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  1. Article: Partial volume effect correction in PET using regularized iterative deconvolution with variance control based on local topology.

    Kirov, A S / Piao, J Z / Schmidtlein, C R

    Physics in medicine and biology

    2008  Volume 53, Issue 10, Page(s) 2577–2591

    Abstract: Correcting positron emission tomography (PET) images for the partial volume effect (PVE) due to the limited resolution of PET has been a long-standing challenge. Various approaches including incorporation of the system response function in the ... ...

    Abstract Correcting positron emission tomography (PET) images for the partial volume effect (PVE) due to the limited resolution of PET has been a long-standing challenge. Various approaches including incorporation of the system response function in the reconstruction have been previously tested. We present a post-reconstruction PVE correction based on iterative deconvolution using a 3D maximum likelihood expectation-maximization (MLEM) algorithm. To achieve convergence we used a one step late (OSL) regularization procedure based on the assumption of local monotonic behavior of the PET signal following Alenius et al. This technique was further modified to selectively control variance depending on the local topology of the PET image. No prior 'anatomic' information is needed in this approach. An estimate of the noise properties of the image is used instead. The procedure was tested for symmetric and isotropic deconvolution functions with Gaussian shape and full width at half-maximum (FWHM) ranging from 6.31 mm to infinity. The method was applied to simulated and experimental scans of the NEMA NU 2 image quality phantom with the GE Discovery LS PET/CT scanner. The phantom contained uniform activity spheres with diameters ranging from 1 cm to 3.7 cm within uniform background. The optimal sphere activity to variance ratio was obtained when the deconvolution function was replaced by a step function few voxels wide. In this case, the deconvolution method converged in approximately 3-5 iterations for most points on both the simulated and experimental images. For the 1 cm diameter sphere, the contrast recovery improved from 12% to 36% in the simulated and from 21% to 55% in the experimental data. Recovery coefficients between 80% and 120% were obtained for all larger spheres, except for the 13 mm diameter sphere in the simulated scan (68%). No increase in variance was observed except for a few voxels neighboring strong activity gradients and inside the largest spheres. Testing the method for patient images increased the visibility of small lesions in non-uniform background and preserved the overall image quality. Regularized iterative deconvolution with variance control based on the local properties of the PET image and on estimated image noise is a promising approach for partial volume effect corrections in PET.
    MeSH term(s) Humans ; Image Processing, Computer-Assisted/methods ; Lung Neoplasms/diagnostic imaging ; Phantoms, Imaging ; Positron-Emission Tomography/methods
    Language English
    Publishing date 2008-05-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 208857-5
    ISSN 1361-6560 ; 0031-9155
    ISSN (online) 1361-6560
    ISSN 0031-9155
    DOI 10.1088/0031-9155/53/10/009
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  2. Article ; Online: Using an external gating signal to estimate noise in PET with an emphasis on tracer avid tumors.

    Schmidtlein, C R / Beattie, B J / Bailey, D L / Akhurst, T J / Wang, W / Gönen, M / Kirov, A S / Humm, J L

    Physics in medicine and biology

    2010  Volume 55, Issue 20, Page(s) 6299–6326

    Abstract: The purpose of this study is to establish and validate a methodology for estimating the standard deviation of voxels with large activity concentrations within a PET image using replicate imaging that is immediately available for use in the clinic. To do ... ...

