Skip to main content
Log in

Sublingual microcirculation: comparison between the 415 nm blue light and 520 nm green light of sidestream dark field videomicroscopes

  • Original Research
  • Published:
Journal of Clinical Monitoring and Computing Aims and scope Submit manuscript

Abstract

Green light with a wavelength of 520 nm is commonly used in sidestream dark field (SDF) video microscopes for sublingual microcirculation assessment in clinical practice. However, blue light could obtain a clearer microcirculatory image due to a higher light absorption coefficient of hemoglobin. The aim of this study was to compare the sublingual microcirculatory image quality acquisition and related microcirculatory parameters between 520 nm green light and 415 nm blue light probes in the SDF device named MicroSee V100. Sublingual microcirculation films from twenty-one healthy volunteers were prospectively collected by blue light and green light probes, and only one video of each wavelength was recorded and analyzed in each volunteer. Moreover, 200 sublingual microcirculation films (100 by blue light probe and 100 by green light probe) of ICU patients were retrospectively scored for microcirculation image quality. Compared to green light, an increase in the perfused vessel density (paired t test, increased by 4.6 ± 4.7 mm/mm2, P < 0.0001) and total vessel density (paired t test, increased by 5.1 ± 4.6 mm/mm2, P < 0.0001) was observed by blue light in the healthy volunteers. The blue light probe had a significantly lower rate of unacceptable films than the green light probe in the 200 films of ICU patients (10/100 vs. 39/100, P < 0.0001). Blue light provides a higher microcirculatory vessel density and image quality than the existing SDF probe using green light.

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

Similar content being viewed by others

References

  1. De Backer D, Hollenberg S, Boerma C, et al. How to evaluate the microcirculation: report of a round table conference. Critical care 2007;11(5):R101. doi: https://doi.org/10.1186/cc6118 [published Online First: 2007/09/12].

  2. He H, Liu D, Ince C. Colloids and the Microcirculation. Anesth Analg. 2018;126(5):1747–54. doi:https://doi.org/10.1213/ANE.0000000000002620.

    Article  CAS  Google Scholar 

  3. He H, Gruartmoner G, Ince Y, et al. Effect of pneumoperitoneum and steep reverse-Trendelenburg position on mean systemic filling pressure, venous return, and microcirculation during esophagectomy. J Thorac disease. 2018;10(6):3399–408. doi:https://doi.org/10.21037/jtd.2018.05.169.

    Article  Google Scholar 

  4. Ince C. Hemodynamic coherence and the rationale for monitoring the microcirculation. Crit Care. 2015;19(Suppl 3):8. doi:https://doi.org/10.1186/cc14726 [published Online First: 2016/01/06]. Suppl 3 ) .

    Article  Google Scholar 

  5. He HW, Long Y, Liu DW, et al. Resuscitation incoherence and dynamic circulation-perfusion coupling in circulatory shock. Chin Med J. 2019;132(10):1218–27. doi:https://doi.org/10.1097/CM9.0000000000000221 [published Online First: 2019/03/22].

    Article  CAS  Google Scholar 

  6. Groner W, Winkelman JW, Harris AG, et al. Orthogonal polarization spectral imaging: a new method for study of the microcirculation. Nat Med. 1999;5(10):1209–12. doi:https://doi.org/10.1038/13529 [published Online First: 1999/09/30].

    Article  CAS  Google Scholar 

  7. Gilbert-Kawai E, Coppel J, Bountziouka V, et al. A comparison of the quality of image acquisition between the incident dark field and sidestream dark field video-microscopes. BMC Med Imaging. 2016;16:10. doi:https://doi.org/10.1186/s12880-015-0078-8 [published Online First: 2016/01/23].

    Article  Google Scholar 

  8. Aykut G, Veenstra G, Scorcella C, et al. Cytocam-IDF (incident dark field illumination) imaging for bedside monitoring of the microcirculation. Intensive care medicine experimental. 2015;3(1):40. doi:https://doi.org/10.1186/s40635-015-0040-7 [published Online First: 2015/07/29].

    Article  Google Scholar 

  9. van Elteren HA, Ince C, Tibboel D, et al. Cutaneous microcirculation in preterm neonates: comparison between sidestream dark field (SDF) and incident dark field (IDF) imaging. J Clin Monit Comput. 2015;29(5):543–8. doi:https://doi.org/10.1007/s10877-015-9708-5 [published Online First: 2015/05/30].

    Article  Google Scholar 

  10. Ince C, Boerma EC, Cecconi M, et al. Second consensus on the assessment of sublingual microcirculation in critically ill patients: results from a task force of the European Society of Intensive Care Medicine. Intensive Care Med. 2018;44(3):281–99. doi:https://doi.org/10.1007/s00134-018-5070-7 [published Online First: 2018/02/08].

