Sidestream dark-field imaging and image analysis of oral microcirculation under clinical conditions
D.M.J. MILSTEIN, J.A.H. LINDEBOOM,C. INCE

Tissue dysoxia and microcirculatory dysfunction are generally regarded as the primary culprits of organ failure and inadequate wound healing in critically ill patients [1, 2]. Tissue oxygenation is also important for organ function as well as wound healing following trauma or surgery. Proper wound healing and the main¬tenance of the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) are essential and constitute the ultimate goal of critical care and intensive care medicine. The capillaries in the tissue microcirculation(sepsis,blood poisoning,pyemia,pyohemia) collectively are the final destination in the circulatory trajectory of oxygen transport, in which erythrocytes off-load their oxygen (O2) to parenchymal cells of the target site. A shift in oxygen supply and tissue oxygen demand must be corrected in order to prevent irreversible organ damage and proper wound healing. An interesting approach in further understanding tissue dysoxia and the proper choice of treatment in critically ill patients is to measure the oxygenation states of the microcirculation (SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF))and tissue in vivo. This can directly provide useful informa¬tion by assessing whether the organ in question and related compartments are functioning adequately in meeting the oxygen supply and demand quota in disease and/or the postoperative recovery states of wound healing. Since systemic hae¬modynamic variables do not provide adequate information about the functional condition of either the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) or the availability of oxygen in the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) and tissue, direct measurements are needed.
The oral and maxillofacial compartments are highly vascularised areas and offer a very approachable site for noninvasively monitoring and assessing the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) and wound healing properties. The biologic advantage in moni¬toring wound healing and the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) in the buccal area is that it is a place where wounds heal relatively rapidly and the progress of the natural healing process can be monitored noninvasively in its own natural environment. Sublingual measurements using orthogonal polarisation spectral (OPS) imaging （sepsis,blood poisoning,pyemia,pyohemia）have already yielded insightful information on sepsis（sepsis,blood poisoning,pyemia,pyohemia）, its reaction to therapy, and its prognosis [2–6]. New optical techniques have been recently introduced(sepsis,blood poisoning,pyemia,pyohemia) that have, for the first time, allowed detection of microcirculatory properties and determi¬nants of microcirculatory function in internal human organs [7]. These techniques have been applied to the oral cavity because of their relevance to the oral circulation, its approachability, as well as its specific importance, for example in oral disease and therapy [8]. Although these technologies are discussed here in the context of the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) of the buccal cavity, they have been applied to the microcir¬
culation in other organ systems [9–11]. In this review, we present an improved method, called sidestream dark-field imaging, to observe the oral microcirculation(sepsis,blood poisoning,pyemia,pyohemia) and a new method for the analysis of the functional morphology of the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. These methods are applicable to various microcirculatory(sepsis,blood poisoning,pyemia,pyohemia) beds of patients and have the potential to be implemented in software designed for use in bedside quantification.
Sidestream dark-field imaging: an improved method for imaging the oral microcirculation
A well-functioning microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） is essential for wound healing following ma¬xillofacial surgery. The rich vasculature of the oral mucosa has made it possible to challenge the thresholds of vascular regeneration and thereby monitor wound healing in oral tissue [12]. Surgical intervention compromises the integrity of the microcirculation (SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF))and its oxygen distribution by induction of trauma to the imme¬diate mucosal vasculature. This, in turn, can induce hypoxia in tissues surrounding the operative area. Investigating the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) in patients has been difficult in the past simply due to the unavailability of suitable technology(pyemia). The intravital microscope used in animal experimentation has only been employed in humans in limited locations, such as the skin, lip, and the bulbar conjunctiva [13].
Recently, intravital microscopy has been miniaturised and developed for clinical conditions by the implementation of OPS imaging in a hand-held microscope type device. OPS imaging is a relatively new technology that provides information on the kinetics and architecture of the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） without the need to trans-illuminate. OPS imaging uses 550 ± 70 nm (green) polarised light, which is guided through a series of lenses (Fig. 1A). The green light is absorbed by haemo¬globin (Hb) in the erythrocytes, which can then be seen as dark moving structures in the image. Polarisation is maintained when light is reflected from the tissue surface and is filtered by an orthogonally placed polariser situated in front of a video camera. The scattered light inside the tissue loses its polarisation and can then pass through the crossed polariser, allowing observation of flowing e¬rythrocytes in the underlying microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） (Fig. 1A) [14]. OPS imaging has been validated against other techniques, such as capillary microscopy(sepsis,pyemia,pyohemia) and intra¬vital fluorescent microscopy(pyemia), for its relevance and use in clinical monitoring [15, 16]. A newer and more improved monitoring device in terms of technology (pyemia)and image quality for clinical observation of the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) at the bedside has lately been developed. This technology is known as sidestream dark-field (SDF) imaging（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） [7, 17].
