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

Quantitative Techniques for PET/CT: A Clinical Assessment of the Impact of PSF and TOF

Tomographic reconstruction has been a challenge for many imaging applications, and it is particularly problematic for count-limited modalities such as Positron Emission Tomography (PET). Recent advances in PET, including the incorporation of time-of-flight (TOF) information and modeling the variation of the point response across the imaging field (PSF), have resulted in significant improvements in image quality. While the effects of these techniques have been characterized with simulations and mathematical modeling, there has been relatively little work investigating the potential impact of such methods in the clinical setting. The objective of this work is to quantify these techniques in the context of realistic lesion detection and localization tasks for a medical environment. Mathematical observers are used to first identify optimal reconstruction parameters and then later to evaluate the performance of the reconstructions. The effect on the reconstruction algorithms is then evaluated for various patient sizes and imaging conditions. The findings for the mathematical observers are compared to, and validated by, the performance of three experienced nuclear medicine physicians completing the same task

Development and Implementation of Fully 3D Statistical Image Reconstruction Algorithms for Helical CT and Half-Ring PET Insert System

X-ray computed tomography: CT) and positron emission tomography: PET) have become widely used imaging modalities for screening, diagnosis, and image-guided treatment planning. Along with the increased clinical use are increased demands for high image quality with reduced ionizing radiation dose to the patient. Despite their significantly high computational cost, statistical iterative reconstruction algorithms are known to reconstruct high-quality images from noisy tomographic datasets. The overall goal of this work is to design statistical reconstruction software for clinical x-ray CT scanners, and for a novel PET system that utilizes high-resolution detectors within the field of view of a whole-body PET scanner. The complex choices involved in the development and implementation of image reconstruction algorithms are fundamentally linked to the ways in which the data is acquired, and they require detailed knowledge of the various sources of signal degradation. Both of the imaging modalities investigated in this work have their own set of challenges. However, by utilizing an underlying statistical model for the measured data, we are able to use a common framework for this class of tomographic problems. We first present the details of a new fully 3D regularized statistical reconstruction algorithm for multislice helical CT. To reduce the computation time, the algorithm was carefully parallelized by identifying and taking advantage of the specific symmetry found in helical CT. Some basic image quality measures were evaluated using measured phantom and clinical datasets, and they indicate that our algorithm achieves comparable or superior performance over the fast analytical methods considered in this work. Next, we present our fully 3D reconstruction efforts for a high-resolution half-ring PET insert. We found that this unusual geometry requires extensive redevelopment of existing reconstruction methods in PET. We redesigned the major components of the data modeling process and incorporated them into our reconstruction algorithms. The algorithms were tested using simulated Monte Carlo data and phantom data acquired by a PET insert prototype system. Overall, we have developed new, computationally efficient methods to perform fully 3D statistical reconstructions on clinically-sized datasets

Using PET/MRI to Assess Hepatic Radioembolization of Yttrium-90 Microspheres

Radioembolization of yttrium-90 (Y-90) microspheres is used to treat primary and secondary cancers in the liver. Though this therapy has existed for decades, the treatment is not well optimized from treatment planning to post-procedural assessment. Recently, there has been a surge to utilize the small positron yield from the radioactive decay of Y-90 for post-radioembolization positron emission tomography (PET) imaging of the microsphere activity distribution. These images provide promise for dosimetry assessment, identifying extrahepatic uptake and possible under-dosed lesions that may benefit from subsequent therapy. However, due to the low positron statistics and high flux of Bremsstrahlung radiation, PET imaging of Y-90 presents with its own unique set of challenges. In this work, we optimized the PET imaging acquisition and reconstruction parameters when imaging with a hybrid PET/MRI scanner to offer the most accurate images for quantitative dosimetric applications. We then tested the variability of imaging Y-90 with PET across multiple institutions in a world-wide phantom study in preparation for a multi-institutional phase I/II clinical trial. Lastly, we determined the clinical utility of using Y-90 PET-based dosimetry to predict clinical outcomes and assess how well it correlates with pre-treatment imaging

