TY - JOUR
AU - MD, Jeffrey W. Shupp,
AB - Abstract Burn conversion is a contributor to morbidity that currently has no quantitative measurement system. Active dynamic thermography (ADT) has recently been characterized for the early assessment of burn wounds and resolves the three-dimensional structure of materials by heat transfer analysis. As conversion is a product of physiological changes in three-dimensional structure, with subsequent modification of heat transfer properties, the authors hypothesize that ADT can specifically identify the process of burn conversion and serve as an important tool for burn care. A heated comb was used to create four contact burns separated by three interspaces on bilateral flanks of 18 rats, resulting in 144 burns and 108 interspaces. Wounds were imaged by ADT and laser Doppler imaging (LDI) pre- and post-injury through hour 36, with a subset undergoing biopsy collection. Direct analysis of thermographic and perfusion data revealed an increasing difference between burns and interspaces by ADT with increasing injury severity (P < .05), while LDI characterized the opposite. Comparison of stasis zones to burns reveals the ability of ADT to distinguish these two regions in both intermediate and deep burns at every assessment (P < .05). In addition, when wounds are grouped as converting or not converting, ADT identifies by hour 12, wounds that will convert (P < .05). LDI identifies by hour 4 wounds that will not (P < .05). This study has demonstrated that ADT can directly identify burn wound conversion, while LDI can identify nonconverting wounds. Further advancement of ADT technology has the potential to guide real-time interventional techniques. A unique and challenging problem in burn wound assessment is the phenomenon of burn wound conversion. This results in a loss of viability of nearby initially uninjured tissue. The Jackson model of the burn wound (Figure 1) illustrates three zones: the zone of necrosis, composed of nonviable tissue, the zone of stasis, which includes potentially viable tissue, and the zone of hyperemia, which invariably recovers.1 Decades of studies have focused on factors that modulate the dynamics of the zone of stasis to result in more or less recovery of viable tissue. These have included fluid resuscitation,2 pharmacotherapy,3 early excision,4 and others.5,6 The assessment of this region however is difficult and subjective as it is largely obstructed from view by the zone of necrosis. In this study, histological assessment is often required to evaluate tissue damage, which is also inherently limited by the biopsy's lack of representation of the whole wound. Clinically, this assessment is further complicated by the variability in response to treatment, both wound-to-wound and person-to-person. Consequently it is apparent that an accurate, more objective and noninvasive metric of wound conversion would be helpful as burn care advances further in the direction of targeted therapy. Figure 1. View largeDownload slide Jackson model of the burn injury illustrating the zones of necrosis, stasis, and hyperemia. Figure 1. View largeDownload slide Jackson model of the burn injury illustrating the zones of necrosis, stasis, and hyperemia. Active dynamic thermography (ADT) is an emerging noncontact diagnostic technique for the assessment of burns, which has recently been shown to be particularly useful in the acute phase of wound development.7 The physiologic changes ADT detects within the burn wound are the development of the concentric zones of the Jackson model, including a manipulation of capillary blood flow, shifting interstitial fluid content and changing of the overall tissue water content. These shifts result in a measurable decrease of thermal conductivity in the zone of necrosis and an increase in the zone of stasis.8,–10 The principle of ADT follows then that if a thermal pulse were delivered to the surface of the skin, its rate of dissipation through the dermal capillary network and to the dermal plexus below would be a direct product of the subsurface resistance to heat transfer (Figure 2). ADT can therefore quantify burn conversion by temporally examining changes in the thermal conductivity of tissue in the zone of stasis. Figure 2. View large Download slide Principle of active dynamic thermography. After a thermal stimulation, the energy emitted in the form of radiation over time (q[Combining Dot Above]R) is proportional to the energy transferred to and removed by the dermal plexus (q[Combining Dot Above]C). Because the thermal conductivity (k) of the zone of stasis is greater than that of the burn, the rate of energy transferred to the dermal plexus will be proportionally greater according to Fourier's law: . The rate of change of energy emitted at the surface will therefore be greater for the zone of stasis than that of necrosis. Figure 2. View large Download slide Principle of active dynamic thermography. After a thermal stimulation, the energy emitted in the form of radiation over time (q[Combining Dot Above]R) is proportional to the energy transferred to and removed by the dermal plexus (q[Combining Dot Above]C). Because the thermal conductivity (k) of the zone of stasis is greater than that of the burn, the rate of