Skin Lesion Characteristics Research Articles

Characterisation, prevalence and severity of skin lesions caused by ophidiomycosis in a population of wild snakes

Ophidiomycosis is an emerging infectious disease affecting wild snakes in the Northern Hemisphere. Recently confirmed in Great Britain, the prevalence, severity and significance of ophidiomycosis has yet to be characterised in free-living snakes at a population level in Europe. Therefore, a population of barred grass snakes (Natrix helvetica) in eastern England was monitored for three seasons (May 2019 to October 2021), to investigate the prevalence (25.5%; 191/750 snakes) and severity of skin lesions and their aetiology. The most frequently observed skin lesion characteristics were changes in scale colour, crusting, and scale margin erosion. The majority of such lesions (96.9%; 185/191 snakes) was observed on the ventral surface along the length of the body. The severity of skin lesions was considered mild in more than half of the cases (53.1%; 98/191 snakes). Predominantly, skin lesions were observed in adult snakes (72.8%; 139/191 snakes). Combined histological examinations and qPCR tests of skin lesions from N. helvetica sloughs and/or carcasses confirmed a diagnosis of ophidiomycosis. Further targeted surveillance, supported by molecular and histological examinations to confirm skin lesion aetiology, is required to determine the extent to which our findings reflect the occurrence of ophidiomycosis in populations within wider landscapes.

Transformer guided self-adaptive network for multi-scale skin lesion image segmentation

BackgroundIn recent years, skin lesion has become a major public health concern, and the diagnosis and management of skin lesions depend heavily on the correct segmentation of the lesions. Traditional convolutional neural networks (CNNs) have demonstrated promising results in skin lesion segmentation, but they are limited in their ability to capture distant connections and intricate features. In addition, current medical image segmentation algorithms rarely consider the distribution of different categories in different regions of the image and do not consider the spatial relationship between pixels. ObjectivesThis study proposes a self-adaptive position-aware skin lesion segmentation model SapFormer to capture global context and fine-grained detail, better capture spatial relationships, and adapt to different positional characteristics. The SapFormer is a multi-scale dynamic position-aware structure designed to provide a more flexible representation of the relationships between skin lesion characteristics and lesion distribution. Additionally, it increases skin lesion segmentation accuracy and decreases incorrect segmentation of non-lesion areas. InnovationsSapFormer designs multiple hybrid transformers for multi-scale feature encoding of skin images and multi-scale positional feature sensing of the encoded features using a transformer decoder to obtain fine-grained features of the lesion area and optimize the regional feature distribution. The self-adaptive feature framework, built upon the transformer decoder module, dynamically and automatically generates parameterizations with learnable properties at different positions. These parameterizations are derived from the multi-scale encoding characteristics of the input image. Simultaneously, this paper utilizes the cross-attention network to optimize the features of the current region according to the features of other regions, aiming to increase skin lesion segmentation accuracy. Main resultsThe ISIC-2016, ISIC-2017, and ISIC-2018 datasets for skin lesions are used as the basis for the experiment. On these datasets, the proposed model has accuracy values of 97.9 %, 94.3 %, and 95.7 %, respectively. The proposed model's IOU values are, in order, 93.2 %, 86.4 %, and 89.4 %. The proposed model's DSC values are 96.4 %, 92.6 %, and 94.3 %, respectively. All three metrics surpass the performance of the majority of state-of-the-art (SOTA) models. SapFormer's metrics on these datasets demonstrate that it can precisely segment skin lesions. Notably, our approach exhibits remarkable noise resistance in non-lesion areas, while simultaneously conducting finer-grained regional feature extraction on the skin lesion image. ConclusionsIn conclusion, the integration of a transformer-guided position-aware network into semantic skin lesion segmentation results in a notable performance boost. The ability of our proposed network to capture spatial relationships and fine-grained details proves beneficial for effective skin lesion segmentation. By enhancing lesion localization, feature extraction, quantitative analysis, and classification accuracy, the proposed segmentation model improves the diagnostic efficiency of skin lesion analysis on dermoscopic images. It assists dermatologists in making more accurate and efficient diagnoses, ultimately leading to better patient care and outcomes. This research paves the way for advances in diagnosing and treating skin lesions, promoting better understanding and decision-making in the clinical setting.

