Characterization of "γ-Eye": a Low-Cost Benchtop Mouse-Sized Gamma Camera for Dynamic and Static Imaging Studies

Mixture prior distributions and Bayesian models for robust radionuclide image processing

The diagnosis of medical conditions and subsequent treatment often involves radionuclide imaging techniques. To refine localisation accuracy and improve diagnostic confidence, compared with the use of a single scanning technique, a combination of two (or more) techniques can be used but with a higher risk of misalignment. For this to be reliable and accurate, recorded data undergo processing to suppress noise and enhance resolution. A step in image processing techniques for such inverse problems is the inclusion of smoothing. Standard approaches, however, are usually limited to applying identical models globally. In this study, we propose a novel Laplace and Gaussian mixture prior distribution that incorporates different smoothing strategies with the automatic model-based estimation of mixture component weightings creating a locally adaptive model. A fully Bayesian approach is presented using multi-level hierarchical modelling and Markov chain Monte Carlo (MCMC) estimation methods to sample from the posterior distribution and hence perform estimation. The proposed methods are assessed using simulated γ -eye TM camera images and demonstrate greater noise reduction than existing methods but without compromising resolution. As well as image estimates, the MCMC methods also provide posterior variance estimates and hence uncertainty quantification takes into consideration any potential sources of variability. The use of mixture prior models, part Laplace random field and part Gaussian random field, within a Bayesian modelling approach is not limited to medical imaging applications but provides a more general framework for analysing other spatial inverse problems. Locally adaptive prior distributions provide a more realistic model, which leads to robust results and hence more reliable decision-making, especially in nuclear medicine. They can become a standard part of the toolkit of everyone working in image processing applications.

Optical to Planar X-ray Mouse Image Mapping in Preclinical Nuclear Medicine Using Conditional Adversarial Networks

In the current work, a pix2pix conditional generative adversarial network has been evaluated as a potential solution for generating adequately accurate synthesized morphological X-ray images by translating standard photographic images of mice. Such an approach will benefit 2D functional molecular imaging techniques, such as planar radioisotope and/or fluorescence/bioluminescence imaging, by providing high-resolution information for anatomical mapping, but not for diagnosis, using conventional photographic sensors. Planar functional imaging offers an efficient alternative to biodistribution ex vivo studies and/or 3D high-end molecular imaging systems since it can be effectively used to track new tracers and study the accumulation from zero point in time post-injection. The superimposition of functional information with an artificially produced X-ray image may enhance overall image information in such systems without added complexity and cost. The network has been trained in 700 input (photography)/ground truth (X-ray) paired mouse images and evaluated using a test dataset composed of 80 photographic images and 80 ground truth X-ray images. Performance metrics such as peak signal-to-noise ratio (PSNR), structural similarity index measure (SSIM) and Fréchet inception distance (FID) were used to quantitatively evaluate the proposed approach in the acquired dataset.

Advanced Monte Carlo simulations of emission tomography imaging systems with GATE

Built on top of the Geant4 toolkit, GATE is collaboratively developed for more than 15 years to design Monte Carlo simulations of nuclear-based imaging systems. It is, in particular, used by researchers and industrials to design, optimize, understand and create innovative emission tomography systems. In this paper, we reviewed the recent developments that have been proposed to simulate modern detectors and provide a comprehensive report on imaging systems that have been simulated and evaluated in GATE. Additionally, some methodological developments that are not specific for imaging but that can improve detector modeling and provide computation time gains, such as Variance Reduction Techniques and Artificial Intelligence integration, are described and discussed.

Optimization of In Vivo Studies by Combining Planar Dynamic and Tomographic Imaging: Workflow Evaluation on a Superparamagnetic Nanoparticles System

Molecular imaging holds great promise in the noninvasive monitoring of several diseases with nanoparticles (NPs) being considered an efficient imaging tool for cancer, central nervous system, and heart- or bone-related diseases and for disorders of the mononuclear phagocytic system (MPS). In the present study, we used an iron-based nanoformulation, already established as an MRI/SPECT probe, as well as to load different biomolecules, to investigate its potential for nuclear planar and tomographic imaging of several target tissues following its distribution via different administration routes. Iron-doped hydroxyapatite NPs (FeHA) were radiolabeled with the single photon γ-emitting imaging agent [99mTc]TcMDP. Administration of the radioactive NPs was performed via the following four delivery methods: (1) standard intravenous (iv) tail vein, (2) iv retro-orbital injection, (3) intratracheal (it) instillation, and (4) intrarectal installation (pr). Real-time, live, fast dynamic screening studies were performed on a dedicated bench top, mouse-sized, planar SPECT system from t = 0 to 1 hour postinjection (p.i.), and consequently, tomographic SPECT/CT imaging was performed, for up to 24 hours p.i. The administration routes that have been studied provide a wide range of possible target tissues, for various diseases. Studies can be optimized following this workflow, as it is possible to quickly assess more parameters in a small number of animals (injection route, dosage, and fasting conditions). Thus, such an imaging protocol combines the strengths of both dynamic planar and tomographic imaging, and by using iron-based NPs of high biocompatibility along with the appropriate administration route, a potential diagnostic or therapeutic effect could be attained.