energy transferred to the dermal plexus will be proportionally greater according to Fourier's law: . The rate of change of energy emitted at the surface will therefore be greater for the zone of stasis than that of necrosis. The animal model employed in this study was one originally developed for the study of pharmacotherapy intervention in burn conversion by Singer et al.6,11,12 and has been vetted by our laboratory and others.13 This model utilizes a heated brass comb to induce four burns separated by uninjured interspaces (Figure 3), which will convert to dead tissue in a period of 36 hours. This model was also modified to include two groups of animals with increased or decreased injury severity. This modification allowed for the difference between a burn and its adjacent zone of stasis to be addressed for a range of injury severities. Figure 3. View largeDownload slide Brass comb used to induce burns (A) and a representative image of the 30-second burn (B). Figure 3. View largeDownload slide Brass comb used to induce burns (A) and a representative image of the 30-second burn (B). The ADT device utilized in this study was custom developed, and improves upon its predecessors by allowing precise, sub-millisecond control of thermal stimulation. Calibration of this imaging system to determine proper stimulation parameters was performed on a custom-built phantom model of skin, based on a similar ADT test target published by Shepard et al.14 To test the hypothesis that ADT is capable of detecting burn wound conversion, this study was designed around an accepted rat model of burn conversion. An ADT system was developed for use with murine species, and a thermography phantom was developed for calibration. Finally, the model was modified to result in a slower or more rapid rate of interspace conversion to test the imagers' ability to characterize this process. Here, data are presented for the first time describing the use of an imaging system to identify and predict the sensitive process of burn conversion. METHODS Imaging Calibration Phantom To determine the optimal stimulation parameters of this custom designed ADT device, an imaging calibration phantom was prepared by mounting a series of stainless steel washers within paraffin wax at depths ranging from 0 to 8 mm, to assess visibility of depth (Figure 4). The inner and outer diameter of the stainless steel (k = 15 W/mK)15 washers ranged from 3.9 to 5.5 mm and 10 to 13.2 mm, respectively. Paraffin wax (k = 0.346 W/mK)16 was chosen as a medium for its thermal conductivity (k) similar to that of human skin (epidermis: k = 0.209 W/mK, dermis: k = 0.310 W/mK).17 The surface of the phantom was prepared with a coat of matte black paint to give a surface emissivity (ε) of (ε = 0.95)18, similar to human skin (ε = 0.976)19. Imaging of the phantom was performed at stimulation times ranging from 500 to 10,000 ms and thermal recording analyzed between 0 and 30 seconds poststimulus to optimize parameters for skin imaging. Figure 4. View largeDownload slide Active thermographic imaging system (A) consisting of thermal camera (a), data acquisition control system (b), and stimulation lamps (c), and calibration model (B). Figure 4. View largeDownload slide Active thermographic imaging system (A) consisting of thermal camera (a), data acquisition control system (b), and stimulation lamps (c), and calibration model (B). Animal Model All animal experimentation performed was approved by the MedStar Health Research Institute Institutional Animal Care and Use Committee. A total of 18 male Sprague Dawley rats (Harlan Laboratories, Frederick, MD) were used in this study designed to assess burn conversion by ADT imaging. Animals were anesthetized with isofluorane, hair was clipped and chemically depilated with Veet (Reckitt Benckiser, Parsippany, NJ) before injury. Burns were created on the bilateral flank of each animal by contact with a 100°C brass comb for 30 seconds. A subset of animals (n = 6) underwent biopsy collection for the remainder of the time course, while another subset (n = 6) underwent imaging. This burn is characterized by four, third-degree 20 × 25 mm rectangles separated by three, 5 × 25 mm interspaces as described by Singer et al6,11,12 (Figure 3). To assess conversion, the injury was modified to produce a less severe 15-second contact (n = 3), and a more severe 45- second contact burn (n = 3). Animals were anesthetized and imaged by laser Doppler imaging (LDI), ADT and a standard photograph before injury, and at 0, 2, 4, 6, 12, 24, and 36 hours postinjury. Active Thermography Imaging Device Design The ADT imaging device (Figure 4A) consisted of a thermal camera, data acquisition system, and stimulation lamps interfacing with Matlab software (MathWorks, Natick, MA). A USB-6218 data acquisition system (National Instruments Austin, TX) controlled a transistor-transistor logic voltage gated 120V, 10A relay (OPTO22, Temecula, CA) to digitally engage the stimulation lamps (Figure 4A). Lamps consist of six-50 W halogen bulbs (Philips Amsterdam, The Netherlands) for a total energy delivery rate of 300 W. Thermal video was captured with an FM 320 focal plane array camera (ICI Beaumont, TX) with 320 × 240 resolution. Matlab code was written to view thermal