    Article  Google Scholar 

  11. Goedhart PT, Khalilzada M, Bezemer R, et al. Sidestream Dark Field (SDF) imaging: a novel stroboscopic LED ring-based imaging modality for clinical assessment of the microcirculation. Opt Express. 2007;15(23):15101–14. doi:https://doi.org/10.1364/oe.15.015101 [published Online First: 2007/11/12].

    Article  CAS  Google Scholar 

  12. Li Z, Kaneko S, Oda ea S. Microcirculation imaging with multicolor LEDs and mini CCD camera. World Congress on Medical Physics and Biomedical Engineering, IFMBE Proceedings 2013:1006-09. doi: https://doi.org/10.1007/978-3-642-29305-4_264.

  13. Bosschaart N, Edelman GJ, Aalders MC, et al. A literature review and novel theoretical approach on the optical properties of whole blood. Lasers Med Sci. 2014;29(2):453–79. doi:https://doi.org/10.1007/s10103-013-1446-7 [published Online First: 2013/10/15].

    Article  Google Scholar 

  14. Hashimoto R, Kurata T, Sekine M, et al. Two-wavelength oximetry of tissue microcirculation based on sidestream dark-field imaging. J Biomed Opt. 2018;24(3):1–8. doi:https://doi.org/10.1117/1.Jbo.24.3.031013 [published Online First: 2018/11/01].

    Article  Google Scholar 

  15. Jiang S, Li P, Shen Y, et al. An adaptive fractal model for sublingual microcirculation. Microvasc Res. 2021;134:104101. https://doi.org/10.1016/j.mvr.2020.104101 [published Online First: 2020/11/10].

    Article  Google Scholar 

  16. Guay CS, Khebir M, Shiva Shahiri T, et al. Evaluation of automated microvascular flow analysis software AVA 4: a validation study. Intensive care medicine experimental. 2021;9(1):15. doi:https://doi.org/10.1186/s40635-021-00380-0 [published Online First: 2021/04/03].

    Article  Google Scholar 

  17. Massey MJ, Larochelle E, Najarro G, et al. The microcirculation image quality score: development and preliminary evaluation of a proposed approach to grading quality of image acquisition for bedside videomicroscopy. J Crit Care. 2013;28(6):913–7. doi:https://doi.org/10.1016/j.jcrc.2013.06.015 [published Online First: 2013/08/27].

    Article  Google Scholar 

  18. Coppel J, Bountziouka V, Martin D, et al. A comparison of the quality of image acquisition between two different sidestream dark field video-microscopes. J Clin Monit Comput. 2021;35(3):577–83. doi:https://doi.org/10.1007/s10877-020-00514-x [published Online First: 2020/05/07].

    Article  Google Scholar 

  19. Hilty MP, Akin S, Boerma C, et al. Automated Algorithm Analysis of Sublingual Microcirculation in an International Multicentral Database Identifies Alterations Associated With Disease and Mechanism of Resuscitation. Crit Care Med. 2020;48(10):e864-e75. doi:https://doi.org/10.1097/ccm.0000000000004491 [published Online First: 2020/09/16].

    Article  Google Scholar 

  20. Hilty MP, Guerci P, Ince Y, et al. MicroTools enables automated quantification of capillary density and red blood cell velocity in handheld vital microscopy. Commun biology. 2019;2:217. doi:https://doi.org/10.1038/s42003-019-0473-8 [published Online First: 2019/06/27].

    Article  Google Scholar 

  21. Gu YM, Wang S, Zhang L, et al. Characteristics and determinants of the sublingual microcirculation in populations of different ethnicity. Hypertension (Dallas, Tex: 1979) 2015;65(5):993–1001. doi: https://doi.org/10.1161/hypertensionaha.114.05119 [published Online First: 2015/02/26].

Download references

Acknowledgements

This work was supported by Peking Union Medical College Hospital of Medical Novel Medical Technology Project (No. XJS20190210), Excellence Program of Key Clinical Specialty of Critical Care Medicine in Beijing.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Huaiwu He.

Ethics declarations

Declarations

Dr. Ince is the CSO of Active Medical BV, Leiden The Netherlands, a company that provides education, services, hardware and software related to clinical microcirculation. There are no financial disclosures for other authors.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Liu, B., He, H., Feng, X. et al. Sublingual microcirculation: comparison between the 415 nm blue light and 520 nm green light of sidestream dark field videomicroscopes. J Clin Monit Comput 37, 297–302 (2023). https://doi.org/10.1007/s10877-022-00891-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10877-022-00891-5

Keywords

Navigation