used the NEMA NU-2 2007 scatter fraction, count rates, and spatial resolution protocols to validate the SimSET simulation model and its new features. The SimSET model overestimated the experimental results of the count rate tests by 11–23% and the spatial resolution test by 13–28%, which is comparable to previous validation studies of other PET scanners in the literature. The difference between the SimSET and GATE simulation was approximately 4–8% for the count rate test and approximately 3–11% for the spatial resolution test. In terms of computational time, SimSET performed simulations approximately 11 times faster than GATE simulations. The new block detector model in SimSET offers a fast and reasonably accurate simulation toolkit for PET imaging applications. (note)