Abstract
Over the past two decades, innovations in small-animal positron emission tomography (PET) have reached an impressive level, which has brought countless opportunities to explore the major puzzles in biomedical research. It is a given that pairing information coming from different imaging modalities renders unprecedented knowledge and provides a great insight into various facets of biological systems, such as anatomy, function, physiology, and metabolism in animal models of human diseases, which are difficult to be beaten by standalone PET scanners. The development of bimodal and tri-modal imaging platforms with advanced software solutions dedicated for quantitative studies in small-animals has spurred academic and industrial interest. However, it is undisputed that the potential success of these scanners in filling the translational gap between human and animal findings, hinges to a great extent upon optimization and standardization of relevant parameters and acquisition protocols, which is often overlooked. This article reviews the trends till 2020 in the field of preclinical PET imaging with emphasize on image reconstruction and quantitative corrections implemented on state-of-the-heart hybrid systems. First, the challenges, limitations, and benefits offered by multi-modality imaging systems are described and then, the most commonly used strategies, as well as novel techniques for image reconstruction and image corrections (attenuation, scattering, normalization, motion, and partial volume effect) are presented. The advantages and disadvantages of different methods are also discussed. We also briefly touch upon the factors that should be considered for reliable kinetic modeling and absolute quantitation in preclinical small animal research. Multi-modality imaging has attracted a lot of research, particularly in the preclinical portfolio. Nevertheless, more research is still needed to optimize the conceptual design, reach the limits of quantitative imaging and implement standardized protocols for small-animal studies. Without any doubt, exploring the potential advantages of combined imaging units providing optimal image quality and reliable tools for quantification of biological parameters through standardized imaging protocols is one of the goals of translational research.
Highlights
As one of the most ubiquitous and versatile tools in investigations involving laboratory animals, preclinical positron emission tomography (PET) scanners are gaining more ground and growing tremendously in various fields of biomedical research [1]
To tackle the difficulties faced by stand-alone PET scanners, in the context of quantitative imaging capabilities, most of the recent advances focused on the development of multi-modality imaging units to provide unparalleled understanding of the various facets of biological systems, such as anatomy, function, physiology, and metabolism in animal models of human disease [2]
We briefly touch upon the factors that should be considered for reliable kinetic modeling and absolute quantification in preclinical studies
Summary
As one of the most ubiquitous and versatile tools in investigations involving laboratory animals, preclinical PET scanners are gaining more ground and growing tremendously in various fields of biomedical research [1]. This has spurred the interest towards more accurate methods like CT-based tissue-dependent spatially-variant models which render artifact-free images, improved quality and better tumor delineation when using high-energy radioisotopes such as 68Ga [87, 94] In this context, particular attention should be paid to positron range correction on simultaneous PET/MRI systems where the effect of magnetic field on the positron distribution is measurable. Direct strategies with multi-tracer kinetic models have led to promising results in separating signals of 18F-FLT and 18F-FDG from a single mouse dynamic scan [100] Another category of 4D or higher dimensional image reconstruction belongs to iterative algorithms including motion compensation to avoid further resolution degradation and artifacts generated by cardiac and respiratory motion [101, 102]. Last but not least, obtaining comparable, accurate and reproducible results that could be translated to clinical applications is unthinkable without identification, optimization and standardization of factors affecting the outcome
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