Shaun S. Gleason

A new X-ray computed tomography system for laboratory mouse imaging

Two versions of a new high-resolution X-ray computed tomography system are being developed to screen mutagenized mice in the Oak Ridge National Laboratory Mammalian Genetics Research Facility. The first prototype employs a single-pixel CdZnTe detector with a pinhole collimator operating in pulse counting mode. The second version employs a phosphor screen/CCD detector operating in current mode. The major system hardware includes a low-energy X-ray tube, two linear translation stages and a rotational stage. For the single-pixel detector, image resolution is determined by the step size of the detector stage; preliminary images have been acquired at 100 /spl mu/m and 250 /spl mu/m resolutions. The resolution of the phosphor screen detector is determined by the modulation transfer function of the phosphor screen; images with resolutions approaching 50 /spl mu/m have been acquired. The system performance with the two detectors is described and recent images are presented.

Reconstruction of multi-energy X-ray computed tomography images of laboratory mice

A new X-ray computed tomography (CT) system is being developed at Oak Ridge National Laboratory to image laboratory mice for the purpose of rapid phenotype screening and identification. One implementation of this CT system allows simultaneous capture of several sets of sinogram data, each having a unique X-ray energy distribution. The goals of this paper are to (1) identify issues associated with the reconstruction of this energy-dependent data and (2) suggest preliminary approaches to address these issues. Due to varying numbers of photon counts within each set, both traditional (filtered backprojection, or FBP) and statistical (maximum likelihood, or ML) tomographic image reconstruction techniques have been applied to the energy-dependent sinogram data. Results of reconstructed images using both algorithms on sinogram data (high- and low-count) are presented. Also, tissue contrast within the energy-dependent images is compared to known X-ray attenuation coefficients of soft tissue (e.g. muscle, bone, and fat).

Unsupervised Semantic Labeling Framework for Identification of Complex Facilities in High-Resolution Remote Sensing Images

Nuclear proliferation is a major national security concern for many countries. Existing feature extraction and classification approaches are not suitable for monitoring proliferation activity using high-resolution multi-temporal remote sensing imagery. In this paper we present an unsupervised semantic labeling framework based on the Latent Dirichlet Allocation method. This framework is used to analyze over 70 images collected under different spatial and temporal settings over the globe representing two major semantic categories: nuclear and coal power plants. Initial experimental results show a reasonable discrimination of these two categories even though they share highly overlapping and common objects. This research also identified several research challenges associated with nuclear proliferation monitoring using high resolution remote sensing images.

A restraint-free small animal SPECT imaging system with motion tracking

We report on an approach toward the development of a high-resolution single photon emission computed tomography (SPECT) system to image the biodistribution of radiolabeled tracers such as Tc-99m and I-125 in unrestrained/unanesthetized mice. An infrared (IR)-based position tracking apparatus has been developed and integrated into a SPECT gantry. The tracking system is designed to measure the spatial position of a mouses head at a rate of 10-15 frames per second with submillimeter accuracy. The high-resolution, gamma imaging detectors are based on pixellated NaI(Tl) crystal scintillator arrays, position-sensitive photomultiplier tubes, and novel readout circuitry requiring fewer analog-digital converter (ADC) channels while retaining high spatial resolution. Two SPECT gamma camera detector heads based upon position-sensitive photomultiplier tubes have been built and installed onto the gantry. The IR landmark-based pose measurement and tracking system is under development to provide animal position data during a SPECT scan. The animal position and orientation data acquired by the tracking system will be used for motion correction during the tomographic image reconstruction.

Quantitative high-resolution microradiographic imaging of amyloid deposits in a novel murine model of AA amyloidosis

The mouse model of experimentally induced systemic AA amyloidosis is long established, well validated, and closely analogous to the human form of this disease. However, the induction of amyloid by experimental inflammation is unpredictable, inconsistent, and difficult to modulate. We have previously shown that murine AA amyloid deposits can be imaged using iodine-123 labeled SAP scintigraphy and report here substantial refinements in both the imaging technology and the mouse model itself. In this regard, we have generated a novel prototype of AA amyloid in which mice expressing the human interleukin 6 gene, when given amyloid enhancing factor, develop extensive and progressive systemic AA deposition without an inflammatory stimulus, i.e., a transgenic rapidly inducible amyloid disease (TRIAD) mouse. Additionally, we have constructed high-resolution micro single photon emission computed tomography (SPECT)/computed tomography (CT) instrumentation that provides images revealing the precise anatomic location of amyloid deposits labeled by radioiodinated serum amyloid P component (SAP). Based on reconstructed microSPECT/CT images, as well as autoradiographic, isotope biodistribution, and quantitative histochemical analyses, the 125I-labeled SAP tracer bound specifically to hepatic and splenic amyloid in the TRIAD animals. The ability to discern radiographically the extent of amyloid burden in the TRIAD model provides a unique opportunity to evaluate the therapeutic efficacy of pharmacologic compounds designed to inhibit fibril formation or effect amyloid resolution.