video input, engage stimulation, and capture and save data. ADT and Quantification Stimulation lamps were positioned 4 inches above the surface of the burn and angled to face the center. Stimulation was applied for 6000 ms as per the results of phantom testing, with image capture beginning immediately after stimulation ended. Image reconstruction was performed using a gradient analysis technique. Each pixel of each frame of video was subtracted from each of the previous frame, producing the gradient of thermal change. These gradient frames were summed for a total of 5 seconds of video, 150 frames at 30 frames per second to produce a resultant image. This method is quantitatively described by Equation 1 and the unit is termed as thermal flux as it is a change in temperature as a function of time. ImageJ software (NIH, Bethesda, MD) was then used to quantify the signal intensity of each of the four burn zones and three interspaces as individual regions of interest from reconstructed images.  Laser Doppler Imaging LDI was performed with a Moor LDI-2 laser Doppler imager (Moor Instruments Ltd., Axminster, United Kingdom). Signal intensity of regions of interest's was computed for each of the four burn zones and three interspaces with the Moor LDI Image Analysis software, corresponding with the ADT analysis. Histological Examination Biopsies preserved in formalin were embedded in paraffin wax, sectioned at 6 µm on a Leica microtome (Solms, Germany) and adhered to Superfrost charged glass slides (ThermoFisher, Waltham, MA). Masson's trichrome staining was performed per standard protocol.20 Photomicrographs were captured at 5× magnification with an Axio Imager brightfield microscope (Zeiss, Jena, Germany). RESULTS Imaging Parameter Assessment Active dynamic thermographic imaging of the skin phantom calibrator revealed an increasing resolution of imaging depth with stimulation time (Figure 5). Stimulation between 500 and 5000 ms resulted in a nearly linear increase in depth resolution, while stimulation above 6000 ms was unable to resolve any further depth due to thermal saturation (Figure 6). A stimulation time of 6000 ms was therefore chosen as the optimal excitation parameter for this study. Figure 5. View largeDownload slide ADT imaging of a calibration skin phantom with representative stimulation of 2000 ms (A), 6000 ms (B), and 10,000 ms (C). Figure 5. View largeDownload slide ADT imaging of a calibration skin phantom with representative stimulation of 2000 ms (A), 6000 ms (B), and 10,000 ms (C). Figure 6. View largeDownload slide ADT calibrator imaging depth as a function of thermal stimulation. Figure 6. View largeDownload slide ADT calibrator imaging depth as a function of thermal stimulation. Direct Thermographic and Perfusion Analysis Direct analysis of thermographic and perfusion data for each burn duration (Figure 7) revealed an inverse trend between the two imaging techniques. In the superficial, 15-second burn (Figure 7A, B) LDI clearly depicts an increase in perfusion of the interspaces over the burn zones (P < .05), while ADT shows no difference, or trend between the two. Assessment of the intermediate, 30-second burn (Figure 7C, D) reveals a similar although minor difference between the interspaces and burn by both ADT and LDI (P < .05). In the case of the deep, 45-second burn (Figure 7E, F) ADT clearly depicts an increasing trend in thermal flux (P < .05), while LDI provides little information about the difference between the burn zone and interspace, and can no longer distinguish the two by hour 18. Figure 7. View largeDownload slide ADT flux thermal flux and LDI perfusion data over time for each of the 15-second (A, B), 30-second (C, D), and 45-second (E, F) burn duration groups. Statistical correlation assessed by Student's t-test, asterisk denotes P < .05. Figure 7. View largeDownload slide ADT flux thermal flux and LDI perfusion data over time for each of the 15-second (A, B), 30-second (C, D), and 45-second (E, F) burn duration groups. Statistical correlation assessed by Student's t-test, asterisk denotes P < .05. Zone of Stasis to Burn Comparison To further characterize the ability of each imaging system to distinguish zones of stasis from burned tissue, the differences between the interspaces and burns were quantified at every time point (Figure 8). Each interspace was compared with its adjacent burns and normalized to baseline skin to standardize units, and present both imaging systems data in terms of percentage of normal skin signal intensity. Figure 8A illustrates the differences ADT can detect between zones of stasis and adjacent burned tissue, which follows an increasing trend with severity of the burn. LDI (Figure 8B) contrarily depicts a large difference between the superficial, 15-second burn and interspaces, but not for those of higher severity. Figure 8. View largeDownload slide Difference in signal between interspaces and surrounding burns for ADT and LDI. Data are normalized to baseline skin to standardize units between imaging systems. Panels A and B contain all burn duration groups for both ADT and LDI without statistical assessment. Panels C and D address the difference in both ADT and LDI between intermediate and deep burns, and panels E and F address