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.

PurposePETbox 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.ProceduresThe 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.ResultsIn-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 mm3 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.ConclusionsThe presented results demonstrate the potential of this new tomograph for small animal imaging.

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, a 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.

PETbox is a low-cost benchtop PET scanner dedicated to high throughput preclinical imaging that is currently under development at our institute. This paper presents the design and characterization of the detectors that are used in the PETbox system. In this work, bismuth germanate scintillator was used for the detector, taking advantage of its high stopping power, high photoelectric event fraction, lack of intrinsic background radiation and low cost. The detector block was segmented into a pixelated array consisting of 20 × 44 elements, with a crystal pitch of 2.2 mm and a crystal cross section of 2 mm × 2 mm. The effective area of the array was 44 mm × 96.8 mm. The array was coupled to two Hamamatsu H8500 position sensitive photomultiplier tubes, forming a flat-panel type detector head with a sensitive area large enough to cover the whole body of a typical laboratory mouse. Two such detector heads were constructed and their performance was characterized. For one detector head, the energy resolution ranged from 16.1% to 38.5% full width at half maximum (FWHM), with a mean of 20.1%; for the other detector head, the energy resolution ranged from 15.5% to 42.7% FWHM, with a mean of 19.6%. The intrinsic spatial resolution was measured to range from 1.55 mm to 2.39 mm FWHM along the detector short axis and from 1.48 mm to 2.33 mm FWHM along the detector long axis, with an average of 1.78 mm. Coincidence timing resolution for the detector pair was measured to be 4.1 ns FWHM. These measurement results show that the detectors are suitable for our specific application.

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 wholebody 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 (SP N ). 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 SP N -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.