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2.3 Microcirculatory Image Acquisition 43
Figure 2.4 Photograph of the SDF imaging device
illustrating the cylindrical encasement and the objective lens
probe covered with a sterile disposable cap.
a protective sterile disposable cap is securely attached around the probe. Once
the probe has been positioned exactly perpendicular on the tissue surface,
alterations in microcirculation perfusion must be avoided by eliminating
pressure-induced artifacts; this is achieved by gently pulling the probe back until
contact is lost and then slowly advancing to the point at which contact is regained
with the microcirculation in proper focus [43].
In a validation study comparing SDF and OPS imaging [44], both nail fold
and sublingual microcirculatory areas were imaged from the same locations
and compared. Moreover, imaging quality was also determined by employing a
specially developed image quality quantification system based on blood vessel
contrast with respect to the surrounding tissue by evaluating cross-sectional
grayscale histograms. Nail fold capillary diameters and RBC velocities yielded equal
quantitative results when measured by both techniques. Sublingual venular image
quality also showed comparable results between the two techniques. However,
capillary imaging quality and contrast was significantly better using the SDF
technique (Figure 2.5). Moreover, SDF images also depicted increased resolvability
in the granularity of flowing RBC columns in venules in comparison to OPS
images. The results of the validation study confirm the validity of SDF imaging for
the assessment of microcirculation geometry and intravascular blood flow kinetics.
Several image acquisition key points have been identified to achieve improved
image acquisition [43], including imaging of at least five sites per organ or tissue
region, avoidance of pressure-induced artifacts, elimination of secretions (such as
excess saliva), proper focus and contrast adjustments, and optimal recording quality.
The intrinsic heterogeneity or variability of the microcirculation dictates that at
least five adjacent sites should be imaged to accurately quantify the microcirculation
in a region of interest. However, when analyzing the images, some clips may be
unsuitable for analysis and should be discarded. It was concluded that at least three
image sites could produce reliable quantification, although if possible, five sites
should be obtained for evaluation. Capillaries and venules may be very sensitive
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44 2 Sidestream Dark-Field (SDF) Video Microscopy for Clinical Imaging of the Microcirculation
OPS imaging OPS imagingSDF imaging SDF imaging
Capillary
contrast and sharpness
Venular
contrast and sharpness
250 µm 225 µm 250 µm 225 µm
(
a
)(
b
)
Figure 2.5 Comparison of the same sublingual microcircu-
lation location using OPS imaging and SDF imaging. Panels
(a) and (b) illustrate the improved imaging quality of the
microvasculature using the SDF technique when compared
with that using OPS. (Reprinted from Goedhart et al. [44]
with permission.)
to pressure applied by the probe and can result in collapsed microvasculature; by
gently retracting and advancing the imaging probe on the tissue surface, these
artifacts can be avoided [45, 46]. Furthermore, reduction of excess secretions or
extravasated blood is recommended and can be performed by gentle cleaning of
the lens surface or the area of interest.
In combination with the above-mentioned recommendations for proper image
acquisitions, several technical issues should be addressed. Images should be
captured and stored as DV-AVI files, which can enable the investigator to perform
frame-by-frame image analysis if necessary. Accordingly, it is recommended to
record at least 20 s per image site.
2.4
Automated Microcirculation Image Analysis
The analysis of microcirculation video recordings can be lengthy, and for reasons
of practicality, a specially designed automated vascular analysis (AVA) software
package was developed [47]. Once acquired and digitized, microcirculation images
must be (semi)quantified to evaluate (alterations in) the functionality of the
microcirculation to distinguish between health and disease and to assess the effects
of therapeutic interventions. As mentioned previously, several scoring systems have
been developed for measurement and calculation of microcirculatory functionality
determinants, such as capillary density and perfusion. To objectify microvascular
image analysis while minimizing user input, specialized software packages have
been developed. CapImage was, for a long time, the only commercially available
software program for the analysis of microcirculation images. CapImage provided
a quantitative method for the estimation of blood vessel diameter, length, and RBC
velocity [42]; yet, vessel segment selection and vessel geometry determination were
done manually by superimposed line drawing on vessels, requiring a large degree
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2.4 Automated Microcirculation Image Analysis 45
of user interaction, which was very time consuming and increased observer bias
significantly. In a validation study comparing a new analysis software, CapiScope,
with CapImage, comparable results for vessel geometry and RBC velocities were
obtained [48]. Although both these software programs enabled semiautomated
analysis of microcirculatory blood flow from consecutive images, the analysis was
restricted to straight vessel segments.
