Skip to main content
Log in

Performance Evaluation of a Novel Preclinical Micro-CT System In Vitro and In Vivo

  • Original Article
  • Published:
Journal of Medical and Biological Engineering Aims and scope Submit manuscript

Abstract

Purpose

With the advent of innovation in the preclinical studies, micro-CT provides optimized resolution by high-power X-ray output tube and flat-panel detector with ultra-short scanning time. The aim of this study was to evaluate the performance of a novel preclinical micro-CT with different parameters and protocols.

Methods

Imaging quality was evaluated by micro-CT HA and wire phantom. The high power output X-ray tube provides tube voltage from 40 to 90 kV with tube current, 10 to 800 μA. The detector with 1536 × 1944 pixels was implemented by three different binning modes (1 × 1, 2 × 2 and 4 × 4). The GPU-based reconstruction was applied with Feldkamp’s algorithm. The maximum reconstruction volume was 1944 × 1944 × 4536 per scan. The phantom images were acquired by four modes with pixel sizes of 44.9, 22.5,15 and 9 μm. In the animal study, ovariectomy mice were imaged followed by analysis of bone mineral density (BMD) and BV/TV ratio (bone volume/total bone volume).

Results

Linearity (R2) measured in all imaging settings were > 0.9 and was 0.99962 at setting of 0.2 mm Cu filter, 90 kV tube voltage and 556 μA tube current. The spatial resolution as measured by full width half-maximum amplitude (FWHM) was 24 µm in the mode ultra-high resolution. The bone analysis results show the operated cohort has high significant (p < 0.05), whereas the control cohort revealed insignificant either in the BMD.

Conclusion

In summary, this novel micro-CT system demonstrated the flexible capability and high spatial resolution with ultra-short acquisition time, and a feasible quantitative BMD software.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  1. Schambach, S. J., Bag, S., Schilling, L., Groden, C., & Brockmann, M. A. (2010). Application of micro-CT in small animal imaging. Methods,50(1), 2–13.

    Article  Google Scholar 

  2. Chugh, B. P., Lerch, J. P., Yu, L. X., Pienkowski, M., Harrison, R. V., Henkelman, R. M., et al. (2009). Measurement of cerebral blood volume in mouse brain regions using micro-computed tomography. Neuroimage,47(4), 1312–1318.

    Article  Google Scholar 

  3. Arentsen, L., & Hui, S. (2013). Characterization of rotating gantry micro-CT configuration for the in vivo evaluation of murine trabecular bone. Microscopy and Microanalysis,19(4), 907–913.

    Article  Google Scholar 

  4. Brasse, D., Humbert, B., Mathelin, C., Rio, M. C., & Guyonnet, J. L. (2005). Towards an inline reconstruction architecture for micro-CT systems. Physics in Medicine & Biology,50(24), 5799–5811.

    Article  Google Scholar 

  5. Ashton, J. R., West, J. L., & Badea, C. T. (2015). In vivo small animal micro-CT using nanoparticle contrast agents. Front Pharmacol.,6, 256.

    Article  Google Scholar 

  6. Clark, D. P., & Badea, C. T. (2014). Micro-CT of rodents: State-of-the-art and future perspectives. Physics in Medicine,30(6), 619–634.

    Article  Google Scholar 

  7. Hui M, Zhao, H. J., Gao. F, & Gong, S. R. (2009). Implementation of FDK reconstruction algorithm in cone-beam CT based on the 3D Shepp-Logan model. In 2009 2nd International Conference on Biomedical Engineering and Informatics, pp. 1–5.

  8. Jara, H. (2013). Theory of quantitative magnetic resonance imaging. Singapore: World Scientific.

    Book  Google Scholar 

  9. Brown, R. W., Haacke, E. M., Cheng, Y.-C. N., Thompson, M. R., & Venkatesan, R. (2014). Magnetic resonance imaging: Physical principles and sequence design. New York: Wiley.

    Book  Google Scholar 

  10. Seeram, E. (2015). Computed tomography: Physical principles, clinical applications, and quality control. Amsterdam: Elsevier.

    Google Scholar 

  11. Handschuh, S., Beisser, C. J., Ruthensteiner, B., & Metscher, B. D. (2017). Microscopic dual-energy CT (microDECT): A flexible tool for multichannel ex vivo 3D imaging of biological specimens. Journal of Microscopy,267(1), 3–26.

    Article  Google Scholar 

  12. Yan, J., Schaefferkoette, J., Conti, M., & Townsend, D. (2016). A method to assess image quality for Low-dose PET: Analysis of SNR, CNR, bias and image noise. Cancer Imaging,16(1), 26. https://doi.org/10.1186/s40644-016-0086-0.

    Article  Google Scholar 

  13. Kohn, M. L., Gooch, A. W., Jr., & Keller, W. S. (1988). Filters for radiation reduction: A comparison. Radiology,167(1), 255–257.

    Article  Google Scholar 

  14. Trout, E. D., Kelley, J. P., & Cathey, G. A. (1952). The use of filters to control radiation exposure to the patient in diagnostic roentgenology. The American Journal of Roentgenology Radium Therapy and Nuclear Medicine,67(6), 946–963.

    Google Scholar 

  15. Koerner, M. (2006). 2D fan beam reconstruction 3D cone beam reconstruction.

Download references

Acknowledgements

This study was supported by the Molecular and Genetic Imaging Core, National Yang-Ming University, Taiwan Animal Consortium and National PET/Cyclotron Center, Department of Nuclear Medicine, Taipei Veterans General Hospital and Delbio company. We appreciated the technical information and the innovation development in hardware and software from Delbio. Also, the authors appreciate all participants who are involved in and all small animal recruitment in this study.

Author information

Authors and Affiliations

Authors

Contributions

YWL, CCK, BHY, RSL—Conceptualization. JSL—Software development support and hardware innovation. WCY, MCH—Acquisition of Phantom data. SYC, CHL, CCK—Acquisition of animal data. YWL, CHL—Data statistics. YWL—Paper writing. CCK—Paper editing. BHY (Physics), RSL (Biomedicine)—Paper review.

Corresponding authors

Correspondence to Bang-Hung Yang or Ren-Shyan Liu.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Lo, YW., Ke, CC., Lee, JS. et al. Performance Evaluation of a Novel Preclinical Micro-CT System In Vitro and In Vivo. J. Med. Biol. Eng. 40, 24–34 (2020). https://doi.org/10.1007/s40846-019-00487-6

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s40846-019-00487-6

Keywords

Navigation