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| FEATURED STORIES - SEPTEMBER 2018 | ||
Organ-Dedicated Molecular Imaging Systemsby Antonio J. Gonzáplez, Filomeno Sánchez, and José M. Benlloch In this review we will cover both clinical and technical aspects of the advantages and disadvantages of organ specific (dedicated) molecular imaging systems, namely PET and SPECT, including gamma cameras. This review will start with the introduction to the organ-dedicated molecular imaging systems. Thereafter we will describe the differences and their advantages/disadvantages when compared with the standard large size scanners. We will review time evolution of dedicated systems, from first attempts to current scanners, and the ones that ended in clinical use. We will review later the state of the art of these systems for different organs, namely: breast, brain, heart, and prostate. We will also present the advantages offered by these systems as a function of the special application or field, such as in surgery, therapy assistance and assessment, etc. Their technological evolution will be introduced for each organ-based imager. Some of the advantages of dedicated devices are: higher sensitivity by placing the detectors closer to the organ, improved spatial resolution, better image contrast recovery (by reducing the noise from other organs), and also lower cost. Designing a complete ring-shaped dedicated PET scanner is sometimes difficult and limited angle tomography systems are preferable as they have more flexibility in placing the detectors around the body/organ. Examples of these geometries will be presented for breast, prostate and heart imaging. Recently achievable excellent TOF capabilities below 300 ps FWHM reduce significantly the impact of missing angles on the reconstructed images. more... |
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Performance study of a radio-frequency field-penetrable PET insert for simultaneous PET/MRIby Chen-Ming Chang, Brian J. Lee, Alexander M. Grant, Andrew N. Groll, and Craig S. Levin Hybrid positron emission tomography (PET)/magnetic resonance imaging (MRI) has risen to the cutting edge of medical imaging technology as it allows simultaneous acquisition of structural, functional and molecular information of the patient. A PET insert that can be installed into existing MR systems can in principle reduce the cost barriers for an existing MR site to achieve simultaneous PET/MRI compared to procuring an integrated PET+MRI system. The PET insert systems developed so far for PET/MRI require the RF transmitter coil to reside inside the PET ring as those PET inserts block the RF fields from the MRI system. Here we report for the first time on the performance of a full-ring brain-sized “RF-penetrable” PET insert we have recently completed. This insert allows the RF fields generated by the built-in body coil to penetrate the PET ring. The PET insert comprises a ring of 16 detector modules employing electro-optical coupled signal transmission and a multiplexing framework based on compressed sensing. Energy resolution, coincidence timing resolution (CTR), photopeak position, and coincidence count rate were acquired outside and inside a 3-Tesla MRI system under simultaneous acquisition to evaluate the impact of MRI on the PET performance. Coincidence count rate performance was evaluated by acquiring a cylinder source with high initial activity decaying over time. Tomographic imaging of two phantoms, a custom 6.5-cm diameter resolution phantom with hot rods of four different sizes (2.8 mm, 3.2 mm, 4.2 mm, and 5.2 mm diameter) and a 3D Hoffman brain phantom, were performed to evaluate the imaging capability of the PET insert. The energy resolution at 511 keV and CTR acquired by the PET insert were 16.2±0.1% and 5.3±0.1 ns FWHM, respectively, and remained stable during MRI operation except when the EPI sequence was applied. The PET system starts to show saturation in coincidence count rate at 2.76 million photon counts per second. Most of the 2.8-mm diameter hot rods and main features of the 3D Hoffman brain phantom were resolved by the PET insert, demonstrating its high spatial resolution and capability to image a complex tracer distribution mimicking that seen in the human brain. more... |
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Spatially-Compact MR-Guided Kernel EM for PET Image Reconstructionby James Bland, Martin A. Belzunce, Sam Ellis, Colm J. McGinnity, Alexander Hammers and Andrew J. Reader Positron emission tomography (PET) is a highly sensitive functional and molecular imaging modality which can measure picomolar concentrations of an injected radionuclide. However, the physical sensitivity of PET is limited, and reducing the injected dose leads to low count data and noisy reconstructed images. A highly effective way of reducing noise is to reparameterise the reconstruction in terms of MR-derived spatial basis functions. Spatial basis functions derived using the kernel method have demonstrated excellent noise reduction properties and maintain shared PET-MR detailed structures. However, as previously shown in the literature, the MR-guided kernel method may lead to excessive smoothing of structures that are only present in the PET data. This work makes two main contributions in order to address this problem: first, we exploit the potential of the MR-guided kernel method to form more spatially-compact basis functions which are able to preserve PET-unique structures, and secondly, we consider reconstruction at the native MR resolution. The former contribution notably improves the recovery of structures which are unique to the PET data. These adaptations of the kernel method were compared to the conventional implementation of the MR-guided kernel method and also to MLEM, in terms of ability to recover PET unique structures for both simulated and real data. The spatially-compact kernel method showed clear visual and quantitative improvements in the reconstruction of the PET unique structures, relative to the conventional kernel method for all sizes of PET unique structures investigated, whilst maintaining to a large extent the impressive noise mitigating and detail preserving properties of the conventional MR-guided kernel method. We therefore conclude that a spatially-compact parameterisation of the MR-guided kernel method, should be the preferred implementation strategy in order to obviate unnecessary losses in PET-unique details. more... |
