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

Explicit fusion of perfusion data from Positron Emission Tomography (PET) or Single Photon Emission Computed Tomography (SPECT) with coronary artery anatomy from Computed Tomographic Coronary Angiography (CTCA) has been shown to improve the diagnostic yield for coronary artery disease (CAD) compared to either modality alone. However, most clinically available methods were developed for multimodal scanners or require interactive alignment prior to display and analysis. A new approach was developed to register and display the two distributions obtained either from a single multimodal imager or from separate scanners, and a preliminary validation was undertaken using interactive alignment by experts.

Use of an extensible array of Electron Multiplying CCDs (EMCCDs) in medical x-ray imager applications was demonstrated for the first time. The large variable electronic-gain (up to 2000) and small pixel size of EMCCDs provide effective suppression of readout noise compared to signal, as well as high resolution, enabling the development of an x-ray detector with far superior performance compared to conventional x-ray image intensifiers and flat panel detectors. We are developing arrays of EMCCDs to overcome their limited field of view (FOV). In this work we report on an array of two EMCCD sensors running simultaneously at a high frame rate and optically focused on a mammogram film showing calcified ducts. The work was conducted on an optical table with a pulsed LED bar used to provide a uniform diffuse light onto the film to simulate x-ray projection images. The system can be selected to run at up to 17.5 frames per second or even higher frame rate with binning. Integration time for the sensors can be adjusted from 1 ms to 1000 ms. Twelve-bit correlated double sampling AD converters were used to digitize the images, which were acquired by a National Instruments dual-channel Camera Link PC board in real time. A user-friendly interface was programmed using LabVIEW to save and display 2K × 1K pixel matrix digital images. The demonstration tiles a 2 × 1 array to acquire increased-FOV stationary images taken at different gains and fluoroscopic-like videos recorded by scanning the mammogram simultaneously with both sensors. The results show high resolution and high dynamic range images stitched together with minimal adjustments needed. The EMCCD array design allows for expansion to an M×N array for arbitrarily larger FOV, yet with high resolution and large dynamic range maintained.

We demonstrate the capability of one detector, the Micro-Angiographic Fluoroscope (MAF) detector, to image for two types of applications: nuclear medicine imaging and radiography. The MAF has 1024 × 1024 pixels with an effective pixel size of 35 microns and is capable of real-time imaging at 30 fps. It has a CCD camera coupled by a fiber-optic taper to a light image intensifier (LII) viewing a 300-micron thick CsI phosphor. The large variable gain of the LII provides quantum-limited operation with little additive instrumentation noise and enables operation in both energy-integrating (EI) and sensitive low-exposure single photon counting (SPC) modes. We used the EI mode to take a radiograph, and the SPC mode to image a custom phantom filled with 1 mCi of I-125. The phantom is made of hot rods with diameters ranging from 0.9 mm to 2.3 mm. A 1 mm diameter parallel hole, medium energy gamma camera collimator was placed between the phantom and the MAF and was moved multiple times at equal intervals in random directions to eliminate the grid pattern corresponding to the collimator septa. Data was acquired at 20 fps. Two algorithms to localize the events were used: 1) simple threshold and 2) a weighted centroid method. Although all the hot rods could be clearly identified, the image generated with the simple threshold method shows more blurring than that with the weighted centroid method. With the diffuse cluster of pixels from each single detection event localized to a single pixel, the weighted centroid method shows improved spatial resolution. A radiograph of the phantom was taken with the same MAF in EI mode without the collimator. It shows clear structural details of the rods. Compared to the radiograph, the sharpness of the emission image is limited by the collimator resolution and could be improved by optimized collimator design. This study demonstrated that the same MAF detector can be used in both radioisotope and x-ray imaging, combining the benefits of each.

We present a maximum-likelihood (ML) method for calibrating the geometrical parameters of an x-ray computed tomography (CT) system. This method makes use of the full image data and not a reduced set of data. This algorithm is particularly useful for CT systems that change their geometry during the CT acquisition, such as an adaptive CT scan. Our ML search method uses a contracting-grid algorithm that does not require initial starting values to perform its estimate, thus avoiding problems associated with choosing initialization values.

Current thick detectors used in medical imaging allow recording many attributes, such as the 3D location of interaction within the scintillation crystal and the amount of energy deposited. An efficient way of dealing with these data is by storing them in list-mode (LM). To reconstruct the data, maximum-likelihood expectation-maximization (MLEM) is efficiently applied to the list-mode data, resulting in the list-mode maximum-likelihood expectation-maximization (LMMLEM) reconstruction algorithm.In this work, we consider a PET system consisting of two thick detectors facing each other. PMT outputs are collected for each coincidence event and are used to perform 3D maximum-likelihood (ML) position estimation of location of interaction. The mathematical properties of the ML estimation allow accurate modeling of the detector blur and provide a theoretical framework for the subsequent estimation step, namely the LMMLEM reconstruction. Indeed, a rigorous statistical model for the detector output can be obtained from calibration data and used in the calculation of the conditional probability density functions for the interaction location estimates.Our implementation of the 3D ML position estimation takes advantage of graphics processing unit (GPU) hardware and permits accurate real-time estimates of position of interaction. The LMMLEM algorithm is then applied to the list of position estimates, and the 3D radiotracer distribution is reconstructed on a voxel grid.

