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Keratins are one of the main fluorophores of the skin. Keratinization disorders can lead to alterations in the optical properties of the skin. We set out to investigate a rare form of keratinopathic ichthyosis caused by KRT1 mutation with two different optical imaging methods. We used a newly developed light emitting diode (LED) based device to analyze autofluorescence signal at 405 nm excitation and diffuse reflectance at 526 nm in vivo. Mean autofluorescence intensity of the hyperkeratotic palmar skin was markedly higher in comparison to the healthy control (162.35 vs. 51.14). To further assess the skin status, we examined samples from affected skin areas ex vivo by nonlinear optical microscopy. Two-photon excited fluorescence and second-harmonic generation can visualize epidermal keratin and dermal collagen, respectively. We were able to visualize the structure of the epidermis and other skin changes caused by abnormal keratin formation. Taken together, we were able to show that such imaging modalities are useful for the diagnosis and follow-up of keratinopathic diseases.
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Hiperqueratosis Epidermolítica , Queratinas , Preescolar , Humanos , Masculino , Microscopía Óptica no Lineal , Imagen Óptica , PielRESUMEN
The microbial colony growth is driven by the activity of the cells located on the edges of the colony. However, this process is not visible unless specific staining or cross-sectioning of the colony is done. Speckle imaging technology is a non-invasive method that allows visualization of the zones of increased microbial activity within the colony. In this study, the laser speckle imaging technique was used to record the growth of the microbial colonies. This method was tested on three different microorganisms: Vibrio natriegens, Escherichia coli, and Staphylococcus aureus. The results showed that the speckle analysis system is not only able to record the growth of the microbial colony but also to visualize the microbial growth activity in different parts of the colony. The developed speckle imaging technique visualizes the zone of "the highest microbial activity" migrating from the center to the periphery of the colony. The results confirm the accuracy of the previous models of colony growth and provide algorithms for analysis of microbial activity within the colony.
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Diagnóstico por Imagen , Escherichia coli , Recuento de Colonia MicrobianaRESUMEN
Rapid identification of effective antibiotic treatment is crucial for increasing patient survival and preventing the formation of new antibiotic-resistant bacteria due to preventative antibiotic use. Currently utilized "gold standard" methods require 16-24 h to determine the most appropriate antibiotic for the patient's treatment. The proposed technique of laser speckle imaging with subpixel correlation analysis allows for identifying dynamics and changes in the zone of inhibition, which are impossible to observe with classical methods. Furthermore, it obtains the resulting zone of inhibition diameter earlier than the disk diffusion method which is recommended by the European Committee on Antimicrobial Susceptibility Testing (EUCAST). These results could improve mathematical models of changes in the diameter of the zone of inhibition around the disc containing the antimicrobial agent, thereby speeding up and facilitating epidemiological analysis.
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Prior research has indicated the feasibility of assessing growth-associated activity in bacterial colonies through the application of laser speckle imaging techniques. A subpixel correlation method was employed to identify variations in sequential laser speckle images, thereby facilitating the visualization of specific zones indicative of microbial growth within the colony. Such differentiation between active (growing) and inactive (non-growing) bacterial colonies holds considerable implications for medical applications, like bacterial response to certain drugs or antibiotics. The present study substantiates the capability of laser speckle imaging to categorize bacterial colonies as growing or non-growing, a parameter which nonvisible in colonies when observed under white light illumination.
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[This corrects the article DOI: 10.3389/fmicb.2023.1221134.].
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Neurofibromatosis type 1 (NF1) is a rare disease, affecting around 1 in 3500 individuals in the general population. The rarity of the disease contributes to the scarcity of the available diagnostic and therapeutic approaches. Multispectral imaging is a non-invasive imaging method that shows promise in the diagnosis of various skin diseases. The device utilized for the present study consisted of four sets of narrow-band LEDs, including 526 nm, 663 nm, and 964 nm for diffuse reflectance imaging and 405 nm LEDs, filtered through a 515 nm long-pass filter, for autofluorescence imaging. RGB images were captured using a CMOS camera inside of the device. This paper presents the results of this multispectral skin imaging approach to distinguish the lesions in patients with NF1 from other more common benign skin lesions. The results show that the method provides a potential novel approach to distinguish NF1 lesions from other benign skin lesions.
