Synthesis and preliminary evaluation of radiolabeled bis(zinc(II)-dipicolylamine) coordination complexes as cell death imaging agents.

The aim of this study was the development of (99m)Tc labeled bis(zinc(II)-dipicolylamine) (Zn²âº-DPA) coordination complexes, and the in vivo evaluation of their usefulness as radiotracers for the detection of cell death. DPA ligand 1 was labeled with (99m)Tc via the (99m)Tc-tricarbonyl core ([(99m)Tc(CO)3-1]³âº) or via HYNIC ((99m)Tc-HYNIC-1) in good radiochemical yields. Highest in vitro stabilities were demonstrated for [(99m)Tc(CO)3-1]³âº. A mouse model of hepatic apoptosis (anti-Fas mAb) was used to demonstrate binding to apoptotic cells. (99m)Tc-HYNIC-1 showed the best targeting of apoptotic hepatic tissue with a 2.2 times higher liver uptake in anti-Fas treated mice as compared to healthy animals. A rat model of ischemia-reperfusion injury was used to further explore the ability of the (99m)Tc-labeled Zn²âº-DPA coordination complexes to target cell death. Selective accumulation could be detected for both tracers in the area at risk, correlating with histological proof of cell death. Area at risk to normal tissue uptake ratios were 3.82 for [(99m)Tc(CO)3-1]³âº and 5.45 for (99m)Tc-HYNIC-1.

DR with a DSLR: Digital Radiography with a Digital Single-Lens Reflex camera.

An inexpensive, portable digital radiography (DR) detector system for use in remote regions has been built and evaluated. The system utilizes a large-format digital single-lens reflex (DSLR) camera to capture the image from a standard fluorescent screen. The large sensor area allows relatively small demagnification factors and hence minimizes the light loss. The system has been used for initial phantom tests in urban hospitals and Himalayan clinics in Nepal, and it has been evaluated in the laboratory at the University of Arizona by additional phantom studies. Typical phantom images are presented in this paper, and a simplified discussion of the detective quantum efficiency of the detector is given.

Maximum-Likelihood Methods for Processing Signals From Gamma-Ray Detectors.

In any gamma-ray detector, each event produces electrical signals on one or more circuit elements. From these signals, we may wish to determine the presence of an interaction; whether multiple interactions occurred; the spatial coordinates in two or three dimensions of at least the primary interaction; or the total energy deposited in that interaction. We may also want to compute listmode probabilities for tomographic reconstruction. Maximum-likelihood methods provide a rigorous and in some senses optimal approach to extracting this information, and the associated Fisher information matrix provides a way of quantifying and optimizing the information conveyed by the detector. This paper will review the principles of likelihood methods as applied to gamma-ray detectors and illustrate their power with recent results from the Center for Gamma-ray Imaging.

System Integration of FastSPECT III, a Dedicated SPECT Rodent-Brain Imager Based on BazookaSPECT Detector Technology.

FastSPECT III is a stationary, single-photon emission computed tomography (SPECT) imager designed specifically for imaging and studying neurological pathologies in rodent brain, including Alzheimer's and Parkinsons's disease. Twenty independent BazookaSPECT [1] gamma-ray detectors acquire projections of a spherical field of view with pinholes selected for desired resolution and sensitivity. Each BazookaSPECT detector comprises a columnar CsI(Tl) scintillator, image-intensifier, optical lens, and fast-frame-rate CCD camera. Data stream back to processing computers via firewire interfaces, and heavy use of graphics processing units (GPUs) ensures that each frame of data is processed in real time to extract the images of individual gamma-ray events. Details of the system design, imaging aperture fabrication methods, and preliminary projection images are presented.

Progress in BazookaSPECT.

Recent progress on a high-resolution, photon-counting gamma-ray and x-ray imager called BazookaSPECT is presented. BazookaSPECT is an example of a new class of scintillation detectors based on integrating detectors such as CCD(charge-coupled device) or CMOS(complementary metal-oxide semiconductor) sensors. BazookaSPECT is unique in that it makes use of a scintillator in close proximity to a microchannel plate-based image intensifier for up-front optical amplification of scintillation light. We discuss progress made in bringing about compact BazookaSPECT modules and in real-time processing of event data using graphics processing units (GPUs). These advances are being implemented in the design of a high-resolution rodent brain imager called FastSPECT III. A key benefit of up-front optical gain is that any CCD/CMOS sensor can now be utilized for photon counting. We discuss the benefits and feasibility of using CMOS sensors as photon-counting detectors for digital radiography, with application in mammography and computed tomography (CT). We present as an appendix a formal method for comparing various photon-counting integrating detectors using objective statistical criteria.

Method of Calibrating Response Statistics for ML Estimation of 3D Interaction Position in a Thick-Detector Gamma Camera.

High-energy photon detectors are often made thick in order to improve their photon-detection efficiency. To avoid issues of parallax and increased signal variance that result from random interaction depth, we must determine the 3D interaction position in the imaging detector. With this goal in mind, we examine a method of calibrating response statistics of a thick-detector gamma camera to produce a maximum- likelihood estimate of 3D interaction position. We parameterize the mean detector response as a function of 3D position and estimate the parameters by maximizing their likelihood given prior knowledge of the pathlength distribution and a complete list of camera signals for an ensemble of gamma-ray interactions. Demonstrating this calibration method with simulated gamma-camera data, we show that the resulting calibration is accurate and can be used to produce unbiased estimates of 3D interaction position.