Fig 2 - available via license: Creative Commons Attribution-NonCommercial 4.0 International
Content may be subject to copyright.
UV Fluorescence Excitation Imaging: sample is excited at specific wavelengths (295 or 335 nm) while a UV sensitive camera images the emission at the corresponding fluorescence wavelengths (340 or 390 nm).
Source publication
Background and objective:
Molecules native to tissue that fluoresce upon light excitation can serve as reporters of cellular activity and protein structure. In skin, the fluorescence ascribed to tryptophan is a marker of cellular proliferation, whereas the fluorescence ascribed to cross-links of collagen is a structural marker. In this work, we in...
Context in source publication
Context 1
... recently developed an ultraviolet fluorescence excita- tion imaging (u-FEI) system that exploits the fluorescence of molecules native to skin [17]. Briefly, the system utilizes a Xenon arc lamp and a series of narrow-band radiation filters to illuminate the tissue at specific excitation wave- lengths, and a series of narrow-band collection filters and a UV-sensitive camera to capture images at specific emission wavelengths as illustrated in Figure 2. For this study, the u-FEI system was used to acquire images at excitation/ emission wavelengths of 295/340 nm and 335/390 nm. ...
Citations
... skin (i.e., baseline) (seeFigure 2). In contrast with Wang et al.,12 upon excitation at 295 nm, the fluorescence of cellular proliferation does not appear to delineate the margin of wounds at day 0 because the inner-part emission masks the margin emission. This dissimilarity is due to the ex vivo skin model lacking hemostasis and inflammation processes. ...
Background
Wound healing monitoring and timely decision‐making are critical for wound classification. Tryptophan (Tr) intrinsic fluorescence, detected at 295/340 nm, provides a noninvasive approach for wound assessment. Our previous work demonstrated that this autofluorescence is associated with keratinocytes in a highly proliferative state in vitro.
Objective
We investigated the correlation between Tr fluorescence and key wound healing parameters, including re‐epithelialization, fibrosis, neovascularization, and acute and chronic inflammation, using a rabbit model.
Methods
Seven rabbits underwent wound healing assessment over a 15‐day period. We employed histological analysis from central and marginal biopsies, and UV fluorescence imaging captured by a monochromatic near‐UV sensitive camera equipped with a passband optical filter (340 nm/12 nm). Excitation was achieved using a 295 nm LEDs ring lamp. Normalized fluorescence values were correlated with histological measurements using Pearson correlation.
Results
The UV fluorescence strongly exhibited a strong correlation with re‐epithelization (r = 0.8) at the wound edge, with peak intensity observed between the sixth and ninth days. Notably, wound‐healing dynamics differed between the wound center and edge, primarily attributed to variations in re‐epithelialization, neovascularization, and chronic inflammation.
Conclusion
Our findings highlight the presence of autofluorescence at 295/340 nm during wound healing, demonstrating a robust association with re‐epithelialization. This excitation/emission signal holds promise as a valuable noninvasive strategy for monitoring wound closure, re‐epithelialization, and other biological processes where Tr plays a pivotal role.
... Haemostasis, commences immediately after an injury and entails the formation of a blood clot to halt bleeding. The primary objective during human skin wound healing is the swift restoration of barrier function (Wang et al., 2016).Stages for wound healing start with phase 1 Hemostasis, phase 2 in ammatory, phase 3 Proleferative and nally phase 4, remodeling with scar formation (Negm, 2023). ...
... Many patients resort to traditional healers or homemade remedies, which may not always be effective and can cause complications due to poor judgment. Visual inspection remains the most basic and effective method in wound care, but it requires a skilled observer and the experience is subjective and may take years to accumulate (Wang et al., 2016). ...
Due to uncontrolled bleeding in victims and frequently delayed emergency response times to road accidents had frequently causes severe casualties. To solve this problem, the robotic arm used in this paper, based on machine learning, is programmed to monitor and react to bleeding in accident victims. A clotting agent is applied to the wounds by the robotic arm at the touch of a button, stopping the bleeding and possibly saving lives. The system's image processing and wound classification were done in a Python-based Jupyter environment. SolidWorks was used to design the robotic arm, which was programmed to respond to input from a Python model. The robotic arm's kinematics was tested in the Simulink environment, displaying the joints' successful operation. The robotic arm design was further analyzed in the Simcape environment, where the arm's trajectory was evaluated. The results showed that the robotic arm could effectively move toward the detected wound, following the training trajectory. Object tracking was successfully performed in Matlab under the Simcape environment, as evidenced by the alignment between the expected and actual trajectory line graphs. The study concludes that the machine learning-based robotic arm can accurately move to any desired position within its workspace, enabling the precise application of the clotting agent on the wound. This system holds significant potential for improving emergency response times and outcomes in road accidents.