More recently, Dobbe et al. developed a novel software package for microcircula-
tion analysis, known as automated vascular analysis [47]. This software automatically
determines vessel center linesin both straight and curvedvessel segments (a process
known as skeletonization), in order to measure vessel geometry and RBC velocities.
The first step in microcirculatory analysis procedure is image sequence stabiliza-
tion, performed using 2D cross-correlation. In the next step, by time-averaging an
image sequence, interruptions in capillary blood flow (e.g., plasma gaps and/or
leukocytes) are filled in, which enhances capillary geometry detection. Blood vessel
center lines are subsequently determined automatically by a method previously
described by Steger [49]. The technique detects each center line pixel in blood
vessels as the point at which the steepness in the grayscale intensity profile normal
to the center line is maximal. After vessel wall detection and skeletonization,
the software automatically cuts vessels at bifurcations for determination of RBC
velocities in separate vessel segments. The investigator is allowed to interact with
the above-mentioned segmentation process by cutting, deleting, or connecting
vessel segments. The novel RBC velocity determination technique, implemented
by Dobbe et al., maps the randomly distributed vessel center line pixels onto the
equidistant intervals of the space–time diagram using linear interpolation [47].
RBC velocity can then be determined by automatic detection or manual detection
of the slope of the line structure in the space–time diagram [42]. Using this new
programed algorithm, the software is able to automatically estimate the orientation
and velocity of RBC flow.
The AVA software was validated using video simulations of microvessels with
known diameters and RBC velocities [47]. The simulation movie was also analyzed
with CapiScope using default factory settings, as recommended by the software
manufacture. In addition, to illustrate clinical utility, sublingual SDF recordings
were acquired from a healthy volunteer and from a patient intraoperatively during
cardiac luxation (i.e., a procedure used during heart surgery involving lifting and
repositioning of the heart, which results in a direct decrease in cardiac output)
while undergoing open-heart surgery. The results demonstrated a close agreement
between the two software packages for vessel diameters and lengths. However,
using AVA, vessel density measurements (i.e., total vessel length (µm)/field of view
(µm
2
)) were performed in 67% of the time needed using CapiScope. Moreover,
determination of vessel diameter distribution took ∼4 h with CapiScope versus
10 min using AVA. RBC velocity analysis using AVA was done manually and was
very accurate (i.e., with a standard deviation of 4% in the range of 2.5–1000 µms
−1
);
assessment of blood velocity in all vessels within the recording was performed in
∼10% of the time required using CapiScope. Automated velocity assessment
with AVA in simulated blood vessels was 95% accurate for velocities of up to
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46 2 Sidestream Dark-Field (SDF) Video Microscopy for Clinical Imaging of the Microcirculation
750 µms
−1
. Validation and comparison of the two software has also shown that
CapiScope was unable to measure velocities below 50 pixels s
−1
(<35 µms
−1
) and
produced relatively large errors for higher velocities [47].
Dobbe et al. [47] have initiated the first step toward automated RBC velocity
assessment in curved vessels. Compared to CapiScope, AVA increases accuracy
and reduces user interaction and analysis time radically. However, visual inspec-
tion of the results of microcirculation images superimposed onto each other and
their possible interactions during selected phases in the analysis remains nec-
essary. It is important to realize when analyzing microcirculatory images that
software-mediated image stabilization implies a minor reduction in image size
and, thus, in microvascular geometry and RBC kinetics. Furthermore, different
video display standards (e.g., NTSC and PAL) use dimensions that may affect the
presentation of the microcirculatory image on a screen. Future OPS and SDF
research should be aimed at improving image quality, enhancing video frame
rate and resolution, and reducing illumination intervals (i.e., <13 ms), to im-
prove software-based microcirculatory image analysis of vessel geometry and RBC
velocity.