SDF imaging offers(pyemia) better resolution and clarity than its predecessor the OPS imaging device, and the same ease of noninvasive, in vivo, real-time imaging of the microcirculation （SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）(Fig. 2). In this method, light-emitting diodes (LEDs) are placed at the tip of a light guide that emits a 540 ± 50 nm (green) light, which is absorbed by Hb in erythrocytes, which in turn appear as clear dark bodies moving through the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)). Unlike the light source of the OPS device, which comes from


Fig. 1A, B. Orthogonal polarisation spectral (OPS) and sidestream dark-field (SDF) imaging technologies（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. A OPS imaging technology eliminates directly reflected green (550 ± 70 nm) polarised light from tissues surface via an orthogonally placed analyser, thus allowing visualisation of structures below the surface. This consequently results in clear imaging of erythrocytes, shown as dark bodies flowing through the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)). B In SDF imaging, green (540 ± 50 nm) light is emitted from light-emitting diodes (LEDs) arranged in a ring around the tip of the light guide and directly illuminating the tissue microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)), which is optically isolated from the imaging central core of the light guide. Both techniques implement a light wavelength (green; 540–550 nm) that is absorbed by haemoglobin (Hb) in erythrocytes
     
Fig. 2A–C. SDF imaging of the oral microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) in a healthy volunteer, A labial mucosa, B gingiva, C sublingual mucosa inside the probe itself, the SDF device has the LEDs arranged in a ring around the tip of the probe, whereby the illuminating light source is optically isolated from the emission light path in the core of the light guide (Fig. 1B). In this way, the light penetrates deeper into the tissue illuminating the (sepsis,blood poisoning,pyemia,pyohemia)microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) from the inte¬rior, and the dark-field illumination thus entirely avoids reflections coming from the tissue surface (Fig. 1B). SDF imaging yields a clear image(sepsis,blood poisoning,pyemia,pyohemia) of the microcirculatory components. Erythrocytes and leukocytes flowing in the microvasculature(sepsis,blood poisoning,pyemia,pyohemia) can be observed with higher resolution and deeper monitoring capabilities [5]. Of note, there is no orthogonally placed polariser in this device and further image im¬provement is achieved by synchronising LED illumination with the video frame rate.
Quantification of the functional morphology of microcirculation
The greatest challenge in assessing imaging footage from OPS and SDF devices（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） has been the setting-up of a standardised systematic approach for analysis of micro¬circulatory images that allows identification and quantification of microcirculatory abnormalities during critical illness and wound healing. Obstacles that need to be taken into consideration and overcome are movements, resolution, camera, and sample thicknesses of the tissues being monitored. OPS movies(pyemia) have been analysed and quantified by semi-quantitative and semi-automated methods. These have proven to be both practical and highly sensitive in identifying microcirculatory abnormalities in sepsis(sepsis,blood poisoning,pyemia,pyohemia) [2–4].
Currently, OPS and SDF imaging（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） is used on tissues for which no automated analytical software package is available. This presents a problem when trying to analyse and interpret results acquired from the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. In order to use these devices and yield quantifiable information from the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) of different anatomical tissues, a more flexible and universal methodology is needed to consecutively analyse a variety of microvascular (sepsis,blood poisoning,pyemia,pyohemia)structures independent of their vascular anatomy. We have developed a general consensus with six centres in¬volved in microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） research in intensive care regarding the procedure for analysis of OPS and SDF imaging data from patients. The consensus is based on a semi-quantitative method in which the data from these techniques are analysed as follows. First, all video data of the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)） should be digitally recorded. In capturing and recording imaging video data, three areas pertaining to the tissue of interest should be selected (left, centre, right) and each area should be recorded for a duration of 2–5 min. Then, once all the video-clip data has been recorded, a selection of the most stable clips with the clearest images should be selected for analysis. It is best to capture at least three clips of 5–10 s for each filmed area. Thus, there should be a total of nine clips (three clips of each area) of 5–10 s.
