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

Efficient methodologies for system matrix modelling in iterative image reconstruction for rotating high-resolution PET

A fully 3D iterative image reconstruction algorithm has been developed for high-resolution PET cameras composed of pixelated scintillator crystal arrays and rotating planar detectors, based on the ordered subsets approach. The associated system matrix is precalculated with Monte Carlo methods that incorporate physical effects not included in analytical models, such as positron range effects and interaction of the incident gammas with the scintillator material. Custom Monte Carlo methodologies have been developed and optimized for modelling of system matrices for fast iterative image reconstruction adapted to specific scanner geometries, without redundant calculations. According to the methodology proposed here, only one-eighth of the voxels within two central transaxial slices need to be modelled in detail. The rest of the system matrix elements can be obtained with the aid of axial symmetries and redundancies, as well as in-plane symmetries within transaxial slices. Sparse matrix techniques for the non-zero system matrix elements are employed, allowing for fast execution of the image reconstruction process. This 3D image reconstruction scheme has been compared in terms of image quality to a 2D fast implementation of the OSEM algorithm combined with Fourier rebinning approaches. This work confirms the superiority of fully 3D OSEM in terms of spatial resolution, contrast recovery and noise reduction as compared to conventional 2D approaches based on rebinning schemes. At the same time it demonstrates that fully 3D methodologies can be efficiently applied to the image reconstruction problem for high-resolution rotational PET cameras by applying accurate pre-calculated system models and taking advantage of the system's symmetries

Noise Characteristics of the FORE+OSEM(DB) Reconstruction Method for the MiCES PET Scanner

The FORE+OSEM(DB) image reconstruction method has been proposed for the fully-3D MiCES PET scanner under construction at the University of Washington. It is based on Fourier rebinning followed by 2D OSEM and an incorporated model of detector blurring (DB). As an extension, this paper presents the noise/resolution characteristics of this method. Multiple realizations were simulated to estimate the noise properties of the algorithm. The results are compared with OSEM followed by post reconstruction 3D Gaussian smoothing. The results show that the incorporation of detector blurring (OSEM(DB)) into the system matrix improves resolution compared to OSEM, while also inducing an increased variance at all radial locations. In addition, radially-varying noise characteristics are more apparent with OSEM(DB) than with OSEM.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/85836/1/Fessler204.pd

Experimental method development for direct dosimetry of permanent interstitial prostate brachytherapy implants

Purpose: To ascertain if PET image data of a positron tracer can be used for the quantitative description of dose distribution in support of direct prostate seed dosimetry. Materials and Methods: Simulated brachytherapy seeds were constructed containing trace amounts of a positron emitter, F-18, such that all annihilation events took place in the encapsulation wall. An acrylic prostate phantom containing these seeds was imaged with a GE Discovery ST PET/CT scanner in 2D and 3D acquisition modes and several image reconstruction methods. The PET scan data was used as the input for Monte Carlo calculation of dose distribution due to the F-18. This dose distribution was then compared to computations wherein the source was restricted to the encapsulation wall. This was done to determine if the measured data could be used to accurately compute the annihilation dose, which in turn would be used to compute the therapeutic dose due to known seed activity. Results: Examination of the dose distributions indicates a close agreement between the measured data and theoretical calculations for certain cases. We found that 2D acquisition with OSEM reconstruction resulted in a maximum difference in transaxial dose distribution of 15% in a single voxel, and a mean difference of 4% for the remaining voxels. However, the mean discrepancy between dose computations based on the ideal source versus PET based source is within or close to the Monte Carlo error of 2% to 4%. These results do not reflect any optimized acquisition protocol that may further reduce the observed differences. Conclusions: This work indicates there is potential for using PET data for the proposed link between the therapeutic brachytherapy dose and the dose due to a trace amount of encapsulated positron emitter, as developed by Sajo and Williams. Because this method does not require explicit information on seed locations, clinical implementation of this technique could significantly reduce the time needed for post-implant evaluation, and several of the uncertainties and limitations inherent in current prostate brachytherapy dosimetry

Efficient methodology for 3D statistical reconstruction of high resolution coplanar PET/CT scanner