... By backscattering configuration, we mean that luminescent light is to be observed in the same hemisphere as the one from which the excitation light arrives, which is being emitted backward. There are several important applications of spectrofluorometry techniques in a backscattering configuration [7][8][9][10][11][12][13][14]. In this configuration, light radiated by a fluorophore must travel back through the region of the sample that is absorbing the excitation light. ...
We propose and test a method for determining a fluorescent medium’s absorption or extinction index while it is fluorescing. The method uses an optical arrangement that records changes in fluorescence intensity at a fixed viewing angle as a function of the angle of incidence of an excitation light beam. We tested the proposed method on polymeric films doped with Rhodamine 6G (R6G). We found a strong anisotropy in the fluorescence emission and, thus, limited the method to TE-polarized excitation light. The method proposed is model dependent, and we provide a simplified model for its use in this work. We report the extinction index of the fluorescing samples at a selected wavelength within the emission band of the fluorophore R6G. We found that the extinction index at the emission wavelengths in our samples is appreciably larger than the extinction index at the excitation wavelength, which is the opposite of what one might expect from measuring the absorption spectrum of the medium with a spectrofluorometer. The proposed method could be applied to fluorescent media with additional absorption other than by the fluorophore.
... Identifying the neo-epithelial/granulation tissue border from wound images can be challenging and delineations of said borders may vary across experts. More accurate analysis could be done by utilizing other types of image analysis (e.g., fluorescence excitation images and histology images), techniques that have inherent disadvantages such as the need for in vivo imaging (for fluorescently labeled markers) or terminal experiments (histological images) precluding temporal analysis [34,35]. The pixel numbers of the wound areas was obtained using the measure function in ImageJ. ...
Evaluating and tracking wound size is a fundamental metric for the wound assessment process. Good location and size estimates can enable proper diagnosis and effective treatment. Traditionally, laboratory wound healing studies include a collection of images at uniform time intervals exhibiting the wounded area and the healing process in the test animal, often a mouse. These images are then manually observed to determine key metrics —such as wound size progress— relevant to the study. However, this task is a time-consuming and laborious process. In addition, defining the wound edge could be subjective and can vary from one individual to another even among experts. Furthermore, as our understanding of the healing process grows, so does our need to efficiently and accurately track these key factors for high throughput (e.g., over large-scale and long-term experiments). Thus, in this study, we develop a deep learning-based image analysis pipeline that aims to intake non-uniform wound images and extract relevant information such as the location of interest, wound only image crops, and wound periphery size over-time metrics. In particular, our work focuses on images of wounded laboratory mice that are used widely for translationally relevant wound studies and leverages a commonly used ring-shaped splint present in most images to predict wound size. We apply the method to a dataset that was never meant to be quantified and, thus, presents many visual challenges. Additionally, the data set was not meant for training deep learning models and so is relatively small in size with only 256 images. We compare results to that of expert measurements and demonstrate preservation of information relevant to predicting wound closure despite variability from machine-to-expert and even expert-to-expert. The proposed system resulted in high fidelity results on unseen data with minimal human intervention. Furthermore, the pipeline estimates acceptable wound sizes when less than 50% of the images are missing reference objects.
... For example, micron-scale features (such as grooves, pits or posts) can by fabricated by stereo-lithography techniques on rigid substrates, to study substrate topography effects on different cellular behaviours including migration [22][23][24][25][26]. Among the different material fabrication strategy, electrospinning could be considered as one of the most facile approaches which produce fibre structures mimicking the physical building blocks of fibrillar ECMs [27][28][29][30][31][32][33][34]. As linear tracks and straight fibre patterns have provided the foundation to recapitulate fibrillar morphology [35][36][37], it is of interest to evaluate how the features at a higher scale of fibre architecture, such as waviness, loops, and cross-junction grid patterns commonly found in ECM, could influence the cell migration dynamics. ...