Monte Carlo Optical Simulations of a Small FoV Gamma Camera. Effect of Scintillator Thicknesses and Septa Materials

Optical Monte Carlo simulations have been extensively used for the accurate modeling of light transport in scintillators for the improvement of detector designs. In the present work, a GATE Monte Carlo toolkit was used to study the effect of scintillator thicknesses and septa materials in the performance parameters evaluation of a commercially available small animal gamma-optical camera, named “γ-eye”. Firstly, the simulated γ-eye system was validated against experimental data. Then, part of the validated camera was modeled defining all of the optical properties by means of the UNIFIED model of GATE. Different CsI:Na scintillator crystals with varying thicknesses (from 4 mm up to 6 mm) and different reflector (septa) materials were simulated and compared in terms of sensitivity, light output and spatial resolution. Results have demonstrated the reliability of the model and indicate that the thicker crystal array presents higher sensitivity values, but degraded spatial resolution properties. Moreover, the use of black tape around crystals leads to an improvement in spatial resolution values compared to a standard white reflector material.

Iron Oxide Colloidal Nanoclusters as Theranostic Vehicles and Their Interactions at the Cellular Level

Advances in surfactant-assisted chemical approaches have led the way for the exploitation of nanoscale inorganic particles in medical diagnosis and treatment. In this field, magnetically-driven multimodal nanotools that perform both detection and therapy, well-designed in size, shape and composition, are highly advantageous. Such a theranostic material—which entails the controlled assembly of smaller (maghemite) nanocrystals in a secondary motif that is highly dispersible in aqueous media—is discussed here. These surface functionalized, pomegranate-like ferrimagnetic nanoclusters (40⁻85 nm) are made of nanocrystal subunits that show a remarkable magnetic resonance imaging contrast efficiency, which is better than that of the superparamagnetic contrast agent Endorem©. Going beyond this attribute and with their demonstrated low cytotoxicity in hand, we examine the critical interaction of such nanoprobes with cells at different physiological environments. The time-dependent in vivo scintigraphic imaging of mice experimental models, combined with a biodistribution study, revealed the accumulation of nanoclusters in the spleen and liver. Moreover, the in vitro proliferation of spleen cells and cytokine production witnessed a size-selective regulation of immune system cells, inferring that smaller clusters induce mainly inflammatory activities, while larger ones induce anti-inflammatory actions. The preliminary findings corroborate that the modular chemistry of magnetic iron oxide nanoclusters stimulates unexplored pathways that could be driven to alter their function in favor of healthcare.

Rigid motion correction of dual opposed planar projections in single photon imaging

Awake and/or freely moving small animal single photon emission imaging allows the continuous study of molecules exhibiting slow kinetics without the need to restrain or anaesthetise the animals. Estimating motion free projections in freely moving small animal planar imaging can be considered as a limited angle tomography problem, except that we wish to estimate the 2D planar projections rather than the 3D volume, where the angular sampling in all three axes depends on the rotational motion of the animal. In this study, we hypothesise that the motion corrected planar projections estimated by reconstructing an estimate of the 3D volume using an iterative motion compensating reconstruction algorithm and integrating it along the projection path, will closely match the true, motion-less, planar distribution regardless of the object motion. We tested this hypothesis for the case of rigid motion using Monte-Carlo simulations and experimental phantom data based on a dual opposed detector system, where object motion was modelled with 6 degrees of freedom. In addition, we investigated the quantitative accuracy of the regional activity extracted from the geometric mean of opposing motion corrected planar projections. Results showed that it is feasible to estimate qualitatively accurate motion-corrected projections for a wide range of motions around all 3 axes. Errors in the geometric mean estimates of regional activity were relatively small and within 10% of expected true values. In addition, quantitative regional errors were dependent on the observed motion, as well as on the surrounding activity of overlapping organs. We conclude that both qualitatively and quantitatively accurate motion-free projections of the tracer distribution in a rigidly moving object can be estimated from dual opposed detectors using a correction approach within an iterative reconstruction framework and we expect this approach can be extended to the case of non-rigid motion.