Performance evaluation of PETbox: a low cost bench top preclinical PET scanner.

PURPOSE: PETbox is a low cost bench top preclinical PET scanner dedicated to pharmacokinetic and pharmacodynamic mouse studies. A prototype system was developed at our institute, and this manuscript characterizes the performance of the prototype system. PROCEDURES: The PETbox detector consists of a 20 × 44 bismuth germanate crystal array with a thickness of 5 mm and cross-section size of 2.05 × 2.05 mm. Two such detectors are placed facing each other at a spacing of 5 cm, forming a dual-head geometry optimized for imaging mice. The detectors are kept stationary during the scan, making PETbox a limited angle tomography system. 3D images are reconstructed using a maximum likelihood and expectation maximization (ML-EM) method. The performance of the prototype system was characterized based on a modified set of the NEMA NU 4-2008 standards. RESULTS: In-plane image spatial resolution was measured to be an average of 1.53 mm full width at half maximum for coronal images and 2.65 mm for the anterior-posterior direction. The volumetric reconstructed resolution was below 8 mm(3) at most locations in the field of view (FOV). The sensitivity, scatter fraction, and noise equivalent count rate (NECR) were measured for different energy windows. With an energy window of 150 - 650 keV and a timing window of 20 ns optimized for mouse imaging, the peak absolute sensitivity was 3.99% at the center of FOV and a peak NECR of 20 kcps was achieved for a total activity of 3.2 MBq (86.8 µCi). Phantom and in vivo imaging studies were performed and demonstrated the utility of the system at low activity levels. The quantitation capabilities of the system were also characterized showing that despite the limited angle tomography, reasonably good quantification accuracy was achieved over a large dynamic range of activity levels. CONCLUSIONS: The presented results demonstrate the potential of this new tomograph for small animal imaging.

Spectrally resolved bioluminescence tomography with the third-order simplified spherical harmonics approximation.

Bioluminescence imaging has been extensively applied to in vivo small animal imaging. Quantitative three-dimensional bioluminescent source information obtained by using bioluminescence tomography can directly and much more accurately reflect biological changes as opposed to planar bioluminescence imaging. Preliminary simulated and experimental reconstruction results demonstrate the feasibility and promise of bioluminescence tomography. However, the use of multiple approximations, particularly the diffusion approximation theory, affects the quality of in vivo small animal-based image reconstructions. In the development of new reconstruction algorithms, high-order approximation models of the radiative transfer equation and spectrally resolved data introduce new challenges to the reconstruction algorithm and speed. In this paper, an SP(3)-based (the third-order simplified spherical harmonics approximation) spectrally resolved reconstruction algorithm is proposed. The simple linear relationship between the unknown source distribution and the spectrally resolved data is established in this algorithm. A parallel version of this algorithm is realized, making BLT reconstruction feasible for the whole body of small animals especially for fine spatial domain discretization. In simulation validations, the proposed algorithm shows improved reconstruction quality compared with diffusion approximation-based methods when high absorption, superficial sources and detection modes are considered. In addition, comparisons between fine and coarse mesh-based BLT reconstructions show the effects of numerical errors in reconstruction image quality. Finally, BLT reconstructions using in vivo mouse experiments further demonstrate the potential and effectiveness of the SP(3)-based reconstruction algorithm.

Experimental bioluminescence tomography with fully parallel radiative-transfer-based reconstruction framework.

Bioluminescence imaging is a very sensitive imaging modality, used in preclinical molecular imaging. However, in its planar projection form, it is non-quantitative and has poor spatial resolution. In contrast, bioluminescence tomography (BLT) promises to provide three dimensional quantitative source information. Currently, nearly all BLT reconstruction algorithms in use employ the diffusion approximation theory to determine light propagation in tissues. In this process, several approximations and assumptions that are made severely affect the reconstruction quality of BLT. It is therefore necessary to develop novel reconstruction methods using high-order approximation models to the radiative transfer equation (RTE) as well as more complex geometries for the whole-body of small animals. However, these methodologies introduce significant challenges not only in terms of reconstruction speed but also for the overall reconstruction strategy. In this paper, a novel fully-parallel reconstruction framework is proposed which uses a simplified spherical harmonics approximation (SPN). Using this framework, a simple linear relationship between the unknown source distribution and the surface measured photon density can be established. The distributed storage and parallel operations of the finite element-based matrix make SPN-based spectrally resolved reconstruction feasible at the small animal whole body level. Performance optimization of the major steps of the framework remarkably improves reconstruction speed. Experimental reconstructions with mouse-shaped phantoms and real mice show the effectiveness and potential of this framework. This work constitutes an important advance towards developing more precise BLT reconstruction algorithms that utilize high-order approximations, particularly second-order self-adjoint forms to the RTE for in vivo small animal experiments.

Source reconstruction for spectrally-resolved bioluminescence tomography with sparse a priori information.

Through restoration of the light source information in small animals in vivo, optical molecular imaging, such as fluorescence molecular tomography (FMT) and bioluminescence tomography (BLT), can depict biological and physiological changes observed using molecular probes. A priori information plays an indispensable role in tomographic reconstruction. As a type of a priori information, the sparsity characteristic of the light source has not been sufficiently considered to date. In this paper, we introduce a compressed sensing method to develop a new tomographic algorithm for spectrally-resolved bioluminescence tomography. This method uses the nature of the source sparsity to improve the reconstruction quality with a regularization implementation. Based on verification of the inverse crime, the proposed algorithm is validated with Monte Carlo-based synthetic data and the popular Tikhonov regularization method. Testing with different noise levels and single/multiple source settings at different depths demonstrates the improved performance of this algorithm. Experimental reconstruction with a mouse-shaped phantom further shows the potential of the proposed algorithm.

A facile route to bulk high-Z polymer composites for gamma ray scintillation.

Two classes of bulk high-Z polymer composites were prepared, which exhibit scintillation properties for gamma-radiation detection.

FPGA Electronics for OPET: A Dual-Modality Optical and Positron Emission Tomograph.

The development of a prototype dual-modality optical and PET (OPET) small animal imaging tomograph is underway in the Crump Institute for Molecular Imaging at the University of California Los Angeles. OPET consists of a single ring of six detector modules with a diameter of 3.5 cm. Each detector has an 8 × 8 array of optically isolated BGO scintillators which are coupled to multichannel photomultiplier tubes and open on the front end. The system operates in either PET or optical mode and reconstructs the data sets as 3D tomograms. The detectors are capable of detecting both annihilation events (511 keV) from PET tracers as well as Single Photon Events (SPEs) (2-3 eV) from bioluminescence. Detector channels are readout using a custom multiplex readout scheme and then filtered in analog circuitry using either a γ-ray or SPE specific filter. Shaped pulses are sent to a Digital Signal Processing (DSP) unit for event processing. The DSP unit has 100 MHz Analog-to-Digital Converters on the front-end which send digitized samples to Field Programmable Gate Arrays which are programmed via user configurable algorithms to process PET coincidence events or bioluminescence SPEs. Information determined using DSP includes: event timing, energy determination-discrimination, position determination-lookup, and coincidence processing. Coincidence or SPE events are recorded to an external disk and minimal post processing is required prior to image reconstruction. Initial imaging results from a phantom filled with 18FDG solution and an optical pattern placed on the front end of a detector module in the vicinity of a SPE source are shown.