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Early GPS receivers were bulky, heavy devices. The agency developed and furthered much of the conceptual basis for the ARPANET—prototypical communications network launched nearly half a century ago—and invented the digital protocols that gave birth to the Internet. Moreover, biopsies are highly impractical for monitoring burn healing progress as they perpetuate the wound presence, thereby increasing the risk of infection.
At present, the most widely used diagnostic method for burn injuries is clinical assessment which involves examination of exterior features of the wounds. As a result, several light-based technologies have been developed over the years to assist in the clinical classification of burns [ 4 ]. A well-recognized optical technique for burn diagnosis is laser Doppler perfusion imaging LDI [ 4 — 6 ].
LDI is a noncontact scanning method based on a frequency change of laser light upon reflection off moving blood cells.
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The frequency shift is proportional to the amount of perfusion in tissue, allowing LDI to produce a color-coded map that corresponds to varying burn depths. LDI is considered to be a valid measure of burn depth and exhibits high correlation with burn wound histology; yet, current commercially-available laser Doppler imagers are relatively large, require a prolong scanning time, and are not promoted for early diagnosis during the first 48 hours post-burn hpb [ 4 , 7 , 8 ]. Laser speckle contrast analysis LASCA is another optical technique, related to LDI, which has been used for noninvasive scan-free assessment of burn severity [ 4 , 9 — 11 ].
In LASCA, a wide-area laser beam illuminates the burn wound to produce speckle from backscatter off the irradiated tissue volume. The volumetric speckle is projected onto a two-dimensional camera sensor to cast a time-integrated speckle image. From this image, a color-coded map that conveys information on burn severity is rapidly generated over a large field-of-view without any scanning by calculating the speckle contrast as the ratio of the standard deviation to the mean speckle intensity over a local sliding window [ 12 ].
Recently, LASCA has been shown to provide early assessment of burn severity in a porcine burn model in vivo using a scientific-grade camera [ 10 ] and a simple imager comprising a camera-phone [ 11 ]. It is worth mentioning that camera-phone-based LASCA imaging has also been demonstrated useful for noninvasive widefield measurements of skin perfusion, blood pulsation and pulse rate [ 13 , 14 ].
In this work, we use point laser illumination of burn wounds rather than widefield illumination and camera-phone imaging to detect diffuse reflectance speckle images of the wounds rather than projected volumetric speckle images. These images are subsequently analyzed for evaluating noninvasively burn severity in tissue phantoms and in a longitudinal in vivo porcine burn study. In particular, we implement a spatiotemporal fluctuation analysis scheme based on the processing scheme proposed by Sadhwani et al.
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Unlike the system devised by Sadhwani et al. While the basic setup used here is similar to that of oblique incidence reflectometry OIR [ 21 , 22 ], we analyze spatial intensity variations in diffuse reflectance laser speckle patterns rather than OIR distances between the diffusion center and illumination entry point.
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Note that a technique related to ours, termed diffuse correlation spectroscopy, based on temporal autocorrelation analysis of rapidly fluctuating photon count signals from a single speckle was used to assess burn severity in vivo in a porcine burn model using fiber optics and photon-counting photomultiplier tubes [ 23 ]. Finally, it is noteworthy that spatiotemporal pattern analysis of time-varying diffuse reflectance speckle has also been used for measuring biomechanical properties and cap thickness of atherosclerotic plaques [ 16 , 17 ].
The manuscript is organized as follows. Section 2 describes the camera-phone diffuse reflectance laser speckle detection dr-LSD system and details methods for analyzing diffuse reflectance laser speckle dr-LS patterns, preparing tissue phantoms, using an in vivo porcine burn model, including histopathological and statistical analysis of porcine burn depth.
In section 3, we present results and discussion on the instrument performance in phantoms and in a longitudinal porcine burn study. Finally, conclusions are drawn in section 4. An optical setup comprising a focused red laser for sample illumination and a camera-phone imager for detecting time-integrated dr-LS patterns at the burn surface was designed as illustrated in Fig.
Note that this incident angle was the smallest possible in the current prototype due to the size of optics and optomechanics used. Low high irradiances of 0. Note that we used only the red channel of the interpolated Bayer data provided by the camera-phone sensor. Finally, the instrument was attached to a support arm, allowing convenient orientation of the apparatus over the wounds and stabilizing the system during data recording. Camera-phone diffuse reflectance laser speckle detection and analysis dr-LSD for burn diagnosis.
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To evaluate burn severity i. In brief, assuming that a burn wound can be simplified as a two-layered medium with a static or low-perfusion burn layer overlying a perfused tissue, Sadhwani et al. This agreement is due to the semi-oval shape of diffuse reflectance light distributions in tissue [ 26 ] and the quasi static versus dynamic coherent light scattering from the burn layer and the underlying perfused tissue, respectively.
To determine r 0 and hence D , we first acquired with a camera-phone imager a data set of 15 raw diffuse reflectance speckle frames of the burn wound with p resolution and H. Note that the H. The number of angles N used throughout this work was We produced two-layered tissue phantoms consisting of a statically-scattering Teflon layer overlying a perfused Intralipid region as illustrated in Fig. An in vivo animal experiment was performed using a porcine skin burn model.
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O research unit Kibbutz Lahav, Israel. Full details of the experiment are described in our previous publication [ 11 ]. The animal was fasted 12 hours prior to anesthesia and hair was clipped from its dorsum at the beginning of the experiment. General anesthesia, endotracheal tubing and monitoring of oxygen saturation, body temperature, electro cardiogram and heart rate were maintained continuously throughout the experiment. Four groups of 12 burns were inflicted, each with a different probe-skin contact time of 10, 20, 30, and 40 s, resulting in a total of 48 burn sites see Fig.
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Temperature was monitored using a thermocouple threaded into the bottom of the block. Only the weight of the block was applied with no extra pressure see Fig. For minimizing variations in producing the burns, only one person YS created all burns. Histopathology of porcine burn biopsies is detailed in our previous publication [ 11 ]. In brief, four 4-mm punch biopsies were removed from each group of burns of probe-skin contact times of 10, 20, 30, and 40 s at 8, 32, and hpb.
Biopsied sites were excluded from subsequent dr-LSD measurements. Burn thickness was determined by the deepest predetermined histopathological feature identified in the slides. Burn depth, indicated by the two-sided arrow, was evaluated by the deepest predetermined histopathological criteria identified in the slides. The single asterisk denotes empty cavity of the pilosebaceous unit, the diamond indicates separation of collagen fibers edema , double asterisks identify vascular congestion, and the triangle points to eosinophilia of collagen fibers through the dermis.
The scale bar is 1 mm. For histopathological assessment of porcine burn thickness, significance of estimated burn depth data was tested by two-way ANOVA with factors of probe-skin contact time 10, 20, 30, and 40 s and time post-burn 8, 32, and hpb. For in vivo camera-phone dr-LSD of porcine burns, statistical significance of speckle spot diameter data was determined via repeated-measures ANOVA with factors of probe-skin contact time 10, 20, 30, and 40 s and time post-burn 8, 32, and hpb.
We tested various threshold values and number of angles for optimal distinguishability between the phantoms.
Note the central region in these profiles where a reduction in the speckle standard deviation occurred due to partial saturation of the camera-phone sensor. Thresholds are indicated by the different shapes. Diameters are averages of five repeated measurements. Standard errors were negligible.