The use of nano-computed tomography to enhance musculoskeletal research

Abstract

Advances in computed tomography (CT) imaging are opening new avenues toward more precise characterization and quantification of connective tissue microarchitecture. In the last two decades, micro-computed tomography (microCT) has significantly augmented destructive methods for the 3D micro-analysis of tissue structure, primarily in the bone research field. Recently, microCT has been employed in combination with contrast agents to generate contrast-enhanced images of soft tissues that are otherwise difficult to visualize due to their native radiodensity. More recent advances in CT technology have enabled ultra-high resolution imaging by utilizing a more powerful nano-focused X-ray source, such as that found in nano-computed tomography (nanoCT) systems. NanoCT imaging has facilitated the expansion of musculoskeletal research by reducing acquisition time and significantly expanding the range of samples that can be imaged in terms of size, age and tissue-type (bone, muscle, tendon, cartilage, vessels and adipose tissue). We present the application and early results of nanoCT imaging in various tissue types and how this ultra-high resolution imaging modality is capable of characterizing microstructures at levels of details previously not possible. Contrast-enhanced imaging techniques to enable soft-tissue visualization and characterization are also outlined.

• Bone
• cellular imaging
• connective tissue imaging
• contrast enhanced-CT
• microCT
• nano-computed tomography
• vascular imaging

Acknowledgments

The authors would like to acknowledge Phillip Nasser (Icahn School of Medicine at Mount Sinai, New York, NY, USA) for his efforts in generating the FEA meshed image of the patellar tendon, and Laura MacLatchy (Department of Anthropology at the University of Michigan, Ann Arbor, MI, USA) for providing the fossilized specimen for imaging.

Declaration of interest

The authors report no conflicts of interest.

Research reported in this publication was supported by the National Institutes of Health under award numbers S10RR026336, AR44927, AR065424, R24 DK092759 and K99 DE024178. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.