Investigation of the Effects of Image Signal-to-Noise Ratio on TSPO PET Quantification of Neuroinflammation

Neuroinflammation may be imaged using positron emission tomography (PET) and the tracer [11C]-PK11195. Accurate and precise quantification of 18 kilodalton Translocator Protein (TSPO) binding parameters in the brain has proven difficult with this tracer, due to an unfavourable combination of low target concentration in tissue, low brain uptake of the tracer and relatively high non-specific binding, all of which leads to higher levels of relative image noise. To address these limitations, research into new radioligands for the TSPO, with higher brain uptake and lower non-specific binding relative to [11C]-PK11195, is being conducted world-wide. However, factors other than radioligand properties are known to influence signal-to-noise ratio in quantitative PET studies, including the scanner sensitivity, image reconstruction algorithms and data analysis methodology. The aim of this thesis was to investigate and validate computational tools for predicting image noise in dynamic TSPO PET studies, and to employ those tools to investigate the factors that affect image SNR and reliability of TSPO quantification in the human brain. The feasibility of performing multiple (n≥40) independent Monte Carlo simulations for each dynamic [11C]-PK11195 frame- with realistic modelling of the radioactivity source, attenuation and PET tomograph geometries- was investigated. A Beowulf-type high performance computer cluster, constructed from commodity components, was found to be well suited to this task. Timing tests on a single desktop computer system indicated that a computer cluster capable of simulating an hour-long dynamic [11C]-PK11195 PET scan, with 40 independent repeats, and with a total simulation time of less than 6 weeks, could be constructed for less than 10,000 Australian dollars. A computer cluster containing 44 computing cores was therefore assembled, and a peak simulation rate of 2.84x105 photon pairs per second was achieved using the GEANT4 Application for Tomographic Emission (GATE) Monte Carlo simulation software. A simulated PET tomograph was developed in GATE that closely modelled the performance characteristics of several real-world clinical PET systems in terms of spatial resolution, sensitivity, scatter fraction and counting rate performance. The simulated PET system was validated using adaptations of the National Electrical Manufacturers Association (NEMA) quality assurance procedures within GATE. Image noise in dynamic TSPO PET scans was estimated by performing n=40 independent Monte Carlo simulations of an hour-long [11C]-PK11195 scan, and of an hour- long dynamic scan for a hypothetical TSPO ligand with double the brain activity concentration of [11C]-PK11195. From these data an analytical noise model was developed that allowed image noise to be predicted for any combination of brain tissue activity concentration and scan duration. The noise model was validated for the purpose of determining the precision of kinetic parameter estimates for TSPO PET. An investigation was made into the effects of activity concentration in tissue, radionuclide half-life, injected dose and compartmental model complexity on the reproducibility of kinetic parameters. Injecting 555 MBq of carbon-11 labelled TSPO tracer produced similar binding parameter precision to 185 MBq of fluorine-18, and a moderate (20%) reduction in precision was observed for the reduced carbon-11 dose of 370 MBq. Results indicated that a factor of 2 increase in frame count level (relative to [11C]-PK11195, and due for example to higher ligand uptake, injected dose or absolute scanner sensitivity) is required to obtain reliable binding parameter estimates for small regions of interest when fitting a two-tissue compartment, four-parameter compartmental model. However, compartmental model complexity had a similarly large effect, with the reduction of model complexity from the two-tissue compartment, four-parameter to a one-tissue compartment, two-parameter model producing a 78% reduction in coefficient of variation of the binding parameter estimates at each tissue activity level and region size studied. In summary, this thesis describes the development and validation of Monte Carlo methods for estimating image noise in dynamic TSPO PET scans, and analytical methods for predicting relative image noise for a wide range of tissue activity concentration and acquisition durations. The findings of this research suggest that a broader consideration of the kinetic properties of novel TSPO radioligands, with a view to selection of ligands that are potentially amenable to analysis with a simple one-tissue compartment model, is at least as important as efforts directed towards reducing image noise, such as higher brain uptake, in the search for the next generation of TSPO PET tracers