Multispectral Imaging for Skin Diseases Assessment-State of the Art and Perspectives.

Skin optical inspection is an imperative procedure for a suspicious dermal lesion since very early skin cancer detection can guarantee total recovery. Dermoscopy, confocal laser scanning microscopy, optical coherence tomography, multispectral imaging, multiphoton laser imaging, and 3D topography are the most outstanding optical techniques implemented for skin examination. The accuracy of dermatological diagnoses attained by each of those methods is still debatable, and only dermoscopy is frequently used by all dermatologists. Therefore, a comprehensive method for skin analysis has not yet been established. Multispectral imaging (MSI) is based on light-tissue interaction properties due to radiation wavelength variation. An MSI device collects the reflected radiation after illumination of the lesion with light of different wavelengths and provides a set of spectral images. The concentration maps of the main light-absorbing molecules in the skin, the chromophores, can be retrieved using the intensity values from those images, sometimes even for deeper-located tissues, due to interaction with near-infrared light. Recent studies have shown that portable and cost-efficient MSI systems can be used for extracting skin lesion characteristics useful for early melanoma diagnoses. This review aims to describe the efforts that have been made to develop MSI systems for skin lesions evaluation in the last decade. We examined the hardware characteristics of the produced devices and identified the typical structure of an MSI device for dermatology. The analyzed prototypes showed the possibility of improving the specificity of classification between the melanoma and benign nevi. Currently, however, they are rather adjuvants tools for skin lesion assessment, and efforts are needed towards a fully fledged diagnostic MSI device.

Automatic skin lesion segmentation based on FC-DPN

Automatic skin lesion segmentation in dermoscopy images is challenging due to the diversity of skin lesion characteristics, low contrast between normal skin and lesions, and the existence of many artefacts in the images. To meet these challenges, we propose a novel segmentation topology called FC-DPN, which is built upon a fully convolutional network (FCN) and dual path network (DPN). The DPN inherits the advantages of residual and densely connected paths, enabling effective feature re-usage and re-exploitation. We replace dense blocks in fully convolutional DenseNets (FC-DenseNets) with two kinds of sub-DPN blocks, namely, sub-DPN projection blocks and sub-DPN processing blocks. This framework enables FC-DPN to acquire more representative and discriminative features for more accurate segmentation. Many images in the original ISBI 2017 Skin Lesion Challenge test dataset are given the incorrect or inaccurate ground truths, and these ground truths have been revised. The revised test dataset is called the modified ISBI 2017 Skin Lesion Challenge test dataset. The proposed method achieves an average Dice coefficient of 88.13% and a Jaccard index of 80.02% on the modified ISBI 2017 Skin Lesion Challenge test dataset and 90.26% and 83.51%, respectively, on the PH2 dataset. Extensive experimental results on the two datasets demonstrate that the proposed method exhibits better performance than FC-DenseNets and other well-established segmentation algorithms.

Irritant and Allergic Contact Dermatitis – Skin Lesion Characteristics

SUMMARY – Contact skin lesions may be the consequences of contact with various irritants or allergens, or due to other factors (e.g., UV radiation, microbials), intrinsic factors (e.g., in autoimmune responses), or even their combination. There are many substances related to irritant contact dermatitis (CD), causing irritant or toxic effects, e.g., chemical and physical agents, plants, phototoxic agents, airborne irritants, etc. Impaired barrier function (e.g., aberrancies in epidermal pH buffering capabilities) also participates by promoting bacterial biofilms and creating an environment favoring sensitization. Development of allergic CD skin lesions includes complex immune pathways and inflammatory mediators, influenced by both genetic (predominantly filaggrin mutations) and environmental triggers. In the pathogenesis of allergic CD, antimicrobial peptides play a prominent role; they are produced by various skin cells (e.g., keratinocytes, sebocytes) and move to inflamed lesions during an inflammation process. Also, in allergic CD skin lesions, the skin shows different types of immune responses to individual allergens, although clinical manifestations do not depend on the causative allergen type, e.g., nickel stimulates immune activation primarily of the Th1/Th17 and Th22 components. Also important are alarmins, proteases, immunoproteomes, lipids, natural moisturizing factors, tight junctions, smoking, etc. We expect that future perspectives may reveal new pathogenetic factors and scientific data important for the workup and treatment of patients with CD.