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Gradient Tree Boosting-based Positioning Method for Monolithic Scintillator Crystals in Positron Emission Tomographyby Florian Muller, David Schug, Patrick Hallen, Jan Grahe, Volkmar Schulz Monolithic crystals are considered as an alternative for complex segmented scintillator arrays in Positron Emission Tomography (PET) systems. Monoliths provide high sensitivity, good timing and energy resolution while being cheaper than highly segmented arrays. Furthermore, monoliths enable intrinsic depth of interaction capabilities and good spatial resolutions mostly based on statistical calibrations. To widely translate monoliths into clinical applications, a time-efficient calibration method and a positioning algorithm implementable in system architecture such as FPGAs are required. We present a novel positioning algorithm based on Gradient Tree Boosting (GTB) and a fast fan beam calibration requiring less than 1h per detector block. GTB is a supervised machine learning technique building a set of sequential binary decisions (decision trees). The algorithm handles different sets of input features, their combinations and partially missing data. GTB models are strongly adaptable influencing both the positioning performance and the memory requirement of trained positioning models. For an FPGA-implementation, the memory requirement is the limiting aspect. We demonstrate a general optimization and propose two different optimization scenarios: One without compromising on positioning performance and one optimizing the positioning performance for a given memory restriction. For a 12mm high LYSO-block, we achieve a spatial resolution better than 1.4mm FWHM. more... |
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A PUBLICATION OF THE IEEE NUCLEAR AND PLASMA SCIENCES SOCIETY |
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| SEPTEMBER 2018 | VOLUME 2 | NUMBER 5 | ITRPFI | (SSN 2469-7311) | ||
REVIEW Organ-Dedicated Molecular Imaging Systems . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. J. González, F. Sánchez, and J. M. Benlloch SCINTILLATORS AND DETECTORS A SiPM-Readout ASIC for SPECT Applications . . . . . . . . . . . . . . . . . . . . . P. Trigilio, P. Busca, R. Quaglia, M. Occhipinti, and C. Fiorini Gradient Tree Boosting-Based Positioning Method for Monolithic Scintillator Crystals in Positron Emission Tomography . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . F. Müller, D. Schug, P. Hallen, J. Grahe, and V. Schulz CAMERA DESIGN AND IMAGING PERFORMANCE Performance Study of a Radio-Frequency Field-Penetrable PET Insert for Simultaneous PET/MRI . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . C.-M. Chang, B. J. Lee, A. M. Grant, A. N. Groll, and C. S. Levin Simulation and Design Considerations of a Dual Layer Plastic Scintillator Intraoperative Probe for Radiolabeled Tumours . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. A. Belzunce, S. Lomazzi, M. Beretta, M. Caccia, and A. J. Reader Simulations of a Multipinhole SPECT Collimator for Clinical Dopamine Transporter (DAT) Imaging . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Könik, J. D. Beenhouwer, J. M. Mukherjee, K. Kalluri, S. Banerjee, N. Zeraatkar, T. Fromme, and M. A. King Tungsten Target Optimization for Photon Fluence Maximization of a Transmission-Type Flat-Panel X-Ray Source by Monte Carlo Simulation and Experimental Measurement . . . . . . K. Wang, Y. Xu, D. Chen, G. Zhang, Z. Zhang, J. She, S. Deng, N. Xu, and J. Chen IMAGE RECONSTRUCTION AND DATA PROCESSING QR-Factorization Algorithm for Computed Tomography (CT): Comparison With FDK and Conjugate Gradient (CG) Algorithms . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . M. J. Rodríguez-Alvarez, F. Sánchez, A. Soriano, L. Moliner, S. Sánchez, and J. M. Benlloch Spatially Compact MR-Guided Kernel EM for PET Image Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . J. Bland, M. A. Belzunce, S. Ellis, C. J. McGinnity, A. Hammers, and A. J. Reader PET-MR Attenuation Correction in Dynamic Brain PET Using [11C]Cimbi-36: A Direct Comparison With PET-CT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . A. Mansur, R. Newbould, G. E. Searle, C. Redstone, R. N. Gunn, and W. A. Hallett Evaluation of Median Root Prior for Robust In-Beam PET Reconstruction . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . D. Us, K. Brzezinski, T. Buitenhuis, P. Dendooven, and U. Ruotsalainen Multitracer Guided PET Image Reconstruction . . . . . . . . . . . . . . . . . . . S. Ellis, A. Mallia, C. J. McGinnity, G. J. R. Cook, and A. J. Reader RADIATION THERAPY Optimization of the Signal-to-Background Ratio in Prompt Gamma Imaging Using Energy and Shifting Time-of-Flight Discrimination: Experiments With a Scanning Parallel-Slit Collimator . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . P. Cambraia Lopes, P. Crespo, J. Huizenga, and D. R. Schaart PLASMA MEDICINE Bioactive Plasma Sprayed Coatings on Polymer Substrates Suitable for Orthopedic Applications: A Study With PEEK . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . L. Barillas, H. Testrich, J. M. Cubero-Sesin, A. Quade, V. I. Vargas, M. Polak, and K. Fricke |
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