2.5
International Consensus on Microcirculation Image Acquisition and Analysis
As stated in Section 2.1, microcirculatory alterations may play an important role
in the development of (multiple) organ failure in critically ill patients, especially
in severe sepsis and septic shock. The rapid development of image acquisition
technology and systematic (semi)quantitative analytical scoring methods has led
to great variations in image acquisition and analysis among medical research
centers investigating the microcirculation. These variations in analytical results, in
conjunction with the analysis-mediated conclusions on microcirculation function,
have led to the organization of a round table conference in November 2007, aiming
to achieve a consensus on microcirculatory image acquisition and analysis to
standardize the clinical assessment of the microcirculation.
In the consensus report [43], it was concluded that, due to the heterogeneous
nature of the microcirculation, ideally, five sites of an organ must be imaged
and analyzed to draw reliable conclusions on microcirculation functionality. The
recommended optical magnification for human sublingual microcirculation is
5×, given that the heterogeneity of the microcirculation cannot be taken into
account when using higher magnification. An important aspect of microcirculatory
image acquisition, which applies for both OPS and SDF imaging, is preven-
tion of pressure-induced artifacts. Pressure on the microvasculature can alter
perfusion and thereby result in unreliable analysis and conclusions about the
microcirculation. During the consensus meeting, it was concluded that venular
flow should always be continuous rather than stopped or intermittent and that
(patho)physiologically induced microcirculatory alterations occur mainly at the cap-
illary level. Thus, it was determined that venular perfusion was a good indicator for
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2.5 International Consensus on Microcirculation Image Acquisition and Analysis 47
the presence of pressure artifacts. Trzeciak et al. [45] recently proposed a standard
operating procedure for microcirculation image acquisition, serving as a guide
for prevention of pressure-induced artifacts. Briefly, the imaging probe should
be advanced to the microvasculature until flow is partially obstructed. Then, the
probe should be carefully withdrawn until contact with the tissue of interest is lost.
Finally, the probe should be advanced once again to the point at which contact
with the tissue of interest is regained. By recording continuously during this
procedure, adequate images for analysis can be included and extracted from the
digital videotape segment obtained from the tissue of interest.
In oral medicine, this technique is particularly important since the capillaries
in the gingiva are highly prone to rapid vascular collapse when positioning the
imaging probe for measurements. As a consequence, since the SDF device relies
on Hb in circulating RBCs for contrast imaging, no microcirculation can be
observed. In a recent study by Milstein et al. [46], the assessment of cytostatic-based
polychemotherapy on rabbit maxillary gingival perfusion was performed with
the SDF imaging device mounted on a micromanipulator. Using a setup with
a micromanipulator easily enabled fine control of probe positioning and the
acquisition of stable microcirculation images on the gingival mucosa without
obstructing gingival microvascular perfusion.
When analyzing SDF images, one should first identify the capillary microvessels,
which are vessels with a diameter ≤25 µm. Geometrical and perfusion analysis will
mainly be performed on these conduits, since they are the primary determinants
of tissue perfusion. In the round table consensus meeting [43], three parameters
were agreed upon, which comprehensively describe microcirculatory alterations
as seen in sepsis: (i) PVD [13], representing an estimate of the FCD; (ii) MFI
[41], providing information about the mean flow properties present; and (iii)
the perfusion heterogeneity [45], derived from the MFI calculation as a crucial
parameter for identifying the oxygen extracting capabilities of the tissue embedding
the microcirculation.
PVD provides an accurate estimate of microcirculatory FCD. The advantage of
the PVD score is that it accounts for most variables involved in tissue perfusion,
including vascular density and PPV. A disadvantage, however, is that RBC veloci-
ties cannot be accounted for in continuously perfused capillaries. MFI scoring is
relatively simple to perform; however, the score does not provide any information
on the FCD and is discontinuous. A change from 1 to 0 might have different
implications than say a change from 2 to 1; this complicates the interpretation
of the MFI score. The consensus is that all index parameters (PVD, PPV, and
MFI) should be measured to comprehensively describe the functional state of the
microcirculation. In addition, to distinguish between perfused and nonperfused
microvessels, the MFI score, provided that flow is homogeneously distributed
within the imaged video segment, can differentiate between flow types, hence pro-
viding more detailed information on perfusion dynamics. Although PPV does not
distinguish between flow types, it does provide information on flow heterogeneity
within the imaged microvasculature. Trzeciak et al. [45] investigated early sublin-
gual microcirculatory perfusion derangements in patients with severe sepsis and
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48 2 Sidestream Dark-Field (SDF) Video Microscopy for Clinical Imaging of the Microcirculation
septic shock. They semiquantified the MFI in five imaged sites and calculated a flow
heterogeneity index (HetIndex), defined as the highest site flow velocity minus the
lowest site flow velocity, divided by the mean flow velocity across all five sublingual
sites. Patients with sepsis had more heterogeneous blood flow when compared to
their control group. The results of this study showed that nonsurviving patients
had a more heterogeneous flow distribution than surviving patients. Hence, flow
velocity, capillary density, and flow heterogeneity could independently contribute
to the risk of organ dysfunction in sepsis.