Professor CHEN Xiuhua's experience in the treatment of atopic dermatitis

Professor CHEN Xiuhua's clinical experiences were introduced in the intervention on atopic dermatitis with external therapies of TCM acupuncture. On the basis of the theory as cultivating the earth and clearing the heart from professor CHEN Dacan and in terms of the disease stages and skin lesion characteristics, as well as in consideration of syndrome differen-tiation, the acupoints for strengthening the spleen and clearing heart fire are selected, such as Zhongwan (CV 12), Daheng (SP 15), Shuifen (CV 9), Tianshu (ST 25), Neiguan (PC 6) and Quchi (LI 11). For the repair of skin lesion, the integration of Chinese and western medicine is used, with the internal application and external use of Chinese herbal medicines involved. The topical ointments are selected rationally. The self-blood therapy is used with acupuncture, bleeding therapy and acupoint injection applied in combination on the basis of the theory of TCM zangfu organs and modern immunological mechanism, which stimulates the nonspecific immune response in the body and strengthens acupoint stimulus effects. Medical thread therapy of Guangxi Zhuang medicine is used in moxibustion for skin damage, which effectively stops itching and promotes wound healing and skin repair.

Decoction of Dictamnus Dasycarpus Turcz. Root Bark Ameliorates Skin Lesions and Inhibits Inflammatory Reactions in Mice with Contact Dermatitis.

Background:The root bark of Dictamnus dasycarpus Turcz. (Dictamni Radicis Cortex) has been widely used to treat skin diseases in Korea, and its anti-inflammatory efficacies were recently reported.Objective:The paper aims to investigate the inhibitory effects of decoction of Dictamni Radicis Cortex (DDRC) in mice with contact dermatitis (CD).Materials and Methods:We investigated the effects of DDRC on skin lesion characteristics such as crust, scales, incrustation and petechiae, the erythema and melanin indexes, skin thickness, histopathologic changes, and cytokine production in 1-fluoro-2,4-dinitrofluorobenzene (DNFB)-induced CD mice.Results:Topical application of DDRC ameliorated crust, scales, incrustation, and induced by DNFB. In addition, DDRC lowered the erythema index significantly (P < 0.05). DDRC effectively inhibited enlargement of skin thickness (P < 0.05). Histopathologic observation showed that DDRC inhibited epidermal hyperplasia, hyperkeratosis, and spongiotic changes. Finally, DDRC decreased production levels of IFN-γ, TNF-α and IL-6 induced by repeated application of DNFB (P < 0.05).Conclusion:These data suggest that DDRC can be used in the treatment of inflammatory skin diseases including CD. Moreover, these results are closely related to the decreasing production of TNF-α IFN-γ and IL-6 in inflamed tissues.SUMMARY DDRC ameliorated skin lesions such as crust, scales, incrustation and petechiae, and lowered erythema index on skin surface in CD miceDDRC inhibited enlargement of dorsal skin and prevented epidermal hyperplasia, hyperkeratosis, and spongiotic changes in inflamed tissuesDDRC reduced the levels of TNF-α, IFN-γ, and IL-6 in inflamed tissues of CD miceDDRC did not affect spleen/body weight ratio in CD mice. Abbreviations used: DDRC: decoction of Dictamni Radicis Cortex, CD: contact dermatitis, DNFB: 1-fluoro-2,4-dinitrofluorobenzene, AOO: acetone and olive oil, DEX: dexamethasone, CBA: cytometric bead array