the difference between superficial and deep burns. Statistical correlation in panels C–F assessed by Student's t-test, asterisk denotes P < .05. Figure 8. View largeDownload slide Difference in signal between interspaces and surrounding burns for ADT and LDI. Data are normalized to baseline skin to standardize units between imaging systems. Panels A and B contain all burn duration groups for both ADT and LDI without statistical assessment. Panels C and D address the difference in both ADT and LDI between intermediate and deep burns, and panels E and F address the difference between superficial and deep burns. Statistical correlation in panels C–F assessed by Student's t-test, asterisk denotes P < .05. If the superficial burn is removed from this dataset (Figure 8C, D), it becomes clear that ADT can distinguish stasis zones from burn in both intermediate and deep burns, which LDI is incapable of doing. This difference is evident (P < .05) immediately after injury, and at nearly every assessment until hour 36. Likewise, if the intermediate, 30-second burn is removed from this same dataset (Figure 8E, F), it becomes apparent that while ADT is most effective at identifying zones of stasis adjacent to deep burns (P < .05) postinjury to hour 36, LDI is most effective with superficial burns (P < .05) by hour 12. Utility of Imaging for Identification of Burn Conversion To more clearly illustrate the differences in each imaging system for the characterization of irreversible burn progression, the data for each of the interspaces was grouped as converting or nonconverting, based on visual inspection at hour 36 (Figure 9). Twelve (67%) of interspaces were determined converted in the 15 second burn group, 35 (97%) in the 30 second group and 18 (100%) in the 45 second group. Perfusion imaging characterizes nonconverting from converting tissue (P < .05) immediately postinjury and consistently to hour 36, observing a linear increase in the difference in perfusion. Conversely, ADT directly identifies the trend of burn conversion (P < .05) by hour 12. Figure 9. View largeDownload slide Difference in signal between interspaces and surrounding burns for ADT and LDI, grouped as converting or nonconverting burns by 48 hours. Data are normalized to baseline skin to standardize units between imaging systems. Statistical correlation assessed by Student's t-test, asterisk denotes P < .05. Figure 9. View largeDownload slide Difference in signal between interspaces and surrounding burns for ADT and LDI, grouped as converting or nonconverting burns by 48 hours. Data are normalized to baseline skin to standardize units between imaging systems. Statistical correlation assessed by Student's t-test, asterisk denotes P < .05. Histologic Examination Conversion of the interspace tissue was confirmed by Masson's trichrome staining, which illustrates a progressing change in tissue architecture and dye affinity of the interspaces from postburn to hour 36 (Figure 10). Hallmarks of necrosis are apparent including complete denaturation of the epidermis and upper dermis as well as a progression of collagen denaturation into the dermis through disorganization and an exchange of dye affinity.21,22 Figure 10. View largeDownload slide Masson's trichrome histological assessment of interspaces at 36 hours postinjury for each of the burn severity groups, control and a full-thickness burn (15 second contact). Red bars illustrate the depth of collagen denaturation into the dermis for the 30- and 45-second contact groups. Scale bar 200 µm. Figure 10. View largeDownload slide Masson's trichrome histological assessment of interspaces at 36 hours postinjury for each of the burn severity groups, control and a full-thickness burn (15 second contact). Red bars illustrate the depth of collagen denaturation into the dermis for the 30- and 45-second contact groups. Scale bar 200 µm. DISCUSSION The current diagnosis of burn conversion is difficult and subjective. The advantage of a noncontact imaging system to identify this process is clear and could serve as an important tool for the burn surgeon. This study has assessed the utility of both ADT and LDI in the identification of burn conversion. Direct analysis of thermal flux and perfusion unit output of these systems has grossly identified a trend of differing utility. While ADT detects less of a difference between the stasis zone and the burn for less severe injuries, it is both useful and predictive for intermediate to deep injuries. By 12 hours postinjury, ADT can predict whether a stasis zone will convert or not. Conversely, while LDI can easily distinguish the zone of stasis from burned skin with the superficial injury, it is incapable of providing much information with intermediate to deep burns and interspaces. This trend is further characterized through the subsequent zone of stasis to burn conversion analysis. ADT is shown to identify an increasing difference between the interspace and burn zone with increasing injury severity, while LDI can only identify the difference with the superficial injury. When these data are finally broken into converting or nonconverting wounds these trends are clarified further. LDI clearly identifies surviving tissue with a trend of increasing difference