Contrast-Enhanced MicroCT for Virtual 3D Anatomical Pathology of Biological Tissues: A Literature Review

To date, the combination of histological sectioning, staining, and microscopic assessment of the 2D sections is still the golden standard for structural and compositional analysis of biological tissues. X-ray microfocus computed tomography (microCT) is an emerging 3D imaging technique with high potential for 3D structural analysis of biological tissues with a complex and heterogeneous 3D structure, such as the trabecular bone. However, its use has been mostly limited to mineralized tissues because of the inherently low X-ray absorption of soft tissues. To achieve sufficient X-ray attenuation, chemical compounds containing high atomic number elements that bind to soft tissues have been recently adopted as contrast agents (CAs) for contrast-enhanced microCT (CE-CT); this novel technique is very promising for quantitative “virtual” 3D anatomical pathology of both mineralized and soft biological tissues. In this paper, we provided a review of the advances in CE-CT since the very first reports on the technology to date. Perfusion CAs for in vivo imaging have not been discussed, as the focus of this review was on CAs that bind to the tissue of interest and that are, thus, used for ex vivo imaging of biological tissues. As CE-CT has mostly been applied for the characterization of musculoskeletal tissues, we have put specific emphasis on these tissues. Advantages and limitations of multiple CAs for different musculoskeletal tissues have been highlighted, and their reproducibility has been discussed. Additionally, the advantages of the “full” 3D CE-CT information have been pinpointed, and its importance for more detailed structural, spatial, and functional characterization of the tissues of interest has been shown. Finally, the remaining challenges that are still hampering a broader adoption of CE-CT have been highlighted, and suggestions have been made to move the field of CE-CT imaging one step further towards a standard accepted tool for quantitative virtual 3D anatomical pathology.

Publication year:2019

BOF-keylabel:yes

IOF-keylabel:yes

BOF-publication weight:1

CSS-citation score:3

Authors from:Higher Education

Accessibility:Open