IEEE Nuclear Science Symposium conference record. Nuclear Science Symposium最新文献

We report on the implementation and hardware platform of a real time Statistics-Based Processing (SBP) method with depth of interaction processing for continuous miniature crystal element (cMiCE) detectors using a sensor on the entrance surface design. Our group previously reported on a Field Programmable Gate Array (FPGA) SBP implementation that provided a two dimensional (2D) solution of the detector's intrinsic spatial resolution. This new implementation extends that work to take advantage of three dimensional (3D) look up tables to provide a 3D positioning solution that improves intrinsic spatial resolution. Resolution is most improved along the edges of the crystal, an area where the 2D algorithm's performance suffers. The algorithm allows an intrinsic spatial resolution of ~0.90 mm FWHM in X and Y and a resolution of ~1.90 mm FWHM in Z (i.e., the depth of the crystal) based upon DETECT2000 simulation results that include the effects of Compton scatter in the crystal. A pipelined FPGA implementation is able to process events in excess of 220k events per second, which is greater than the maximum expected coincidence rate for an individual detector. In contrast to all detectors being processed at a centralized host, as in the current system, a separate FPGA is available at each detector, thus dividing the computational load. A prototype design has been implemented and tested using a reduced word size due to memory limitations of our commercial prototyping board.

Previously, we presented a direct EM method for producing kinetic parameter images from list mode PET data, where the time-activity curve for each voxel is described by a one-tissue compartment model (1T). The initial evaluations were performed with simulations, without motion, randoms, or scatter effects included. By extension of our previous frame-based physics correction methods, a practical direct 4D parametric reconstruction algorithm is now proposed and implemented for human data. Initial evaluations were performed using 3 human subjects with the serotonin transporter tracer [(11)C]AFM. Comparisons with the 2-step approach (frame-based reconstruction followed by voxel-by-voxel parameter estimation) provided encouraging initial results. Regional analysis showed that the 2-step and 4D methods have similar K(1) and V(T) values, but with a consistent difference. Visual analysis showed some noise reduction in 4D. These initial results suggest that direct 4D parametric reconstruction can be performed with real data, and offers the potential for improved accuracy and precision over the 2-step frame method.

Continuous miniature crystal element (cMiCE) detectors are a potentially lower cost alternative to high resolution discrete crystal designs. We report on the intrinsic spatial resolution performance for two cMiCE PET detector designs with depth of interaction (DOI) positioning capability. The first detector utilizes a 50 mm by 50 mm by 8 mm LYSO crystal coupled to a 64 channel, multi-anode PMT. It provides 4 layers of DOI information. The crystal has beveled edges along two of its sides to improve the detector packing when placed in a ring geometry. The second detector utilizes a 50 mm by 50 mm by 15 mm, rectangular LYSO crystal coupled to a 64 channel, multi-anode PMT. It provides up to 15 layers of DOI information. The average intrinsic X, Y spatial resolution for the 8 mm thick, truncated crystal detector was 1.33 +/- 0.31 mm FWHM (45.6 mm by 46.6 mm useful imaging area). The average DOI resolution was 3.5 +/- 0.22 mm. The average intrinsic X, Y spatial resolution for the 15 mm thick crystal detector was 1.74 +/- 0.35 mm FWHM (44.6 mm by 44.6 mm useful imaging area). In addition, the average DOI spatial resolution for 56 test points spanning a 26.4 mm by 12.2 mm region of the crystal was 4.80 +/- 0.36 mm. We believe the 8 mm thick truncated crystal design is suitable for mouse imaging while the 15 mm thick crystal design is more suited for human organ specific imaging systems (e.g., breast and brain).

This work presents a row/column summing readout electronics for an 8×8 silicon photomultiplier array. The summation circuit greatly reduces the number of electronic channels, which is desirable for pursuing higher resolution positron emission tomography scanners. By using a degenerated common source topology in the summation circuit, more fan-in is possible and therefore a greater reduction in the number of electronic channels can be achieved. The timing signal is retrieved from a common anode, which allows the use of a single fast-sampling analog to digital converter (ADC) for the timing channel and slower, lower power ADCs for the 64 spatial channels. Preliminary results of one row summation of the 8×8 readout electronics exhibited FWHM energy resolution of 17.8% and 18.3% with and without multiplexing, respectively. The measured timing resolution is 2.9ns FWHM.