Micro-Imaging of Amyloid in Mice

Scintigraphic imaging of radioiodinated serum amyloid P-component is a proven method for the clinical detection of peripheral amyloid deposits (Hawkins et al., 1990). However, the inability to perform comparably high-resolution studies in experimental animal models of amyloid disease has impacted not only basic studies into the pathogenesis of amyloidosis but also in the preclinical in vivo evaluation of potential anti-amyloid therapeutic agents. We have developed microimaging technologies, implemented novel computational methods, and established protocols to generate high-resolution images of amyloid deposits in mice. (125)I-labeled serum amyloid P component (SAP) and an amyloid-fibril reactive murine monoclonal antibody (designated 11-1F4) have been used successfully to acquire high-resolution single photon emission computed tomographic (SPECT) images that, when fused with x-ray computed tomographic (CT) data, have provided precise anatomical localization of secondary (AA) and primary (AL) amyloid deposits in mouse models of these diseases. This chapter will provide detailed protocols for the radioiodination and purification of amyloidophilic proteins and the generation of mouse models of AA and AL amyloidosis. A brief description of the available hardware and the parameters used to acquire high-resolution microSPECT and CT images is presented, and the tools used to perform image reconstruction and visualization that permit the analysis and presentation of image data are discussed. Finally, we provide established methods for measuring organ- and tissue-specific activities with which to corroborate the microSPECT and CT images.

Fast Feldkamp reconstruction based on focus of attention and distributed computing

The Feldkamp algorithm is widely accepted as a practical conebeam reconstruction method for three‐dimensional x‐ray computed tomography. We introduce focus of attention, an effective and simple to implement datadriven preprocessing scheme, for identifying a convex subset of voxels that include all those relevant to the object under study. By concentrating on this subset of voxels during reconstruction, we reduce the computational demands of the Feldkamp algorithm correspondingly. To achieve further speed‐up, all computations are distributed across a cluster of inexpensive, dual‐processor PCs. We present experimental work based on mouse data obtained from the MicroCAT which is a high‐resolution x‐ray computed tomography system for small animal imaging. This work shows that focus of attention can cut the overall computation time in half without affecting the image quality. The method is general by nature and can easily be adapted to apply to other geometries and modalities as well as to iterative reconstruction algorithms.

Automatic classification of spatial signatures on semiconductor wafermaps

This paper describes spatial signature analysis (SSA), a cooperative research project between SEMATECH and Oak Ridge National Laboratory for automatically analyzing and reducing semiconductor wafermap defect data to useful information. Trends towards larger wafer formats and smaller critical dimensions have caused an exponential increase in the volume of visual and parametric defect data which must be analyzed and stored, therefore necessitating the development of automated tools for wafer defect analysis. Contamination particles that did not create problems with 1 micron design rules can now be categorized as killer defects. SSA is an automated wafermap analysis procedure which performs a sophisticated defect clustering and signature classification of electronic wafermaps. This procedure has been realized in a software system that contains a signature classifier that is user-trainable. Known examples of historically problematic process signatures are added to a training database for the classifier. Once a suitable training set has been established, the software can automatically segment and classify multiple signatures from a standard electronic wafermap file into user-defined categories. It is anticipated that successful integration of this technology with other wafer monitoring strategies will result in reduced time-to-discovery and ultimately improved product yield.

Design and Performance of a New SPECT Detector for Multimodality Small Animal Imaging Platforms

A new detector for single photon emission computed tomography (SPECT) has been developed for the Siemens microCATreg II and Inveon Multimodality preclinical imaging systems. The detector provides an active imaging area of 15 cm times 15 cm. We review the design of this new SPECT detector and present some key performance characteristics. Integral and differential uniformity were 3.7% and 3.0%, respectively. Mean energy resolution for 99mTc (140 keV) was 12.5%. Sensitivity as high as 1400 cps/MBq was measured for 99mTc on a dual-detector system, and a spatial resolution of 0.7 mm (FWHM) was obtained using 0.5 mm single pinhole collimators. Additionally, we present data from representative preclinical SPECT studies acquired with single and multi-pinhole collimators and multiple isotopes. Reconstructed images demonstrate that this detector is capable of high-resolution SPECT for multimodality small animal imaging.

Real-time landmark-based unrestrained animal tracking system for motion-corrected PET/SPECT imaging

Oak Ridge National Laboratory (ORNL) and Jefferson Lab and are collaborating to develop a new high-resolution single photon emission tomography (SPECT) instrument to image unrestrained laboratory animals. This technology development will allow functional imaging studies to be performed on the animals without the use of anesthetic agents. This technology development could have eventual clinical applications for performing functional imaging studies on patients that cannot remain still (Parkinsons patients, Alzheimers patients, small children, etc.) during a PET or SPECT scan. A key component of this new device is the position tracking apparatus. The tracking apparatus is an integral part of the gantry and designed to measure the spatial position of the animal at a rate of 10-15 frames per second with sub-millimeter accuracy. Initial work focuses on brain studies where anesthetic agents or physical restraint can significantly impact physiologic processes.