247 research outputs found

    Model-based correction for scatter and tailing effects in simultaneous 99mTc and 123I imaging for a CdZnTe cardiac SPECT camera

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    2015 Institute of Physics and Engineering in Medicine. An advantage of semiconductor-based dedicated cardiac single photon emission computed tomography (SPECT) cameras when compared to conventional Anger cameras is superior energy resolution. This provides the potential for improved separation of the photopeaks in dual radionuclide imaging, such as combined use of 99mTc and 123I . There is, however, the added complexity of tailing effects in the detectors that must be accounted for. In this paper we present a model-based correction algorithm which extracts the useful primary counts of 99mTc and 123I from projection data. Equations describing the in-patient scatter and tailing effects in the detectors are iteratively solved for both radionuclides simultaneously using a maximum a posteriori probability algorithm with one-step-late evaluation. Energy window-dependent parameters for the equations describing in-patient scatter are estimated using Monte Carlo simulations. Parameters for the equations describing tailing effects are estimated using virtually scatter-free experimental measurements on a dedicated cardiac SPECT camera with CdZnTe-detectors. When applied to a phantom study with both 99mTc and 123I, results show that the estimated spatial distribution of events from 99mTc in the 99mTc photopeak energy window is very similar to that measured in a single 99mTc phantom study. The extracted images of primary events display increased cold lesion contrasts for both 99mTc and 123I

    Deep Boosted Regression for MR to CT Synthesis

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    Attenuation correction is an essential requirement of positron emission tomography (PET) image reconstruction to allow for accurate quantification. However, attenuation correction is particularly challenging for PET-MRI as neither PET nor magnetic resonance imaging (MRI) can directly image tissue attenuation properties. MRI-based computed tomography (CT) synthesis has been proposed as an alternative to physics based and segmentation-based approaches that assign a population-based tissue density value in order to generate an attenuation map. We propose a novel deep fully convolutional neural network that generates synthetic CTs in a recursive manner by gradually reducing the residuals of the previous network, increasing the overall accuracy and generalisability, while keeping the number of trainable parameters within reasonable limits. The model is trained on a database of 20 pre-acquired MRI/CT pairs and a four-fold random bootstrapped validation with a 80:20 split is performed. Quantitative results show that the proposed framework outperforms a state-of-the-art atlas-based approach decreasing the Mean Absolute Error (MAE) from 131HU to 68HU for the synthetic CTs and reducing the PET reconstruction error from 14.3% to 7.2%.Comment: Accepted at SASHIMI201

    Integration of advanced 3D SPECT modelling for pinhole collimators into the open-source STIR framework

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    Single-photon emission computed tomography (SPECT) systems with pinhole collimators are becoming increasingly important in clinical and preclinical nuclear medicine investigations as they can provide a superior resolution-sensitivity trade-off compared to conventional parallel-hole and fanbeam collimators. Previously, open-source software did not exist for reconstructing tomographic images from pinhole-SPECT datasets. A 3D SPECT system matrix modelling library specific for pinhole collimators has recently been integrated into STIR—an open-source software package for tomographic image reconstruction. The pinhole-SPECT library enables corrections for attenuation and the spatially variant collimator–detector response by incorporating their effects into the system matrix. Attenuation correction can be calculated with a simple single line-of-response or a full model. The spatially variant collimator–detector response can be modelled with point spread function and depth of interaction corrections for increased system matrix accuracy. In addition, improvements to computational speed and memory requirements can be made with image masking. This work demonstrates the flexibility and accuracy of STIR’s support for pinhole-SPECT datasets using measured and simulated single-pinhole SPECT data from which reconstructed images were analysed quantitatively and qualitatively. The extension of the open-source STIR project with advanced pinhole-SPECT modelling will enable the research community to study the impact of pinhole collimators in several SPECT imaging scenarios and with different scanners

    Design of a low-dose, stationary, tomographic Molecular Breast Imaging system using 3D position sensitive CZT detectors

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    Molecular Breast Imaging (MBI) has been shown to have high sensitivity for lesion detection, particularly in patients with dense breasts where conventional mammography is limited. However, relatively high radiation dose and long imaging time are limiting factors. Most current MBI systems are based on planar imaging. Improved performance can be achieved using tomographic techniques, which normally involve detector motion. Our goal is to develop a low-dose stationary tomographic MBI system with similar or better performance in terms of lesion detection compared to planar MBI. The proposed system utilizes two opposing CZT detectors with high intrinsic resolution and depth of interaction (DOI) capability, combined with densely packed multi-pinhole collimators. This leads to improved efficiency and adequate angular sampling, but also to significant multiplexing (MX), which can result in artefacts. We have developed de-MX algorithms that take advantage of the DOI information. We have performed both analytic and Monte Carlo simulations to demonstrate the feasibility, optimize the design and investigate the expected performance of the proposed system. Lesion detectability was preserved with reduction of acquisition time (or radiation dose) by a factor of 2 compared to planar images at the lowest reported dose. The first prototype is under evaluation at Kromek