Cell migration plays an important role in physiological and pathological processes where the fibrillar morphology of extracellular matrices (ECM) could regulate the migration dynamics. To mimic the morphological characteristics of fibrillar matrix structures, low-voltage continuous electrospinning was adapted to construct straight, wavy, looped and gridded fibre patterns made of polystyrene (of fibre diameter ca. 3 μm). Cells were free to explore their different shapes in response to the directly-adhered fibre, as well as to the neighbouring patterns. For all the patterns studied, analysing cellular migration dynamics of MDA-MB-231 (a highly migratory breast cancer cell line) demonstrated two interesting findings: first, although cells dynamically adjust their shapes and migration trajectories in response to different fibrillar environments, their average step speed is minimally affected by the fibre global pattern; secondly, a switch in behaviour was observed when the pattern features approach the upper limit of the cell body’s minor axis, reflecting that cells’ ability to divert from an existing fibre track is limited by the size along the cell body’s minor axis. It is therefore concluded that the upper limit of cell body’s minor axis might act as a guide for the design of microfibre patterns for different purposes of cell migration.
... researchers employ various invasive (histology/scanning electron microscopy (SEM)) and non-invasive imaging methods (ultrasound imaging, magnetic resonance imaging, optical imaging, photoacoustic imaging, positron emission tomography (PET), and single-photon emission computed tomography (SPECT)) with or without fluorescent probes to monitor the scaffold's activity during the in vivo tissue engineering application [24][25][26][27][28]. Among them, optical imaging is highly sensitive, safe (non-radioactive), low cost, easy to use, rapid, long-term, non-ionizing, continuous, and contact-free examination of in vitro and in vivo tissues [29][30][31]. However, an accurate result from the optical imaging technique is possible only in the tissue sample with planar surface morphology. ...
Regeneration of damaged tissues or organs is one of the significant challenges in tissue engineering and regenerative medicine. Many researchers have fabricated various scaffolds to accelerate the tissue regeneration process. However, most of the scaffolds are limited in clinical trials due to scaffold inconsistency, non-biodegradability, and lack of non-invasive techniques to monitor tissue regeneration after implantation. Recently, carbon dots (CDs) mediated fluorescent scaffolds are widely explored for the application of image-guided tissue engineering due to their controlled architecture, light-emitting ability, higher chemical and photostability, excellent biocompatibility, and biodegradability. In this review, we provide an overview of the recent advancement of CDs in terms of their different synthesis methods, tunable physicochemical, mechanical, and optical properties, and their application in tissue engineering. Finally, this review concludes the further research directions that can be explored to apply CDs in tissue engineering.
... Identifying the neo-epithelial/granulation 165 tissue border from wound images can be challenging and delineations of said borders 166 may vary across experts. More accurate analysis could be done by utilizing other 167 types of image analysis (e.g., fluorescence excitation images and histology images), 168 techniques that have inherent disadvantages such as the need for in vivo imaging (for 169 fluorescently labeled markers) or terminal experiments (histological images) precluding 170 temporal analysis [31,32]. The pixel numbers of the wound areas was obtained using the 171 measure function in ImageJ. ...
Evaluating and tracking wound size is a fundamental metric for the wound assessment process. Good location and size estimates can enable proper diagnosis and effective treatment. Traditionally, laboratory wound healing studies include a collection of images at uniform time intervals exhibiting the wounded area and the healing process in the test animal, often a mouse. These images are then manually observed to determine key metrics —such as wound size progress— relevant to the study. However, this task is a time-consuming and laborious process. In addition, defining the wound edge could be subjective and can vary from one individual to another even among experts. Furthermore, as our understanding of the healing process grows, so does our need to efficiently and accurately track these key factors for high throughput (e.g., over large-scale and long-term experiments). Thus, in this study, we develop a deep learning-based image analysis pipeline that aims to intake non-uniform wound images and extract relevant information such as the location of interest, wound only image crops, and wound periphery size over-time metrics. Our work focuses on images of wounded laboratory mice that are used widely for translationally relevant wound studies. We compare results to that of expert measurements and demonstrate preservation of information relevant to predicting wound closure despite variability from machine-to-expert and even expert-to-expert. The proposed system resulted in high fidelity results on unseen data with minimal human intervention.