The performance characteristics of a monolithic crystal PET detector utilizing a novel sensor on the entrance surface (SES) design is reported. To facilitate this design, we propose to utilize a 2D silicon photomultiplier (SiPM) array device. SiPMs are a form of Geiger-Muller mode avalanche photodiodes (GMAPD) that can provide signal gain similar to a photomultiplier tube (PMT). Since these devices are still under active development, their performance parameters are changing. Using a multi-step simulation process, we investigated how different SiPM parameters affect the performance of a monolithic crystal PET detector. These parameters include gain variability between different channels; gain instability; and dark count noise. The detector simulated was a 49.6 mm by 49.6 mm by 15 mm LYSO crystal detector readout by a 16 by 16 array of 2.8 mm by 2.8 mm SiPM elements. To reduce the number of signal channels that need to be collected, the detector utilizes row-column summing. A statistics based positioning method is used for event positioning and depth of interaction (DOI) decoding. Of the variables investigated, the dark count noise had the largest impact on the intrinsic spatial resolution. Gain differences of 5-10% between detector calibration and detector testing had a modest impact on the intrinsic spatial resolution performance and led to a slight bias in positioning. There was no measurable difference with a gain variability of up to 25% between the individual SiPM channels. Based upon these results we are planning to cool our detectors below room temperature to reduce dark count noise and to actively control the temperature of the SiPMs to reduce drifts in gain over time.

Advances in 3D rapid-prototyping printers, 3D modeling software, and casting techniques allow for the fabrication of cost-effective, custom components in gamma-ray and x-ray imaging systems. Applications extend to new fabrication methods for custom collimators, pinholes, calibration and resolution phantoms, mounting and shielding components, and imaging apertures. Details of the fabrication process for these components are presented, specifically the 3D printing process, cold casting with a tungsten epoxy, and lost-wax casting in platinum.

We present an algorithm for accurate localization of block detectors in a positron emission tomography (PET) scanner. Accurate reconstruction of PET images requires precise knowledge of the physical position and orientation of the detectors. However, in some systems, block detector positioning and orientation can have relatively large tolerances, leading to implicit errors in the coincidence line-of-response (LOR) positioning. To compensate we utilize a rotating point source phantom where the rotational angle of the phantom is used to precisely determine the location of each scintillator crystal within a detector block. The aggregate block positions are then applied to the system model to determine the true location of each LOR. Images reconstructed with the more accurate LOR positioning demonstrate improved image fidelity.

Motion correction in PET has become more important as system resolution has improved. The purpose of this study was to evaluate the accuracy of three motion compensation methods, event-by-event motion compensation with list-mode reconstruction (MOLAR), frame-based motion correction, and post-reconstruction image registration. Motion compensated image reconstructions were carried out with simulated HRRT data, using a range of motion information based on human motion data. ROI analyses in high contrast regions were performed to evaluate the accuracy of all the motion compensation methods, with particular attention to within-frame motion.Our study showed that MOLAR with list-mode based motion correction using accurate motion data can reliably correct for all reasonable head motions. Over all motions, the average ROI count was within 0.1±4.2% and 0.7±0.9% of the reference, no-motion value for two different ROIs. The location of the ROI centroid was found to be within 0.7±0.3mm of that of the reference image for the raphe nucleus. Frame-based motion compensation and post-reconstruction image registration were able to correct for small (<5mm), but the ROI intensity begins to deteriorate for medium motions (5-10mm), especially for small brain structures such as the raphe nucleus. For large (>10mm) motions, the average centroid locations of the raphe nucleus ROI had an offset error of 1.5±1.8mm and 1.8±1.8mm for each of the frame-based methods. For each frame-based method, the decrease in the average ROI intensity was 16.9±4.3% and 20.2±9.9% respectively for the raphe nucleus, and was 5.5±2.2% and 7.4±0.2% for putamen. Based on these data, we conclude that event-by-event based motion correction works accurately for all reasonable motions, whereas frame-based motion correction is accurate only when the within-frame motion is less than 10mm.

Modern Field Programmable Gate Arrays (FPGAs) are capable of performing complex digital signal processing algorithms with clock rates well above 100MHz. This, combined with FPGA's low expense and ease of use make them an ideal technology for a data acquisition system for a positron emission tomography (PET) scanner. The University of Washington is producing a series of high-resolution, small-animal PET scanners that utilize FPGAs as the core of the front-end electronics. For these next generation scanners, functions that are typically performed in dedicated circuits, or offline, are being migrated to the FPGA. This will not only simplify the electronics, but the features of modern FPGAs can be utilizes to add significant signal processing power to produce higher resolution images. In this paper we report how we utilize the reconfigurable property of an FPGA to self-calibrate itself to determine pulse parameters necessary for some of the pulse processing steps. Specifically, we show how the FPGA can generate a reference pulse based on actual pulse data instead of a model. We also report how other properties of the photodetector pulse (baseline, pulse length, average pulse energy and event triggers) can be determined automatically by the FPGA.