    Systematic Evaluation of the Impact of Involuntary Motion in Whole Body Dynamic PET

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    Involuntary patient motion can happen in dynamic whole body (DWB) PET due to long scanning times, which may cause inaccurate quantification of tissue parameters. To quantify the impact on Patlak parameters, we simulated dynamic data using patient-derived motion fields, systematically introducing the motion at different passes of the dynamic scan, both inter and intra-frame. Estimated parameters are compared against the ground truth. Results show that errors can be large, even for small motion. Caution is advised when quantitatively evaluating DWB-PET images, if any motion has been detected

    ASL-incorporated pharmacokinetic modelling of PET data with reduced acquisition time: Application to amyloid imaging

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    Pharmacokinetic analysis of Positron Emission Tomography (PET) data typically requires at least one hour of image acquisition, which poses a great disadvantage in clinical practice. In this work, we propose a novel approach for pharmacokinetic modelling with significantly reduced PET acquisition time, by incorporating the blood flow information from simultaneously acquired arterial spin labelling (ASL) magnetic resonance imaging (MRI). A relationship is established between blood flow, measured by ASL, and the transfer rate constant from plasma to tissue of the PET tracer, leading to modified PET kinetic models with ASL-derived flow information. Evaluation on clinical amyloid imaging data from an Alzheimer’s disease (AD) study shows that the proposed approach with the simplified reference tissue model can achieve amyloid burden estimation from 30 min [18F]florbetapir PET data and 5 min simultaneous ASL MR data, which is comparable with the estimation from 60 min PET data (mean error=−0.03). Conversely, standardised uptake value ratio (SUVR), the alternative measure from the data showed a positive bias in areas of higher amyloid burden (mean error=0.07)

    Towards accurate partial volume correction in (99m}^Tc oncology SPECT: perturbation for case-specific resolution estimation

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    BACKGROUND: Currently, there is no consensus on the optimal partial volume correction (PVC) algorithm for oncology imaging. Several existing PVC methods require knowledge of the reconstructed resolution, usually as the point spread function (PSF)-often assumed to be spatially invariant. However, this is not the case for SPECT imaging. This work aimed to assess the accuracy of SPECT quantification when PVC is applied using a case-specific PSF. METHODS: Simulations of SPECT [Formula: see text]Tc imaging were performed for a range of activity distributions, including those replicating typical clinical oncology studies. Gaussian PSFs in reconstructed images were estimated using perturbation with a small point source. Estimates of the PSF were made in situations which could be encountered in a patient study, including; different positions in the field of view, different lesion shapes, sizes and contrasts, noise-free and noisy data. Ground truth images were convolved with the perturbation-estimated PSF, and with a PSF reflecting the resolution at the centre of the field of view. Both were compared with reconstructed images and the root-mean-square error calculated to assess the accuracy of the estimated PSF. PVC was applied using Single Target Correction, incorporating the perturbation-estimated PSF. Corrected regional mean values were assessed for quantitative accuracy. RESULTS: Perturbation-estimated PSF values demonstrated dependence on the position in the Field of View and the number of OSEM iterations. A lower root mean squared error was observed when convolution of the ground truth image was performed with the perturbation-estimated PSF, compared with convolution using a different PSF. Regional mean values following PVC using the perturbation-estimated PSF were more accurate than uncorrected data, or data corrected with PVC using an unsuitable PSF. This was the case for both simple and anthropomorphic phantoms. For the simple phantom, regional mean values were within 0.7% of the ground truth values. Accuracy improved after 5 or more OSEM iterations (10 subsets). For the anthropomorphic phantoms, post-correction regional mean values were within 1.6% of the ground truth values for noise-free uniform lesions. CONCLUSION: Perturbation using a simulated point source could potentially improve quantitative SPECT accuracy via the application of PVC, provided that sufficient reconstruction iterations are used

    Performance evaluation of MAP algorithms with different penalties, object geometries and noise levels

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    A new algorithm (LBFGS-B-PC) which combines ideas of two existing convergent reconstruction algorithms, relaxed separable paraboloidal surrogate (SPS) and limited-memory Broyden-Fletcher-Goldfarb-Shanno with boundary constraints (LBFGS-B), is proposed. Its performance is evaluated in terms of log-posterior value and regional recovery ratio. The results demonstrate the superior convergence speed of the proposed algorithm to relaxed SPS and LBFGS-B, regardless of the noise level, activity distribution, object geometry, and penalties
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