Attenuation correction is necessary for SPECT quantification. There are a variety of methods to create attenuation maps. For dedicated breast SPECT imaging, it is unclear if either SPECT- or CT-based attenuation map would provide the most accurate quantification and whether or not segmenting the different tissue types will have an effect on the qunatification. For these experiments, ^99mTc diluted in methanol and water was filled into geometric and anthropomorphic breast phantoms and was imaged with a dedicated dual-modality SPECT-CT scanner. SPECT images were collected using a compact CZT camera with various 3D acquisitions including vertical and 30° tilted parallel beam, and complex sinusoidal trajectories. CT images were acquired using a quasi-monochromatic x-ray source and CsI(T1) flat panel digital detector in a half-cone beam geometry. Measured scatter correction for SPECT and CT were implemented. To compare photon attenuation correction in the reconstructed SPECT images, various volumetric attenuation matrices were derived from 1) uniform SPECT, 2) uniform CT, and 3) segmented CT, populated with different attenuation coefficient values. Comparisons between attenuation masks using phantoms consisting of materials with different attenuation values show that at 140 keV the differences in the attenuation between materials do not affect the quantification as much as the size and alignment of the attenuation map. The CT-based attenuation maps give quantitative values 30% below the actual value, but are consistent. While the SPECT-based attenuation maps can provide within 10% accurate quantitative values, but are less consistent.

We present an analysis of the effects of ultra-low dose X-ray computerized tomography (CT) based attenuation correction for positron emission tomography (PET). By ultra low dose we mean less than approximately 5 mAs or 0.5 mSv total effective whole body dose. The motivation is the increased interest in using respiratory motion information acquired during the CT scan for both phase-matched CT-based attenuation correction and for motion estimation. Since longer duration CT scans are desired, radiation dose to the patient can be a limiting factor. In this study we evaluate the impact of reducing photon flux rates in the CT data on the reconstructed PET image by using the CATSIM simulation tool for the CT component and the ASIM simulation tool for the PET component. The CT simulation includes effects of the x-ray tube spectra, beam conditioning, bowtie filter, detector noise, and bean hardening correction. The PET simulation includes the effect of attenuation and photon counting. Noise and bias in the PET image were evaluated from multiple realizations of test objects. We show that techniques can be used to significantly reduce the mAs needed for CT based attenuation correction if the CT is not used for diagnostic purposes. The limiting factor, however, is not the noise in the CT image but rather the bias introduced by CT sinogram elements with no detected flux. These results constrain the methods that can be used to lower CT dose in a manner suitable for attenuation correction of PET data. We conclude that ultra-low-dose CT for attenuation correction of PET data is feasible with current PET/CT scanners.

We describe a custom multiple-module multiplexer integrated circuit (MMMIC) that enables the combination of discrete Electron multiplying charge coupled devices (EMCCD) based imaging modules to improve medical imaging systems. It is highly desirable to have flexible imaging systems that provide high spatial resolution over a specific region of interest (ROI) and a field of view (FOV) large enough to encompass areas of clinical interest. Also, such systems should be dynamic, i.e. should be able to maintain a specified acquisition bandwidth irrespective of the size of the imaged FOV. The MMMIC achieves these goals by 1) multiplexing the outputs of an array of imaging modules to enable a larger FOV, 2) enabling a number of binning modes for adjustable high spatial resolution, and 3) enabling selection of a subset of modules in the array to achieve ROI imaging at a predetermined display bandwidth. The MMMIC design also allows multiple MMMICs to be connected to control larger arrays. The prototype MMMIC was designed and fabricated in the ON-SEMI 0.5μm CMOS process through MOSIS (www.mosis.org). It has three 12-bit inputs, a single 12-bit output, three input enable bits, and one output enable, so that one MMMIC can control the output from three discrete imager arrays. The modular design of the MMMIC enables four identical chips, connected in a two-stage sequential arrangement, to readout a 3×3 collection of individual imaging modules. The first stage comprises three MMMICs (each connected to three of the individual imaging module), and the second stage is a single MMMIC whose 12-bit output is then sent via a CameraLink interface to the system computer. The prototype MMMIC was successfully tested using digital outputs from two EMCCD-based detectors to be used in an x-ray imaging array detector system.Finally, we show how the MMMIC can be used to extend an imaging system to include any arbitrary (M×N) array of imaging modules enabling a large FOV along with ROI imaging and adjustable high spatial resolution.

We have developed a Monte-Carlo photon-tracking and readout simulator called SCOUT to study the stochastic behavior of signals output from a simplified rectangular scintillation-camera design. SCOUT models the salient processes affecting signal generation, transport, and readout. Presently, we compare output signal statistics from SCOUT to experimental results for both a discrete and a monolithic camera. We also benchmark the speed of this simulation tool and compare it to existing simulation tools. We find this modeling tool to be relatively fast and predictive of experimental results. Depending on the modeled camera geometry, we found SCOUT to be 4 to 140 times faster than other modeling tools.

Modern Field Programmable Gate Arrays (FPGAs) are capable of performing complex discrete signal processing algorithms with clock rates above 100MHz. This combined with FPGA's low expense, ease of use, and selected dedicated hardware make them an ideal technology for a data acquisition system for a positron emission tomography (PET) scanner. The University of Washington is producing a high-resolution, small-animal PET scanner that utilizes FPGAs as the core of the front-end electronics. For this next generation scanner, 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 on an all-digital pulse pileup correction algorithm that is being developed for the FPGA. The pileup mitigation algorithm will allow the scanner to run at higher count rates without incurring large data losses due to the overlapping of scintillation signals. This correction technique utilizes a reference pulse to extract timing and energy information for most pileup events. Using pulses were acquired from a Zecotech Photonics MAPDN with an LFS-3 scintillator, we show that good timing and energy information can be achieved in the presence of pileup.