Evaluation of yttrium-90 positron emission tomography dosimetry

Purpose: Radioembolization is a novel treatment which utilizes the liver\u27s unique dual system blood supply to trap yttrium-90 (90Y) microspheres in microvasculature near liver tumors. Radioembolization dose planning and dosimetry are based on crude, inaccurate assumptions due to the lack of knowledge of patient specific 90Y microsphere distribution. In recent years, the very small 3.1867e-5 internal pair production decay branch of 90Y has been shown to allow for positron emission tomography (PET) imaging following radioembolization. This work explores the accuracy and limitation of 90Y PET imaging due to the extremely low signal to noise (SNR) ratio associated with 90Y and verifies the accuracy of using these PET images for 3-dimensional (3D) dosimetry. ^ Material and Methods: PET acquisitions of a phantom containing 90Y filled cylindrical inserts were acquired to determine quantitative accuracy of the PET images to measure 90Y activity. Numerous reconstruction algorithms were used to determine the optimal protocol to balance image noise and accuracy. A GATE model of the PET scanner was used to evaluate the origin of prompt signal and random noise coincidence counts in these PET acquisitions. PET images were converted to dose maps using standard S-kernel convolution. Polymer gel dosimetry was used to validate the 3D dose map results. Furthermore, PET, with associated CT images, were used as input data into MC simulations to model dose rates surrounding patients for future patient release studies. A Siemens® Biograph 64 TruePoint PET/CT was used for all acquisitions and reconstructions. ^Results: The phantom study determined Siemens® OSEM-PSF algorithm, known as TrueX, with 2 iterations and 14 subsets had the optimal balance of noise and accuracy. Using this reconstruction algorithm, the PET images were found to accurately measure activity and calculated dose within 10% when 90Y concentration was above the minimum detectable concentrations (MDC) of 1 MBq/ml. However, this reconstruction algorithm was shown to have a positive bias in areas where concentration was below the MDC due to truncation of negative sinogram bin values caused by statistical noise in the random correction. Polymer gel dosimetry verified the accuracy of PET dose maps but also identified a limitation in cases of highly gradient distributions due to the PET spatial resolution spreading of measured activity. Additionally, external dose rates were found to be accurately predicted through use of 90Y PET/CT images as inputs into a MC simulation.Conclusion: Research in 90Y PET/CT has quickly been expanding over recent years as a feasible method to provide liver distribution of 90Y following radioembolization. This study demonstrates the accuracy and limitations of the use of these 90Y PET/CT images in patient specific qualitative dosimetry

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

Initial PET Performance Evaluation of a Preclinical Insert for PET/MRI with Digital SiPM Technology

Hyperion-IID is a positron emission tomography (PET) insert which allows simultaneous operation in a clinical magnetic resonance imaging (MRI) scanner. To read out the scintillation light of the employed LYSO crystal arrays with a pitch of 1 mm pitch and 12 mm in height, digital silicon photomultipliers (DPC 3200-22, Philips Digital Photon Counting) (DPC) are used. The basic PET performance in terms of energy resolution, coincidence resolution time (CRT) and sensitivity as a function of operating parameters, such as the operating temperature, the applied overvoltage, activity and configuration parameters of the DPCs, were evaluated on system level. The measured energy resolution did not show a large dependency on the selected parameters and is in the range of 12.4-12.9% for low activities and degrades to ~13.6% at activities of ~100 MBq. The CRT strongly depends on the selected trigger scheme (trig) of the DPCs. We measured approximately 260 ps, 440 ps, 540 ps and 1300 ps for trig 1-4, respectively. The trues sensitivity for a NEMA NU 4 mouse-sized scatter phantom with a 70-mm-long tube of activity was dependent on the operating parameters and was determined to be 0.4-1.4% at low activities. The random fraction stayed below 5% at activities up to 100 MBq and the scatter fraction was evaluated as ~6% for an energy window of 411-561 keV and ~16% for 250-625 keV. Furthermore, we performed imaging experiments using a mouse-sized hot-rod phantom and a large rabbit-sized phantom. In 2D slices of the reconstructed mouse-sized hot-rod phantom ({\O} = 28 mm), the rods were distinguishable from each other down to a rod size of 0.8 mm. There was no benefit of the better CRT of trig 1 over trig 3, where in the larger rabbit-sized phantom ({\O} = 114 mm), we could show a clear improvement of image quality using the time-of-flight information.Comment: Final journal version including the supplemntal data. The images in the supplement were compressed to meet the arXiv file size limi

