Recent developments in time-of-flight PET

While the first time-of-flight (TOF)-positron emission tomography (PET) systems were already built in the early 1980s, limited clinical studies were acquired on these scanners. PET was still a research tool, and the available TOF-PET systems were experimental. Due to a combination of low stopping power and limited spatial resolution (caused by limited light output of the scintillators), these systems could not compete with bismuth germanate (BGO)-based PET scanners. Developments on TOF system were limited for about a decade but started again around 2000. The combination of fast photomultipliers, scintillators with high density, modern electronics, and faster computing power for image reconstruction have made it possible to introduce this principle in clinical TOF-PET systems. This paper reviews recent developments in system design, image reconstruction, corrections, and the potential in new applications for TOF-PET. After explaining the basic principles of time-of-flight, the difficulties in detector technology and electronics to obtain a good and stable timing resolution are shortly explained. The available clinical systems and prototypes under development are described in detail. The development of this type of PET scanner also requires modified image reconstruction with accurate modeling and correction methods. The additional dimension introduced by the time difference motivates a shift from sinogram- to listmode-based reconstruction. This reconstruction is however rather slow and therefore rebinning techniques specific for TOF data have been proposed. The main motivation for TOF-PET remains the large potential for image quality improvement and more accurate quantification for a given number of counts. The gain is related to the ratio of object size and spatial extent of the TOF kernel and is therefore particularly relevant for heavy patients, where image quality degrades significantly due to increased attenuation (low counts) and high scatter fractions. The original calculations for the gain were based on analytical methods. Recent publications for iterative reconstruction have shown that it is difficult to quantify TOF gain into one factor. The gain depends on the measured distribution, the location within the object, and the count rate. In a clinical situation, the gain can be used to either increase the standardized uptake value (SUV) or reduce the image acquisition time or administered dose. The localized nature of the TOF kernel makes it possible to utilize local tomography reconstruction or to separate emission from transmission data. The introduction of TOF also improves the joint estimation of transmission and emission images from emission data only. TOF is also interesting for new applications of PET-like isotopes with low branching ratio for positron fraction. The local nature also reduces the need for fine angular sampling, which makes TOF interesting for limited angle situations like breast PET and online dose imaging in proton or hadron therapy. The aim of this review is to introduce the reader in an educational way into the topic of TOF-PET and to give an overview of the benefits and new opportunities in using this additional information

A GPU-based Implementation for Improved Online Rebinning Performance in Clinical 3-D PET

Online rebinning is an important and well-established technique for reducing the time required to process Positron Emission Tomography data. However, the need for efficient data processing in a clinical setting is growing rapidly and is beginning to exceed the capability of traditional online processing methods. High-count rate applications such as Rubidium 3-D PET studies can easily saturate current online rebinning technology. Realtime processing at these high-count rates is essential to avoid significant data loss. In addition, the emergence of time-of-flight (TOF) scanners is producing very large data sets for processing. TOF applications require efficient online Rebinning methods so as to maintain high patient throughput. Currently, new hardware architectures such as Graphics Processing Units (GPUs) are available to speedup data parallel and number crunching algorithms. In comparison to the usual parallel systems, such as multiprocessor or clustered machines, GPU hardware can be much faster and above all, it is significantly cheaper. The GPUs have been primarily delivered for graphics for video games but are now being used for High Performance computing across many domains. The goal of this thesis is to investigate the suitability of the GPU for PET rebinning algorithms

A Promising Future: comparable Imaging Capability of MRI-Compatible Silicon Photomultiplier and Conventional Photosensor Preclinical PET Systems

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

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

Simulation of Clinical PET Studies for the Assessment of Quantification Methods

On this PhD thesis we developed a methodology for evaluating the robustness of SUV measurements based on MC simulations and the generation of novel databases of simulated studies based on digital anthropomorphic phantoms. This methodology has been applied to different problems related to quantification that were not previously addressed. Two methods for estimating the extravasated dose were proposed andvalidated in different scenarios using MC simulations. We studied the impact of noise and low counting in the accuracy and repeatability of three commonly used SUV metrics (SUVmax, SUVmean and SUV50). The same model was used to study the effect of physiological muscular uptake variations on the quantification of FDG-PET studies. Finally, our MC models were applied to simulate 18F-fluorocholine (FCH) studies. The aim was to study the effect of spill-in counts from neighbouring regions on the quantification of small regions close to high activity extended sources