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Fabry disease (FD) is a multisystemic X-linked lysosomal storage disease that presents with angiokeratomas (AKs). Our objective was to investigate the clinical and morphologic features of AKs and to present two experimental techniques, multispectral imaging (MSI) and non-linear microscopy (NLM). A thorough dermatological examination was carried out in our 26 FD patients and dermoscopic images (n = 136) were evaluated for specific structures. MSI was used for the evaluation of AKs in seven patients. NLM was carried out to obtain histology samples of two AKs and two hemangiomas. Although AKs were the most common manifestation, the majority of patients presented an atypical distribution and appearance, which could cause a diagnostic challenge. Dermoscopy revealed lacunae (65%) and dotted vessels (56%) as the most common structures, with a whitish veil present in only 25%. Autofluorescence (405 nm) and diffuse reflectance (526 nm) images showed the underlying vasculature more prominently compared to dermoscopy. Using NLM, AKs and hemangiomas could be distinguished based on morphologic features. The clinical heterogeneity of FD can result in a diagnostic delay. Although AKs are often the first sign of FD, their presentation is diverse. A thorough dermatological examination and the evaluation of other cutaneous signs are essential for the early diagnosis of FD.
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Melanoma is the most aggressive form of skin cancer that is known for its metastatic potential and has an increasing incidence worldwide. Breslow thickness, which determines the staging and surgical margin of the tumor, is unavailable at initial diagnosis. Novel imaging techniques for assessing Breslow thickness lack comparative data. This study evaluates optically guided high-frequency ultrasound (OG-HFUS) and multispectral imaging (MSI) for preoperative estimation of Breslow thickness and staging. We enrolled 101 patients with histologically confirmed primary melanoma and categorized them based on tumor thickness. Optically guided 33 MHz HFUS and MSI were utilized for the assessment. Our MSI-based algorithm categorized melanomas into three subgroups with a sensitivity of 62.6%, specificity of 81.3%, and fair agreement (κ = 0.440, CI: 0.298-0.583). In contrast, OG-HFUS demonstrated a sensitivity of 91.8%, specificity of 96.0%, and almost perfect agreement (κ = 0.858, CI: 0.763-0.952). OG-HFUS performed better than MSI in estimating Breslow thickness, emphasizing its potential as a valuable tool for melanoma diagnosis and patient management. OG-HFUS holds promise for enhancing preoperative staging and treatment decision-making in melanoma.
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In this work, we propose to use an artificial neural network to classify limited data of clinical multispectral and autofluorescence images of skin lesions. Although the amount of data is limited, the deep convolutional neural network classification of skin lesions using a multi-modal image set is studied and proposed for the first time. The unique dataset consists of spectral reflectance images acquired under 526 nm, 663 nm, 964 nm, and autofluorescence images under 405 nm LED excitation. The augmentation algorithm was applied for multi-modal clinical images of different skin lesion groups to expand the training datasets. It was concluded from saliency maps that the classification performed by the convolutional neural network is based on the distribution of the major skin chromophores and endogenous fluorophores. The resulting classification confusion matrices, as well as the performance of trained neural networks, have been investigated and discussed.
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In this study, an optical contactless laser speckle imaging technique for the early identification of bacterial colony-forming units was tested. The aim of this work is to compare the laser speckle imaging method for the early assessment of microbial activity with standard visual inspection under white light illumination. In presented research, the growth of Vibrio natriegens bacterial colonies on the solid medium was observed and analyzed. Both - visual examination under white light illumination and laser speckle correlation analysis were performed. Based on various experiments and comparisons with the theoretical Gompertz model, colony radius growth curves were obtained. It was shown that the Gompertz model can be used to describe both types of analysis. A comparison of the two methods shows that laser speckle contrast imaging, combined with signal processing, can detect colony growth earlier than standard CFU counting method under white light illumination.