Development and evaluation of quantitative imaging for improved estimation of radiopharmaceutical bio-distribution in small animal imaging

Quantitative imaging techniques like Positron Emission Tomography (PET) and Single Photon Emission Computed Tomography (SPECT) are an essential part of the treatment planning based on dosimetry in targeted radiation therapy. Apart from Fluorine-18 (18F), the potential of various other radionuclides with respect to the development of new radiopharmaceuticals which can be used for both diagnostic and therapeutic applications are increasingly under investigation. Three such radionuclides that are attractive for further research are Gallium-68 (68Ga), Copper-64 (64Cu) and Zirconium-89 (89Zr). To determine the performance of a PET or a SPECT, the National Electrical Manufacturing Association (NEMA) has published a standard set of protocols. However, there are limitations with the NEMA method with respect to the determination of the spatial resolution. Firstly, it does not take into account the overall behavior of the point spread function (PSF). Secondly, it has a very limited scope for a validation or a quality check criterion and thus the error of the calculated full width at half maximum (FWHM) cannot be determined. In the first part of this work, the aim was to quantitatively develop, evaluate and improve the performance characteristics of the PET and SPECT subsystem of the Albira II pre-clinical tri-modal system (Bruker BioSpin MRI GmbH, Ettlingen, Germany) for the radionuclides 18F, 68Ga, 64Cu and 89Zr (PET) and 99mT (SPECT). In this study, the sensitivity and spatial resolution characteristics of the systems based on a developed point source phantom were furthermore investigated for each of the radionuclides and compared with the NEMA protocol results based on measurements with a 22Na point source. In addition, a new set of protocols was developed for quantitative image reconstruction with the respective systems. In the second part of this work, an alternative method to accurately determine the PSF of an imaging system was developed to improve quantification accuracy in dosimetry. The developed method is based on 3-dimensional Gaussian fit functions taking into account the correction for the pixel size and the source dimension. Additionally, the effect of inaccurate determination of the PSF on the partial volume correction and hence the quantification of small structures in a diagnostic image was investigated. The ability of quantitative image reconstructions was determined based on the recovery coefficients that showed that upto 95% and 60% activity values could be recovered with the PET and SPECT systems, respectively. Overall the system performed satisfactory with respect to the linearity for the activity range (8-10) MBq generally used for pre-clinical imaging for all the investigated radionuclides. With respect to the determination of the system PSF, the method includes fitting of 3-dimensional functions, validation of fitting quality and choosing the best fit function based on the Akaike information criterion (AIC). The proposed method has advantages that it can better take into account the 3D distribution of the data and additionally yields an estimate for the error of the FWHM calculated from the estimated PSF. Furthermore, the investigation demonstrated that the PSF determined using the NEMA or another inadequate fit function can lead to a relative deviation of more than 40% for the recovery correction of small structures. Thus, the general method developed here can be used for obtaining robust and better reproducible PSFs for performing recovery corrections in PET/SPECT quantification studies and thus is a prerequisite for optimal evaluation of biokinetics in small animal studies