    Abstract The purpose of this study is to establish and validate a methodology for estimating the standard deviation of voxels with large activity concentrations within a PET image using replicate imaging that is immediately available for use in the clinic. To do this, ensembles of voxels in the averaged replicate images were compared to the corresponding ensembles in images derived from summed sinograms. In addition, the replicate imaging noise estimate was compared to a noise estimate based on an ensemble of voxels within a region. To make this comparison two phantoms were used. The first phantom was a seven-chamber phantom constructed of 1 liter plastic bottles. Each chamber of this phantom was filled with a different activity concentration relative to the lowest activity concentration with ratios of 1:1, 1:1, 2:1, 2:1, 4:1, 8:1 and 16:1. The second phantom was a GE Well-Counter phantom. These phantoms were imaged and reconstructed on a GE DSTE PET/CT scanner with 2D and 3D reprojection filtered backprojection (FBP), and with 2D- and 3D-ordered subset expectation maximization (OSEM). A series of tests were applied to the resulting images that showed that the region and replicate imaging methods for estimating standard deviation were equivalent for backprojection reconstructions. Furthermore, the noise properties of the FBP algorithms allowed scaling the replicate estimates of the standard deviation by a factor of 1/square root N, where N is the number of replicate images, to obtain the standard deviation of the full data image. This was not the case for OSEM image reconstruction. Due to nonlinearity of the OSEM algorithm, the noise is shown to be both position and activity concentration dependent in such a way that no simple scaling factor can be used to extrapolate noise as a function of counts. The use of the Well-Counter phantom contributed to the development of a heuristic extrapolation of the noise as a function of radius in FBP. In addition, the signal-to-noise ratio for high uptake objects was confirmed to be higher with backprojection image reconstruction methods. These techniques were applied to several patient data sets acquired in either 2D or 3D mode, with (18)F (FLT and FDG). Images of the standard deviation and signal-to-noise ratios were constructed and the standard deviations of the tumors' uptake were determined. Finally, a radial noise extrapolation relationship deduced in this paper was applied to patient data.
    MeSH term(s) Algorithms ; Biological Transport ; Humans ; Image Processing, Computer-Assisted/methods ; Imaging, Three-Dimensional ; Neoplasms/diagnostic imaging ; Neoplasms/metabolism ; Phantoms, Imaging ; Positron-Emission Tomography/methods ; Radioactive Tracers ; Software
    Chemical Substances Radioactive Tracers
    Language English
    Publishing date 2010-10-21
    Publishing country England
    Document type Journal Article
    ZDB-ID 208857-5
    ISSN 1361-6560 ; 0031-9155
    ISSN (online) 1361-6560
    ISSN 0031-9155
    DOI 10.1088/0031-9155/55/20/016
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  3. Article: An iterative technique to segment PET lesions using a Monte Carlo based mathematical model.

    Nehmeh, S A / El-Zeftawy, H / Greco, C / Schwartz, J / Erdi, Y E / Kirov, A / Schmidtlein, C R / Gyau, A B / Larson, S M / Humm, J L

    Medical physics

    2009  Volume 36, Issue 10, Page(s) 4803–4809

    Abstract: Purpose: The need for an accurate lesion segmentation tool in 18FDG PET is a prerequisite for the estimation of lesion response to therapy, for radionuclide dosimetry, and for the application of 18FDG PET to radiotherapy planning. In this work, the ... ...

    Abstract Purpose: The need for an accurate lesion segmentation tool in 18FDG PET is a prerequisite for the estimation of lesion response to therapy, for radionuclide dosimetry, and for the application of 18FDG PET to radiotherapy planning. In this work, the authors have developed an iterative method based on a mathematical fit deduced from Monte Carlo simulations to estimate tumor segmentation thresholds.
    Methods: The GATE software, a GEANT4 based Monte Carlo tool, was used to model the GE Advance PET scanner geometry. Spheres ranging between 1 and 6 cm in diameters were simulated in a 10 cm high and 11 cm in diameter cylinder. The spheres were filled with water-equivalent density and simulated in both water and lung equivalent background. The simulations were performed with an infinite, 8/1, and 4/1 target-to-background ratio (T/B). A mathematical fit describing the correlation between the lesion volume and the corresponding optimum threshold value was then deduced through analysis of the reconstructed images. An iterative method, based on this mathematical fit, was developed to determine the optimum threshold value. The effects of the lesion volume and T/B on the threshold value were investigated. This method was evaluated experimentally using the NEMA NU2-2001 IEC phantom, the ACNP cardiac phantom, a randomly deformed aluminum can, and a spheroidal shape phantom implemented artificially in the lung, liver, and brain of patient PET images. Clinically, the algorithm was evaluated in six lesions from five patients. Clinical results were compared to CT volumes.
    Results: This mathematical fit predicts an existing relationship between the PET lesion size and the percent of maximum activity concentration within the target volume (or threshold). It also showed a dependence of the threshold value on the T/B, which could be eliminated by background subtraction. In the phantom studies, the volumes of the segmented PET targets in the PET images were within 10% of the nominal ones. Clinically, the PET target volumes were also within 10% of those measured from CT images.
    Conclusions: This iterative algorithm enabled accurately segment PET lesions, independently of their contrast value.
    MeSH term(s) Algorithms ; Artificial Intelligence ; Computer Simulation ; Data Interpretation, Statistical ; Humans ; Image Enhancement/methods ; Image Interpretation, Computer-Assisted/methods ; Models, Biological ; Models, Statistical ; Monte Carlo Method ; Neoplasms/diagnostic imaging ; Pattern Recognition, Automated/methods ; Phantoms, Imaging ; Positron-Emission Tomography/instrumentation ; Positron-Emission Tomography/methods ; Reproducibility of Results ; Sensitivity and Specificity ; Software
    Language English
    Publishing date 2009-10
    Publishing country United States
    Document type Journal Article
    ZDB-ID 188780-4
    ISSN 0094-2405
    ISSN 0094-2405
    DOI 10.1118/1.3222732
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 1210: Show issues Location:
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  4. Article: GATE: a simulation toolkit for PET and SPECT.

