Full 3D-OSEM reconstruction with compressed response of the system

Proceeding of: Nuclear Science Symposium Conference Record, 2004 IEEE, Rome ,16-22 Oct. 2004Small animal PET scanners require high spatial resolution (< 1 mm) and good sensitivity. To obtain high resolution images, iterative reconstruction methods, like OSEM, applied to image reconstruction in three-dimensional (3D) positron emission tomography (PET), have superior performance over analytical reconstruction algorithms like FBP. However, the high computational cost of iterative methods remains a serious drawback to their development and clinical routine use. The increase in performance of current computers should make iterative image reconstruction fast enough to attain clinical viability. However, dealing with the large number of probability coefficients for the response of the system in high-resolution PET scanners becomes a difficult task that prevents the algorithms from reaching peak performance. Taking into account all possible axial, in-plane and other symmetries, we have reduced the storage needs what allows us to store the whole response of the system in dynamic memory of ordinary industry standard computers, so that the reconstruction algorithm can achieve near peak performance

Statistical reconstruction methods in PET: resolution limit, noise, edge artifacts and considerations for the design of better scanners

Proceeding of: 2005 IEEE Nuclear Science Symposium Conference Record, Puerto Rico, 23-29 Oct. 2005Small animal positron emission tomography (PET) scanners are being increasingly used as a basic measurement tool in modern biomedical research. The new designs and technologies of these scanners and the modern reconstruction methods have allowed to reach high spatial resolution and sensitivity. Despite their successes, some important issues remain to be addressed in high resolution PET imaging. First, iterative reconstruction methods like maximum likelihood-expectation maximization (MLEM) are known to recover resolution, but also to create noisy images and edge artifacts if some kind of regularization is not imposed. Second, the limit of resolution achievable by iterative methods on high resolution scanners is not quantitatively understood. Third, the use of regularization methods like Sieves or maximum a posteriori (MAP) requires them determination of the optimal values of several adjustable parameter that may be object-dependent. In this work we review these problems in high resolution PET and establish that the origin of them is more related with the physical effects involved in the emission and detection of the radiation during the acquisition than with the kind of iterative reconstruction method chosen. These physical effects (positron range, non-collinearity, scatter inside the object and inside the detector materials) cause that the tube of response (TOR) that connects the voxels with a line of response (LOR) is rather thick. This implies that the higher frequencies of the patient organ structures are not recorded by the scanner and therefore cannot be recovered during the reconstruction. As iterations grow, MLEM algorithms try to recover higher frequencies in the image. Once that a certain critic frequency is reached, this only maximizes high frequency noise. Using frequency response analyses techniques, we determine the maximum achievable resolution, before edge artifacts spoil the quality of the image, for a particular scanner as a function of the thickness of the TOR, and independently of the reconstruction method employed. With the same techniques, we can deduce well defined stopping criteria for reconstructions methods. Also, criteria for the highest number of subsets which should be used and how the design of the scanners can be optimized when statistical reconstruction methods are employed, is established.This work was supported in part by the UCM, Fundación para la investigación biomédica del Hospital Gregorio Marañon”, support from MEC project (BFM2003 04147 C02 01)

PeneloPET, a Monte Carlo PET simulation toolkit based on PENELOPE: features and validation

Proceeding of: 2006 IEEE Nuclear Science Symposium Conference Record, San Diego, California, Oct. 29 – Nov. 4, 2006PENELOPE is a Monte Carlo code that simulates the transport in matter of electrons, positrons and photons with energies from a few hundred of eV to 1 GeV. It is robust, fast and very accurate, but it may be unfriendly for people not acquainted with the FORTRAN programming language. We have developed a tookit (‘PeneloPET’) to prepare simulations of PET and SPECT within PENELOPE. Sophisticated simulations can be setup by modifying just a few simple input files. The output data can be generated at different levels of detail and can be analyzed afterwards with the preferred programming language or tools. In this work, we present the features of PeneloPET as well as validations against other dedicated PET simulation programs and two real scanners.Support from MEC (FPA2006-07393) and CDTEAM (CENIT-Ingenio 2010) Ministerio de Industria, Spain, projects. The numerical computations of this work were done at the “High capacity cluster for physical techniques'' of the Faculty for Physical Sciences of the UCM, funded in part by the UE under the FEDER programme and in part by the UCM. Parts of this work were performed under the HGGMUCM contract "Modelización de escáneres PET de alta resolución y reconstrucción estadística de imágenes PET en animales pequeños"