Author summary
Knowledge of the wound size changes over-time allows us to observe important insights such as rate of closure, time to closure, and expansion events, which are key indicators for predicting healing status. To better perform wound measurements it is essential to utilize a technique that returns accurate and consistent results every time. Over the last years, collecting wound images is becoming easier and more popular as digital cameras and smartphones are more accessible. Commonly, scientists/clinicians trace the wound in these images manually to observe changes in the wound, which is normally a slow and labor-intensive process and also requires a trained eye. The clinical goal is to more efficiently and effectively treat wounds by employing easy to use and precise wound measurement techniques. Therefore, the objective should be devising automatic and precise wound measurement tools to be used for wound assessment. To this end, we leveraged a combination of various state-of-the-art computer vision and machine learning-based methods for developing a versatile and automatic wound assessment tool. We applied this tool to analyze the images of wound inflicted lab mice and showed that our developed tool automated the overall wound measurement process, therefore, resulting in high fidelity results without significant human intervention. Furthermore, we compared results to two expert measurements. We found variability in measurement even across experts further validating the need for a consistent approach. However, qualitative behavior, which is most important for predicting wound closure, is preserved.
... These conditions suggest that the quantification of vitamin A and cell proliferation may be used as fibrosis markers. Vitamin A and the amino acid tryptophan have already demonstrated utility as good fluorescence probes of fat content at the 320/420-nm band and cellular proliferation at the fluorescence 295/345-nm band, respectively [20][21][22][23]. Therefore, a non-subjective, minimally-invasive, and quantifying simultaneous technique of different endogenous fluorophores may provide information on the state and functionality of the liver [24]. ...
Build-up of extracellular matrix in liver fibrosis results in changes on endogenous molecules expression that may be studied through the fluorescence characterization of ex vivo liver samples. To the best of our knowledge, no investigations have provided in-depth evidence and discussion on the changes of the endogenous fluorescence in ex vivo tissue due to the effects of the preservation media. In this work, we contrast and analyze the endogenous fluorescence from tryptophan, vitamin A, hydroxyproline and elastin cross-links potential biomarkers of the liver fibrosis, in in vivo measurements and liver samples preserved on formaldehyde, and two standard preservation media. As it is known, chemical changes in tissue, caused by formaldehyde fixation, alter the endogenous fluorescence spectra. We propose the use of phosphate-buffered saline (PBS), and Iscove’s Modified Dulbecco’s Medium (IMDM) to elude the fluorescence changes. PBS and IMDM showed to maintain the endogenous fluorescence characteristics similar to in vivo conditions. The results of this work point the way for a more reliable assessment of endogenous fluorescence in ex vivo hepatic studies.
... 82,83 Fluorescence imaging method has been applied to quantify wound size, closure extents, and gaps based on dermal fluorescence of pepsin-digestible collagen cross-links in an ex vivo human skin wound healing study. 84 For exogenous fluorescence imaging process, the most widely used fluorescent dye is indocyanine green (ICG), which has been approved by the FDA for intravenous injection for imaging. 85 Through intravenous injection of ICG, fluorescence imaging can be used to reveal wound depth and vascularization around the wound. ...
Significance: Chronic wounds affect millions of patients worldwide, placing a huge burden on health care resources. Although significant progress has been made in the development of wound treatments, very few advances have been made in wound diagnosis.
Recent Advances: Standard imaging methods like computed tomography, single-photon emission computed tomography, magnetic resonance imaging, terahertz imaging, and ultrasound imaging have been widely employed in wound diagnostics. A number of noninvasive optical imaging modalities like optical coherence tomography, near-infrared spectroscopy, laser Doppler imaging, spatial frequency domain imaging, digital camera imaging, and thermal and fluorescence imaging have emerged over the years.
Critical Issues: While standard diagnostic wound imaging modalities provide valuable information, they cannot account for dynamic changes in the wound environment. In addition, they lack the capability to predict the healing outcome. Thus, there remains a pressing need for more efficient methods that can not only indicate the current state of the wound but also help determine whether the wound is on track to heal normally.
Future Directions: Many imaging probes have been fabricated and shown to provide real-time assessment of tissue microenvironment and inflammatory responses in vivo. These probes have been demonstrated to noninvasively detect various changes in the wound environment, which include tissue pH, reactive oxygen species, fibrin deposition, matrix metalloproteinase production, and macrophage accumulation. This review summarizes the creation of these probes and their potential implications in wound monitoring.
... Threedimensional (3D) organ culture can be used to investigate bacterial infections based on in vitro culture of skin explants. These tissues can be acquired from surgical procedures or post slaughter Smijs et al., 2007;Steinstraesser et al., 2010;Sidgwick et al., 2016;Wang et al., 2016). Since the multicellular interaction and tissue cytoarchitecture are preserved, 3D models are considered to be phenotypically and histologically similar to the organs and tissues in vivo and their importance in the development of relevant models have been widely recognized Edmondson et al., 2014). ...
