Advances in micro-CT imaging of small animals

• Published in: Physica medica 2021-08, Vol.88, p.175-192
• Main Authors: Clark, D.P., Badea, C.T.
• Format: Article
• Language: English
• Subjects: Animals; Contrast agents; Contrast Media; Deep learning; Micro-CT; Nanoparticles; Phantoms, Imaging; Phase contrast; Photon counting detector; Photons; Preclinical; Spectral CT; Theranostics; Tomography Scanners, X-Ray Computed; X-Ray Microtomography
• ISSN: 1120-1797; 1724-191X; 1724-191X
• DOI: 10.1016/j.ejmp.2021.07.005

•Commercially available micro-CT scanners and recent applications are described.•Spectral micro-CT and phase contrast micro-CT promise improved contrast.•Micro-CT and nanoparticle contrast agents can serve in theranostics studies.•Deep learning will have a great impact on future micro-CT developments. Micron-scale computed tomography (micro-CT) imaging is a ubiquitous, cost-effective, and non-invasive three-dimensional imaging modality. We review recent developments and applications of micro-CT for preclinical research. Based on a comprehensive review of recent micro-CT literature, we summarize features of state-of-the-art hardware and ongoing challenges and promising research directions in the field. Representative features of commercially available micro-CT scanners and some new applications for both in vivo and ex vivo imaging are described. New advancements include spectral scanning using dual-energy micro-CT based on energy-integrating detectors or a new generation of photon-counting x-ray detectors (PCDs). Beyond two-material discrimination, PCDs enable quantitative differentiation of intrinsic tissues from one or more extrinsic contrast agents. When these extrinsic contrast agents are incorporated into a nanoparticle platform (e.g. liposomes), novel micro-CT imaging applications are possible such as combined therapy and diagnostic imaging in the field of cancer theranostics. Another major area of research in micro-CT is in x-ray phase contrast (XPC) imaging. XPC imaging opens CT to many new imaging applications because phase changes are more sensitive to density variations in soft tissues than standard absorption imaging. We further review the impact of deep learning on micro-CT. We feature several recent works which have successfully applied deep learning to micro-CT data, and we outline several challenges specific to micro-CT. All of these advancements establish micro-CT imaging at the forefront of preclinical research, able to provide anatomical, functional, and even molecular information while serving as a testbench for translational research.