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Melanoma is a melanocytic tumor that is responsible for the most skin cancer-related deaths. By contrast, seborrheic keratosis (SK) is a very common benign lesion with a clinical picture that may resemble melanoma. We used a multispectral imaging device to distinguish these two entities, with the use of autofluorescence imaging with 405 nm and diffuse reflectance imaging with 525 and 660 narrow-band LED illumination. We analyzed intensity descriptors of the acquired images. These included ratios of intensity values of different channels, standard deviation and minimum/maximum values of intensity of the lesions. The pattern of the lesions was also assessed with the use of particle analysis. We found significantly higher intensity values in SKs compared with melanoma, especially with the use of the autofluorescence channel. Moreover, we found a significantly higher number of particles with high fluorescence in SKs. We created a parameter, the SK index, using these values to differentiate melanoma from SK with a sensitivity of 91.9% and specificity of 57.0%. In conclusion, this imaging technique is potentially applicable to distinguish melanoma from SK based on the analysis of various quantitative parameters. For this application, multispectral imaging could be used as a screening tool by general physicians and non-experts in the everyday practice.
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Pseudoxanthoma elasticum (PXE) is a rare multisystemic autosomal recessive connective tissue disease. In most cases, skin manifestations of PXE are the first to develop, followed later by severe ocular and cardiovascular complications. In our present study, in addition to dermoscopy, we introduced novel techniques, autofluorescence (AF) and diffuse reflectance (DR) imaging for the assessment of affected skin sites of five PXE patients. PXE-affected skin areas in most skin sites showed a previously observed pattern upon dermoscopic examination. With the novel imaging, PXE-affected skin lesions displayed high AF intensity. During our measurements, significantly higher mean, minimum and maximum AF intensity values were found in areas of PXE-affected skin when compared to uninvolved skin. Conversely, images acquired with the use of 660 and 940 nm illumination showed no mentionable difference. Our results demonstrate that AF imaging may be used in the in vivo diagnostics and quantification of the severity of the skin lesions of PXE patients. In addition, it is a safe, fast and cost-effective diagnostic method. AF imaging may be also used to objectively monitor the efficacy of the possible novel therapeutic approaches of PXE in the future.
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Breslow thickness is a major prognostic factor for melanoma. It is based on histopathological evaluation, and thus it is not available to aid clinical decision making at the time of the initial melanoma diagnosis. In this work, we assessed the efficacy of multispectral imaging (MSI) to predict Breslow thickness and developed a classification algorithm to determine optimal safety margins of the melanoma excision. First, we excluded nevi from the analysis with a novel quantitative parameter. Parameter s' could differentiate nevi from melanomas with a sensitivity of 89.60% and specificity of 88.11%. Following this step, we have categorized melanomas into three different subgroups based on Breslow thickness (≤1 mm, 1-2 mm and >2 mm) with a sensitivity of 78.00% and specificity of 89.00% and a substantial agreement (κ = 0.67; 95% CI, 0.58-0.76). We compared our results to the performance of dermatologists and dermatology residents who assessed dermoscopic and clinical images of these melanomas, and reached a sensitivity of 60.38% and specificity of 80.86% with a moderate agreement (κ = 0.41; 95% CI, 0.39-0.43). Based on our findings, this novel method may help predict the appropriate safety margins for curative melanoma excision.
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A clinical trial on the autofluorescence imaging of skin lesions comprising 16 dermatologically confirmed pigmented nevi, 15 seborrheic keratosis, 2 dysplastic nevi, histologically confirmed 17 basal cell carcinomas and 1 melanoma was performed. The autofluorescence spatial properties of the skin lesions were acquired by smartphone RGB camera under 405 nm LED excitation. The diagnostic criterion is based on the calculation of the mean autofluorescence intensity of the examined lesion in the spectral range of 515 nm-700 nm. The proposed methodology is able to differentiate seborrheic keratosis from basal cell carcinoma, pigmented nevi and melanoma. The sensitivity and specificity of the proposed method was estimated as being close to 100%. The proposed methodology and potential clinical applications are discussed in this article.
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The feasibility of smartphones for in vivo skin autofluorescence imaging has been investigated. Filtered autofluorescence images from the same tissue area were periodically captured by a smartphone RGB camera with subsequent detection of fluorescence intensity decreasing at each image pixel for further imaging the planar distribution of those values. The proposed methodology was tested clinically with 13 basal cell carcinoma and 1 atypical nevus. Several clinical cases and potential future applications of the smartphone-based technique are discussed.