Cutaneous anaplastic large-cell lymphoma (ALCL): A comparative clinical feature and survival outcome analysis of 52 cases according to primary tumor site

Cutaneous anaplastic large-cell lymphoma (ALCL) is primary extranodal or secondary to nodal disease. We sought to analyze clinical features and survival outcomes by primary tumor site in patients with cutaneous ALCL. Clinical features, survival outcomes, and prognostic factors of 52 patients with primary or secondary cutaneous ALCL to primary nodal disease were retrospectively evaluated using medical records. Although skin lesion characteristics did not significantly differ between groups, the head and neck location was more common in primary cutaneous ALCL, whereas cutaneous lesion extent was greater in secondary cutaneous ALCL. Skin lesion extent in primary cutaneous ALCL was indicative of extracutaneous dissemination development and skin lesion relapse. Neither anaplastic lymphoma kinase expression nor clinical stage affected skin lesion characteristics in secondary cutaneous ALCL. Patients with primary rather than secondary cutaneous ALCL demonstrated better survival outcomes. The skin lesion extent and location on the leg were associated with the tendency toward a poorer prognosis in primary cutaneous ALCL. The secondary cutaneous ALCL prognosis was not influenced by skin lesion characteristics. This was a retrospective study in a single institution. Survival outcomes and prognostic factors in cutaneous ALCL differed by primary tumor site.

Training pattern recognition of skin lesion morphology, configuration, and distribution

The ability to reliably recognize and classify a range of skin signs and symptoms remains a necessary skill across most clinical disciplines but one that is traditionally mastered via nonsystematic experience over long periods. We investigated whether online Perceptual and Adaptive Learning Modules (PALMs) could efficiently train preclerkship medical students to identify and discriminate primary skin lesion morphologies, configurations, and anatomic distributions. Medical students completed an online skin lesion morphology PALM voluntarily in year 1 and by requirement, along with configuration and anatomic distribution PALMs, in year 2. In controlled before-and-after studies, multiple-choice pretests and posttests using previously unused images, assessed PALM-induced learning. In prospective cohort studies, differences in year-2 performance between students who had and had not completed the morphology PALM in year 1 were also assessed. Multiple-choice tests, used to evaluate PALM effectiveness, demonstrated large (effect sizes of 1.1 [±0.1 SE] to 2.2 [±0.1 SE]) and statistically significant (P < .0001) improvements after PALM training, with learning retention when tested after 1 year. Results are from self-selected groups and a single class at 1 institution. PALMs are a useful tool for efficient development of the core clinical skills of pattern recognition and classification of skin lesion characteristics.

Factors Associated With the Number of Lesions Excised for Each Skin Cancer

To assess physician, patient, and skin lesion characteristics that affect the number of benign skin lesions excised by primary care physicians for each skin cancer. Prospective study collecting clinical, patient, and histopathologic details of excisions or biopsies of skin lesions by random samples of primary care physicians. Southeast Queensland involving traditional family medicine physicians (n = 104; response rate, 53.9%) and family medicine physicians working in 27 primary care skin cancer clinics (n = 50; response rate, 75.0%). Of 28 755 skin examinations recorded during the study, 11 403 skin lesions were excised or biopsied; 97.5% of the excised lesions had clinical and histologic diagnoses recorded. Number of lesions needed to excise or biopsy (NNE) for 1 melanoma (pigmented lesions only) and NNE for 1 nonmelanoma skin cancer (nonpigmented lesions only). The NNE for nonpigmented lesions (n = 8139) was 1.5 (95% confidence interval, 1.4-1.6) and for pigmented lesions (n = 2977) was 19.6 (16.2-22.9). The NNE estimates were up to 8 times lower if the physician thought the lesion was likely to be malignant and up to 2.5 times higher if there was strong patient pressure to excise. The NNE estimates varied by other physician-, patient-, and lesion-related variables. Clinical impressions of excised skin lesions were strongly associated with NNE estimates. By focusing on pigmented skin lesions and by addressing the physician- and patient-specific factors identified, the effectiveness of future training for primary care physicians in the clinical management of skin cancer could be improved.