Sidestream dark field images of the microcirculation: intra-observer reliability and correlation between two semi-quantitative methods for determining flow

BMC Med Imaging. 2014 May 6:14:14. doi: 10.1186/1471-2342-14-14.


Background: Since analysis of Sidestream Dark Field images still requires subjective interpretation, we wanted to determine intra-observer repeatability and to estimate the correlation between different evaluation methods.

Methods: Fifty-four Sidestream Dark Field videos were analyzed twice by the same blinded observer using validated software. Vessels were detected, generating the parameter Total Vessel Density (TVD), and flow was determined by (i) classifying each vessel separately, generating the parameters Perfused Vessel Density (PVD) and Proportion of Perfused Vessels (PPV), and by (ii) the "Boerma" method, generating a Microvascular Flow Index (MFI) by quadrants.

Results: Intraclass Correlation Coefficients (ICCs) were above 0.9 for TVD and above 0.8 for PDV and PPV. MFIby quadrants had the lowest reliability (ICC = 0.52 for capillaries and ICC = 0.59 for all vessels), significantly lower than for PVD (ICC = 0.89, p < 0.001 for capillaries and ICC = 0.90, p < 0.001 for all vessels) and PPV (ICC = 0.82, p = 0.003 for capillaries and ICC = 0.83, p = 0.01 for all vessels). Correlation coefficient (r) between PPV and MFIby quadrants corrected for measurement error was 0.39 (0.10 - 0.64) for capillaries and 1.01 (0.85 - 1.16) for all vessels.

Conclusions: Intra-observer reliability for full evaluation of Sidestream Dark Field images was good for vessel detection and for flow classification but significantly poorer for the faster "Boerma" method. Furthermore, the Boerma method is likely to estimate different aspects of capillary flow than do the standard methods.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Animals
  • Blood Flow Velocity*
  • Microcirculation*
  • Microscopy, Video / methods*
  • Observer Variation
  • Reproducibility of Results
  • Software
  • Swine