Resolution improvement of small animal positron emission tomography images using a step and shoot rotating scanner

Abstract of: AMI Annual Conference 2006, Orlando, Florida, March 25-29Publicad

Noise and physical limits to maximum resolution of PET images

In this work we show that there is a limit for the maximum resolution achievable with a high resolution PET scanner, as well as for the best signal-to-noise ratio, which are ultimately related to the physical effects involved in the emission and detection of the radiation and thus they cannot be overcome with any particular reconstruction method. These effects prevent the spatial high frequency components of the imaged structures to be recorded by the scanner. Therefore, the information encoded in these high frequencies cannot be recovered by any reconstruction technique. Within this framework, we have determined the maximum resolution achievable for a given acquisition as a function of data statistics and scanner parameters, like the size of the crystals or the inter-crystal scatter. In particular, the noise level in the data as a limitation factor to yield high-resolution images in tomographs with small crystal sizes is outlined. These results have implications regarding how to decide the optimal number of voxels of the reconstructed image or how to design better PET scannersPublicad

Normalization in 3D PET: dependence on the activity distribution of the source

Proceeding of: 2006 IEEE Nuclear Science Symposium Conference Record, San Diego, CA, Oct. 29 - Nov. 1, 2006In this communication we show the dependence of the normalization of 3D small animal PET scanners on the calibrating source geometry and non-uniformity of the activity distribution inside it. The potential impact on the reconstructed images of deviations from the ideal activity is discussed. Results from simulated and real data for a pair of block detectors suggest that planar or annular sources can be equally suitable for a normalization procedure if their geometry and their intersections with the system lines-of-response (LORs) are properly taken into account. When comparing an annulus with a centered planar source, both filled with the same total activity, the planar source produces twice the count rate with a 92% of trues versus 66% of trues for the annulus. Scatter and randoms are lower by factors of 3 and 4 respectively in the planar case. We conclude that, although planar and annular sources can be suitable for a normalization procedure if their geometries are properly taken into account, planar source normalization results are better than those of an annulus, particularly if the normalization does not consider the effect of scatter correction, more significant for the annulus source than for the planar oneThis work has been partially funded by projects PI052583 and PI052583 (Ministerio de Sanidad), BFM2003-04147-C02-01 (Ministerio de Edcucación y Ciencia) and CD-TEAM (Ministerio de Industria, CENIT program), Spai

Optimal and robust PET data sinogram restoration based on the response of the system

Proceeding of: 2006 IEEE Nuclear Science Symposium Conference Record, San Diego, CA, Oct. 29 - Nov. 1, 2006We present an optimal and robust technique for the restoration of positron emission tomography (PET) data. It is based on an iterative deconvolution of Fourier Rebinned (FORE) sinograms employing the EM-ML algorithm regularized with MAP. The deconvolution kernel is related to the System Response Matrix (SRM) and the axial point spread function(PSF) caused by FORE. This method is able to deblur the acquired data whitout the introduction of additional noise and enhancing the quality (resolution, contrast) of the images reconstructed using FBP.Support from UCM grant. J.M. Udias acknowledges support from MEC (FPA2006- 07393) and CENIT (Ministerio de Industria, Spain). Part of the computations of this work were done at the “High capacity cluster for physical techniques” of the Faculty for Physical Sciences of UCM, funded in part by the UE under the FEDER program and in part by the UCM

Performance evaluation of SiPM photodetectors for PET imaging in the presence of magnetic fields