In summary, scoring should include a vascular density index (PVD and PPV),
a capillary perfusion index (MFI), and a HetIndex to describe tissue perfusion
dynamics. It is important to emphasize, however, that these scoring systems have
been developed and validated for identifying and quantifying microcirculatory
networks as they pertain to human sublingual microcirculation during sepsis
and septic shock scenarios. For scoring microcirculatory alterations during other
disease states, although applicable, it is recommended that each parameter be
validated first for each particular condition.
2.6
Future Prospects
In the future, technological improvements in microcirculatory imaging will be
realized with the incorporation of more advanced camera technology with improve-
ments in image resolution and video frame rates. This will enable RBC velocity
measurements in high flow vessels (e.g.,
>
1000 µms
−1
) with more accurate vessel
geometry determination. Technological modifications in conjunction with fully au-
tomated analytical software with advanced built-in microcirculatory scoring systems
will lead to rapid and more exact determination of microcirculatory functionality
in both clinical and experimental settings. To this end, future research should also
be dedicated to the precise role of vessel diameter and RBC velocity as they relate
to oxygen delivery to tissue parenchymal cells. Efforts have already been made
to assess microcirculation MFI in critically ill patients on-site (patient bedside)
in a (near) real-time point-of-care (POC) setting [50]. The results from that study
indicated a good correlation between bedside-derived POC MFI scores and conven-
tional offline analysis. However, on-site microcirculatory measurements of vessel
length, diameter, and RBC velocity would be more difficult to realize, since images
must be stabilized and time averaged to obtain the desired parameters. Another
point of concern for OPS and SDF imaging is to eliminate pressure artifacts related
to application of the SDF probe onto organ and tissue surfaces [40, 45]. Lindert
et al. [40] has engineered a suction device that can be placed around an OPS probe.
Suction applied via small perforations in the device prevented the OPS probe from
applying pressure onto the tissue and subsequently reduced movement during
microcirculatory image acquisition. Recently, a similar suction device, the image
acquisition stabilizer (IAS), was developed and clinically validated for SDF imaging
[51]. The IAS can be directly attached around the tip of the SDF probe disposable
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References 49
plastic cap. Using the IAS increased the yield of analyzable microcirculatory images
by reducing both image drifting and the force necessary to prevent pressure arti-
facts, resulting in prolonged stable image recordings. Moreover, the results also
showed that there was no significant difference in blood flow in small, medium, or
large blood vessels in comparison to data acquisitions without the IAS.
Another clinically favorable feature enhancing intravital microvascular research
would be a microcirculatory oxygenation imaging modality directly implemented
into a handheld device. Such an imaging modality would provide images of the
microcirculation, in which oxygenation in each pixel is expressed in false colors
(e.g., blue to red representing 0–100% blood oxygenation) [52]. This technique
could allow on-site assessment of microcirculatory tissue oxygenation, which
would be of use especially in emergency medicine, where quick assessment of
microcirculatory functionality is desired.
2.7
Conclusion
Microcirculatory image acquisition and analysis has advanced considerably since
the discovery of the capillary in the late seventeenth century. The introduction
of intravital SDF imaging and the new AVA software has significantly improved
microcirculation assessment, bringing the clinician ever closer to real-time di-
agnostics at the microvascular level. The consensus on microcirculatory image
acquisition and analysis has furthermore standardized OPS and SDF protocols
to enable the comparison of microcirculatory alterations among different studies.
With technological advancements, conclusions based on the analysis of the micro-
circulation have eased the transition from bench to bedside, enabling the clinician
to rapidly distinguish between health and disease and to evaluate the impact of
therapeutic interventions at the bedside.
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