Incorporating accurate statistical modeling in PET: reconstruction for whole-body imaging

Tese de doutoramento em Biofísica, apresentada à Universidade de Lisboa através da Faculdade de Ciências, 2007The thesis is devoted to image reconstruction in 3D whole-body PET imaging. OSEM ( Ordered Subsets Expectation maximization ) is a statistical algorithm that assumes Poisson data. However, corrections for physical effects (attenuation, scattered and random coincidences) and detector efficiency remove the Poisson characteristics of these data. The Fourier Rebinning (FORE), that combines 3D imaging with fast 2D reconstructions, requires corrected data. Thus, if it will be used or whenever data are corrected prior to OSEM, the need to restore the Poisson-like characteristics is present. Restoring Poisson-like data, i.e., making the variance equal to the mean, was achieved through the use of weighted OSEM algorithms. One of them is the NECOSEM, relying on the NEC weighting transformation. The distinctive feature of this algorithm is the NEC multiplicative factor, defined as the ratio between the mean and the variance. With real clinical data this is critical, since there is only one value collected for each bin the data value itself. For simulated data, if we keep track of the values for these two statistical moments, the exact values for the NEC weights can be calculated. We have compared the performance of five different weighted algorithms (FORE+AWOSEM, FORE+NECOSEM, ANWOSEM3D, SPOSEM3D and NECOSEM3D) on the basis of tumor detectablity. The comparison was done for simulated and clinical data. In the former case an analytical simulator was used. This is the ideal situation, since all the weighting factors can be exactly determined. For comparing the performance of the algorithms, we used the Non-Prewhitening Matched Filter (NPWMF) numerical observer. With some knowledge obtained from the simulation study we proceeded to the reconstruction of clinical data. In that case, it was necessary to devise a strategy for estimating the NEC weighting factors. The comparison between reconstructed images was done by a physician largely familiar with whole-body PET imaging

Investigation of accuracy in quantitation of 18F-FDG concentration of PET/CT

The PET/CT scanner has been recognized as a powerful diagnostic imaging modality in oncology and radiation treatment planning. Traditionally, PET has been used for quantitative analysis, and diagnostic interpretations of PET images greatly relied on a nuclear medicine physician’s experience and knowledge. The PET data set represents a positron emitter’s activity concentration as a gray scale in each pixel. The assurance of the quantitative accuracy of the PET data is critical for diagnosis and staging of disease and evaluation of treatment. The standard uptake value (SUV) is a widely employed parameter in clinical settings to distinguish malignant lesions from others. SUV is a rough normalization of radioactive tracer uptake where normal tissue uptake is unity. The PET scanner is a sensitive diagnostic method to detect small lesions such as lymph node metastasis less than 1 cm in diameter, whereas the CT scanner may be limited in detecting these lesions. The accuracy of quantitation of small lesions is critical for predicting prognosis or planning a treatment of the patient. PET/CT uses attenuation correction factors obtained from CT scanner data sets. Non-biological materials such as metals and contrast agents are recognized as a factor that leads to a wrong scaling factor in the PET image. We challenge the accuracy of the quantitative method that physicians routinely use as a parameter to distinguish malignant lesions from others under clinical settings in commercially available CT/PET scanners. First, we verified if we could recover constant activity concentration throughout the field of view for small identical activity concentration sources. Second, we tested how much the CT-based attenuation correction factor could be influenced by contrast agents. Third, we tested how much error in quantitation could be introduced by object size. Our data suggest that the routine normalization process of the PET scanner does not guarantee an accurate quantitation of discrete uniform activity sources in the PET/CT scanner. Also, activity concentrations greatly rely on an object’s dimensions and object size. A recovery correction factor is necessary on these quantitative data for oncological evaluation to assure accurate interpretation of the activity concentration. Development of parameters for quantitation other than SUV may overcome SUV’s inherent limitations reflecting patient-specific physiology and the imaging characteristics of individual scanners