The multi pixel photon counter (MPPC) or silicon photomultiplier (SiPM), recently introduced as a solid state photodetector, consists of an array of Geiger mode photodiodes (microcells). It is a promising device for PET due to its potential for high photon detection efficiency (PDE) and its foreseeable immunity to magnetic fields. It is also easy to use with simple read outs, has a high gain and a small size. In this work we evaluate the in field performance of three 1x1mm2 (with 100, 400 and 1600 microcells, respectively) and one 6x6mm2 (arranged as a 2x2 array) Hamamatsu MPPCs for their use in PET imaging. We examine the dependence of the energy resolution and the gain of these devices on the temperature and reverse bias voltage, when coupled to LYSO scintillator crystals under conditions that one would find in a PET system. We find that the 400 and 1600 microcells models and the 2x2 array are suitable for small size crystals, like those employed in high resolution small animal scanners. We have confirmed the good performance of these devices up to magnetic fields of 7 T as well as their suitability for performing PET acquisitions in the presence of fast switching gradients and high duty radiofrequency MRI sequencesThis work was supported in part by the CDTEAM project of the CENIT program, and by Ministerio de Ciencia e Innovacio´n under projects FPA2007 62216TEC2008 06715 C02 01, UCM (Grupos UCM; 910059), CPAN (Consolider Ingenio 2010) CSPD 2007 00042 projects, and project SENSORCZT S 0505/MAT/000279, Comunidad de Madrid. Part of the computations of this work were done at the ‘‘High Capacity Cluster for Physical Techniques’’ of UCM, funded in part by the UE under the FEDER program and in part by UCMPublicad

Validation of peneloPET simulations of the Biograph PET/CT scanner with TOF capabilities

Actas de: XXVIII Congreso Anual de la Sociedad Española de Ingeniería Biomédica (CASEIB 2010). Madrid, 24-26 de noviembre de 2010.Monte Carlo simulations are currently widely used in positron emission tomography (PET) imaging for optimizing detector design and acquisition protocols, and for developing and assessing corrections and reconstruction methods. PeneloPET is a Monte Carlo code for PET simulations with basic components of detector geometry, acquisition electronics and material and source definitions. The purpose of the present study was to validate the simulations of the Siemens Biograph PET/CT scanner with TOF capabilities performed with peneloPET. The scanner components incorporate four rings of 48 detector blocks. Each block comprises 13 × 13 matrix of 4 × 4 × 20 mm3. Results were compared with experimental data obtained in accordance with the NEMA-2007 performance measurement protocol done by Jakoby, et al.This work has been supported by MEC (FPA2007-62216), UCM (Grupos UCM, 910059), CPAN (Consolider-Ingenio 2010) CSPD-2007-00042, the RECAVA-RETIC network, ARTEMIS S2009/DPI-1802, European Regional Development, ENTEPRASE grant, PSE-300000-2009-5 and TEC2008-0675-C02-01, Ministerio de Ciencia e Innovación. Spanish Government.Publicad

Fully 3D GPU PET reconstruction

Fully 3D iterative tomographic image reconstruction is computationally very demanding. Graphics Processing Unit(GPU) has be enproposed formany years as potential accelerators incomplex scientific problems, but it has not be enuseduntil there cent advances in the programmability of GPU sthat the best available reconstruction code shave started tobe implemented toberunon GPUs. This work presents a GPU based fully 3D PET iterative reconstruction sofware. This new code may reconstruct sinogram data from several commercially available PET scanners. The most important and time consuming part soft he code,the forward and backward projection operations, arebasedonan accurate model of the scanner obtained with the MonteCarlo code PeneloPET and they have been massively parallelize don the GPU.For the PET scanners considered, the GPU based code is more than 70 times faster than asimilar code running on a single core of a fast CPU, obtainingin both cases the same images. The code has been designed to be easily adapted to reconstruct sinograms from any other PET scanner, including scanner prototypes.This work has been supported by MEC(FPA200762216), UCM (Grupos UCM,910059), CPAN(Consolider Ingenio 2010) CSPD 200700042,the RECAVARETIC network, ARTEMISS2009/ DPI 1802, European Regional Development,ENTEPRASE grant, PSE 30000020095 and TEC20080675C0201, Ministerio de Ciencia e Innovación, Spanish Government.Publicad