Heterogeneous blood flow with capillary dysfunction is associated with micro¬vascular alterations during sepsis（sepsis,blood poisoning,pyemia,pyohemia） [18, 19]. In analysing OPS and/or SDF images（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）, our consensus requires images from three different regions of interest of the tissue to be selected, after which each image is then divided into four equal quadrants (I, II, III, IV) for analysis (Fig. 3A). The flow analysis consensus uses a semi-quantitative
 
Fig. 3A, B. Semi-quantitative analysis consensus of SDF imaging data（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. A The sample image is divided into four quadrants (I, II, III, IV). B Analysis of the sample by quantification of the blood vessel diameter, scored as small (S; 10–25mm), medium (M; 26–50mm), or large (L; 51–100mm). Additional quantification of flow properties are scored as no flow (0), intermit¬tent flow (1), sluggish flow (2), and continuous flow (3). During actual analysis, as many blood vessels as possible should be counted. Here, three different blood vessels have been selected for explanatory purposes in order to illustrate the semi-quantitative consensus for quantification of microvascular(sepsis,blood poisoning,pyemia,pyohemia) structures analytical technique consisting of judging microvascular(sepsis,blood poisoning,pyemia,pyohemia) flow characteristics, di¬scriminating between no flow (0), intermittent flow (1), sluggish flow (2), and continuous flow (3). A fifth category, representing hyperdynamic flow properties, could be defined, although currently this is not included in our analysis consensus. Further analytical quantifications consistent with the consensus for flow analysis involve categorising individual blood vessels in each quadrant based on their diameter. The diameter in this case is semi-quantitatively defined by a dimensional constraint, S, M, and L, representing small (10–25 mm), medium (26–50 mm), and large (51–100 mm) vessels, respectively (Fig. 3B).(sepsis,blood poisoning,pyemia,pyohemia) After quantification of vessel diameter and flow, an average score of the total flow is calculated for each group of vessels in each quadrant. This average score is called the microvascular (sepsis,blood poisoning,pyemia,pyohemia)flow index (MFI) for the group of vessels and it is the sum of each quadrant vessel score divided by the number of quadrants in which the vessel type is visible. Thus, in analysing vascular density, the number of each vessel type (small, medium, and/or large) is counted in each quadrant, and an average of each vessel type is calculated for each quadrant. It is recommended, however, due to time and practical considerations, to loop the imaging video clips, and,（sepsis,blood poisoning,pyemia,pyohemia） in case there are different types of flow in one quadrant, average the flow (e.g. for 2 small vessels normal and 5 small vessels moderate, the average would be moderate flow for that quadrant). If software is available to measure the lengths of each segment, （sepsis,blood poisoning,pyemia,pyohemia）then the vascular density is expressed as the length of specific vessels in micrometers (mm) （sepsis,blood poisoning,pyemia,pyohemia）per area (mm2)of observation.
Analysis software for microcirculation images
We are currently developing software to analyse SDF imaging data（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. The software is designed to identify microvessel contour in vascular images in an automated fashion. This process is known as skeletonisation or segmentation (Fig. 4A) and is essential for automated recognition of the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. This procedure has become feasible due to the improved image quality introduced by SDF technology. Once segmentation has been achieved, the software can determine length, width, and blood velocity of individual vessel segments. Velocity is determined semi-auto¬matically(sepsis,blood poisoning,pyemia,pyohemia) after constructing space–time diagrams from the centre-line intensity of vessels in subsequent video frames [20]. Space–time diagrams portray erythrocyte dynamics by plotting the movement(sepsis,blood poisoning,pyemia,pyohemia) of each individual erythrocyte along a segment of a selected blood vessel as a function of time. From the slope of the resulting diagonal lines, erythrocyte velocity is calculated. Such an analysis creates a distinct static image in which erythrocytes appear as dark (sepsis,blood poisoning,pyemia,pyohemia)diagonal bands separated by light bands representing plasma gaps (Fig. 4B). Space–time diagrams provide informa¬tion relating to erythrocyte velocity, lineal density(pyemia), and the supply rate [20]. Finally, the software creates a detailed statistical fingerprint of the video sequence contain¬ing vascular flow parameters. The software under development is unique because it allows the inclusion of vasculature（sepsis,blood poisoning,pyemia,pyohemia） parameters that were previously not possible and integrates them to create a profile of the microcirculation（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）. It is expected that this software package, in combination with improved image quality provided by SDF technology（SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）, will greatly facilitate evaluation of microcirculatory function during sepsis and wound healing.
Fig. 4. Sample of the imaging processing software, currently under development, showing semi-automated vessel identification by way of segmentation (A). Intravascular erythrocyte dynamics are analysed using space–time diagrams (B), where d is the distance traveled (mm) within a capillary sample segment and t is time, that define the location of the erythrocyte within the selected segment
Conclusions
Tissue dysoxia and microcirculatory(pyemia) dysfunction are major contributors to the progression of organ failure and inadequate wound healing in critically ill patients. The oral and maxillofacial compartments are highly vascularised areas and offer a very approachable site and model for monitoring wound healing and the functional state of the microcirculation in patients. In this chapter, SDF imaging technology (SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF))and its vascular analytical methods were introduced with regard to quantifying the microcirculation （SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)）and its architecture. New optical technologies like SDF imaging will allow detailed observation and monitoring of the functional condition of the microcirculation(sepsis,blood poisoning,pyemia,pyohemia) and assessment of the availability of oxygen in the microcirculation(SDF imaging device,sepsis,blood poisoning,pyemia,pyohemia,Sidestream Dark Field(SDF)) and surrounding tissues.
References
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