Proceeding of: 2008 IEEE Nuclear Science Symposium Conference Record (NSS '08), Dresden, Germany, 19-25 Oct. 2008A fully 3D statistical image reconstruction algorithm has been developed for a high-resolution coplanar PETtCT scanner based on rotating planar PET detectors. The system matrix has been modeled with custom Monte Carlo techniques optimized for the specific scanner architecture. The system model includes positron range, non-colinearity of gamma rays and crystal interaction modelling with attenuation and Compton scattering effects. Only 0.21 % of the system matrix columns are modeled in detail, obtaining the rest of the values with axial and transaxial voxel-driven symmetries. The iterative algorithm is a fully 3D approach, regularized with the anatomical registered image using a novel version of the minimum cross entropy (MXE) scheme, and accelerated employing ordered subsets. The proposed method has been shown to produce images with superior quality than 3D hybrid (FORE+2D-OSEM) algorithms applied on synthetic GATE data, as well as on real small animal acquisitionsThis work has been partly funded by the CDTEAM project and CENIT programme (Spanish Ministry of Industry), EMIL (ED Network of Excellence), CIBER CB07/09/0031 and RETIC-RECAVA (Spanish Ministry of Health) and TEC2007-64731/TCM(Spanish Ministry of Education and Science

Performance evaluation for 68Ga and 18F of the ARGUS small-animal PET scanner based on the NEMA NU-4 standard

Proceeding of: 2010 IEEE Nuclear Science Symposium, Medical Imaging Conference and 17th Room Temperature Semiconductor Detector Workshop (IEEE), Knoxville, Tennessee, USA, October 30 - November 6, 201068Ga is one of the non-conventional nuclides that are being used in preclinical imaging. One disadvantage of 68Ga versus 18F is its larger positron range, which deteriorates the effective spatial resolution and the overall image quality. In this work we present a performance evaluation of the ARGUS smallanimal positron emission tomography (PET) scanner for two positron emitters, 68Ga and 18F. These experiments followed the procedure based on the National Electrical Manufacturers Association (NEMA) NU 4-2008 standard. We show how the use of 68Ga may affect the NEMA performance of the system in terms of image quality and spatial resolution. The recovery coefficients (RC) measured in the image-quality phantom ranged from 0.17 to 0.72 for 68Ga and from 0.28 to 0.92 for 18F, using iterative image reconstruction methods and applying all corrections. Under the same conditions the image noise (%STD) in a uniform region was 17.0% for 68Ga and 15.1% for 18F. The respective spillover ratios (SOR) were 0.13 and 0.09 in air, and 0.21 and 0.12 in water. Attenuation correction yielded an improvement of the SOR close to 50% for both radionuclides in the air-filled region. This work evaluates the image reconstruction methods and corrections available in the ARGUS PET for 68Ga and 18F to assess the influence of their physical properties on the NEMA parameters.Publicad

Performance evaluation of the GE healthcare eXplore VISTA dual-ring small-animal PET scanner

This work was supported in part by grant CA92871 from the National Institutes of Health, Bethesda, MD.Publicad

Practical aspects of a data-driven motion correction approach for brain SPECT

Patient motion can cause image artifacts in single photon emission computed tomography despite restraining measures. Data-driven detection and correction of motion can be achieved by comparison of acquired data with the forward projections. This enables the brain locations to be estimated and data to be correctly incorporated in a three-dimensional (3-D) reconstruction algorithm. Digital and physical phantom experiments were performed to explore practical aspects of this approach. Noisy simulation data modeling multiple 3-D patient head movements were constructed by projecting the digital Hoffman brain phantom at various orientations. Hoffman physical phantom data incorporating deliberate movements were also gathered. Motion correction was applied to these data using various regimes to determine the importance of attenuation and successive iterations. Studies were assessed visually for artifact reduction, and analyzed quantitatively via a mean registration error (MRE) and mean square difference measure (MSD). Artifacts and distortion in the motion corrupted data were reduced to a large extent by application of this algorithm. MRE values were mostly well within 1 pixel (4.4 mm) for the simulated data. Significant MSD improvements (>2) were common. Inclusion of attenuation was unnecessary to accurately estimate motion, doubling the efficiency and simplifying implementation. Moreover, most motion-related errors were removed using a single iteration. The improvement for the physical phantom data was smaller, though this may be due to object symmetry. In conclusion, these results provide the basis of an implementation protocol for clinical validation of the technique

ROC comparison of acquisition parameters for two PET/CT scanners based on lesion detectability in a torso phantom

Positron emission tomography (PET) and computed tomography (CT) are well established and powerful tools for medical diagnostics but even integrated PET/CT scanner images still lack the necessary quality and resolution that would make medical diagnoses flawless. In this thesis experiments were performed to statistically determine the effect that image acquisition parameters have upon diagnostic accuracy. Images from different PET/CT scanners were assessed by comparing subject human diagnostic accuracy from a sample of both professional and student volunteers. The assessment results were compared to the objective NEMA-standards performance data provided by the manufacturers for each scanner. The data analysis method is the receiver operating characteristic (ROC) curves. We hypothesize that human performance in making accurate diagnoses from PET images correlates with the system performance. The data shows that human diagnostic performance correlates to spatial resolution and sensitivity of the PET imaging systems