    Jan, S / Santin, G / Strul, D / Staelens, S / Assié, K / Autret, D / Avner, S / Barbier, R / Bardiès, M / Bloomfield, P M / Brasse, D / Breton, V / Bruyndonckx, P / Buvat, I / Chatziioannou, A F / Choi, Y / Chung, Y H / Comtat, C / Donnarieix, D /
    Ferrer, L / Glick, S J / Groiselle, C J / Guez, D / Honore, P F / Kerhoas-Cavata, S / Kirov, A S / Kohli, V / Koole, M / Krieguer, M / van der Laan, D J / Lamare, F / Largeron, G / Lartizien, C / Lazaro, D / Maas, M C / Maigne, L / Mayet, F / Melot, F / Merheb, C / Pennacchio, E / Perez, J / Pietrzyk, U / Rannou, F R / Rey, M / Schaart, D R / Schmidtlein, C R / Simon, L / Song, T Y / Vieira, J M / Visvikis, D / Van de Walle, R / Wieërs, E / Morel, C

    Physics in medicine and biology

    2004  Volume 49, Issue 19, Page(s) 4543–4561

    Abstract: Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols and the development or assessment of image reconstruction algorithms and correction ...

    Abstract Monte Carlo simulation is an essential tool in emission tomography that can assist in the design of new medical imaging devices, the optimization of acquisition protocols and the development or assessment of image reconstruction algorithms and correction techniques. GATE, the Geant4 Application for Tomographic Emission, encapsulates the Geant4 libraries to achieve a modular, versatile, scripted simulation toolkit adapted to the field of nuclear medicine. In particular, GATE allows the description of time-dependent phenomena such as source or detector movement, and source decay kinetics. This feature makes it possible to simulate time curves under realistic acquisition conditions and to test dynamic reconstruction algorithms. This paper gives a detailed description of the design and development of GATE by the OpenGATE collaboration, whose continuing objective is to improve, document and validate GATE by simulating commercially available imaging systems for PET and SPECT. Large effort is also invested in the ability and the flexibility to model novel detection systems or systems still under design. A public release of GATE licensed under the GNU Lesser General Public License can be downloaded at http:/www-lphe.epfl.ch/GATE/. Two benchmarks developed for PET and SPECT to test the installation of GATE and to serve as a tutorial for the users are presented. Extensive validation of the GATE simulation platform has been started, comparing simulations and measurements on commercially available acquisition systems. References to those results are listed. The future prospects towards the gridification of GATE and its extension to other domains such as dosimetry are also discussed.
    MeSH term(s) Computer Simulation ; Monte Carlo Method ; Reproducibility of Results ; Software ; Thermodynamics ; Tomography, Emission-Computed, Single-Photon/methods
    Language English
    Publishing date 2004-11-08
    Publishing country England
    Document type Journal Article ; Research Support, Non-U.S. Gov't ; Research Support, U.S. Gov't, P.H.S.
    ZDB-ID 208857-5
    ISSN 1361-6560 ; 0031-9155
    ISSN (online) 1361-6560
    ISSN 0031-9155
    DOI 10.1088/0031-9155/49/19/007
    Database MEDical Literature Analysis and Retrieval System OnLINE

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