between burned tissue and the zone of stasis, while ADT identifies with a linear trend, that which will convert to dead tissue. The potential utility of this device in the clinical environment is great. Not only could a patient's response to resuscitative therapy be characterized and optimized for the individual but also the conversion of already damaged tissue could be predicted, allowing for earlier surgical intervention. Several factors of burn-related morbidity are attributed to burn conversion including greater wound contracture,5,13 an increased likelihood of infection1,5 and worsened scarring and pigmentation outcomes,1,13 all of which, if diagnosed in a timely manner, could be significantly attenuated or prevented altogether. A second and very important conclusion of this study is that ADT alone is not the single solution to burn assessment. While we have demonstrated the ability of ADT to monitor and predict the structural changes of burn conversion, we have also demonstrated the ability of LDI to predict healing. It is important to highlight how each of these devices fell short when characterizing a specific category of burns and interspaces. For ADT it was superficial burns, while for LDI it was moderate and severe burns. It is known that the penetration depth of light into skin is limited, which is a shortcoming of all laser-based imaging applications,23 and explains why LDI was limited in distinguishing burns that extended below the superficial dermis. The inability of ADT to characterize shallow burns however may extend from current limitations in this novel technique and improve with further development. Thermal stimulation of the skin involves balancing the potential for under-stimulating and not visualizing any structure vs over-stimulating and causing a burn. Warm-up and cool-down periods of incandescent bulbs, such as halogen lamps also complicate the length of stimulation. The use of flash lamps in the future may provide a solution; however, work must be done to ensure safety. There are several benefits to the ADT system over conventional technologies. The cost of an imaging device can be relatively low and will continue decreasing with the development of thermal camera technologies. Imaging time is also much more rapid in ADT compared with LDI, a region requiring 5 minutes of scanning using LDI can be imaged using ADT in 10 seconds. Size and portability however are comparable in the two modalities. This study had several limitations. Those inherent to the comb-burn model include a generalized comparison to human burn wound healing that is imperfect, as the model utilizes a more homogenous injury than wound typically be seen in patients. Similarly, there is limited background knowledge of burn conversion in the murine model. In addition, the sample size of this study is small and the focus is on the lateral conversion of viable skin, not the vertical progression of already damaged tissue, which should be addressed in future studies. Finally, the gradient image reconstruction technique described herein has in our experience proved to be a robust and useful tool for dynamic image reconstruction. The ability to provide a visual map of burn severity and conversion potential to the clinician is an important aspect of burn imaging and a considerable challenge with emerging assessment techniques. Figure 11 illustrates the output of this technique, which can be portrayed like LDI in heat-map form, three-dimensional graph or black and white images. Figure 11. View largeDownload slide Representative photographs, laser Doppler scanning images, and active dynamic thermography gradient method reconstructed images for the 30-second burn, converting injury. Figure 11. View largeDownload slide Representative photographs, laser Doppler scanning images, and active dynamic thermography gradient method reconstructed images for the 30-second burn, converting injury. CONCLUSION This study has shown that ADT is capable of identifying the structural changes that represent wound conversion as early as 12 hours post-injury. In addition, further evidence of a potential synergistic relationship between structural and perfusion imaging is provided, which advocates for the further development of multi-parametric diagnostic devices for burns. ACKNOWLEDGMENTS The authors acknowledge Timothy R. Currie for mechanical engineering design assistance. REFERENCES 1. JW Shupp, TJ Nasabzadeh, DS Rosenthal, MH Jordan, P Fidler, JC Jeng A review of the local pathophysiologic bases of burn wound progression. J Burn Care Res  2010; 31: 849– 73. Google Scholar CrossRef Search ADS PubMed  2. DE Kim, TM Phillips, JC Jeng Microvascular assessment of burn depth conversion during varying resuscitation conditions. J Burn Care Rehabil  2001; 22: 406– 16. Google Scholar CrossRef Search ADS PubMed  3. 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TI - Active Dynamic Thermography is a Sensitive Method for Distinguishing Burn Wound Conversion
JF - Journal of Burn Care & Research
DO - 10.1097/BCR.0000000000000296
DA - 2016-11-01
UR - https://www.deepdyve.com/lp/oxford-university-press/active-dynamic-thermography-is-a-sensitive-method-for-distinguishing-bVCKzIBiCw
SP - e559
EP - e568
VL - 37
IS - 6
DP - DeepDyve
ER -