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Archives of Dermatological Research May 2024Skin cancer treatment is a core aspect of dermatology that relies on accurate diagnosis and timely interventions. Teledermatology has emerged as a valuable asset across... (Review)
Review
Skin cancer treatment is a core aspect of dermatology that relies on accurate diagnosis and timely interventions. Teledermatology has emerged as a valuable asset across various stages of skin cancer care including triage, diagnosis, management, and surgical consultation. With the integration of traditional dermoscopy and store-and-forward technology, teledermatology facilitates the swift sharing of high-resolution images of suspicious skin lesions with consulting dermatologists all-over. Both live video conference and store-and-forward formats have played a pivotal role in bridging the care access gap between geographically isolated patients and dermatology providers. Notably, teledermatology demonstrates diagnostic accuracy rates that are often comparable to those achieved through traditional face-to-face consultations, underscoring its robust clinical utility. Technological advancements like artificial intelligence and reflectance confocal microscopy continue to enhance image quality and hold potential for increasing the diagnostic accuracy of virtual dermatologic care. While teledermatology serves as a valuable clinical tool for all patient populations including pediatric patients, it is not intended to fully replace in-person procedures like Mohs surgery and other necessary interventions. Nevertheless, its role in facilitating the evaluation of skin malignancies is gaining recognition within the dermatologic community and fostering high approval rates from patients due to its practicality and ability to provide timely access to specialized care.
Topics: Humans; Artificial Intelligence; Dermatology; Dermoscopy; Remote Consultation; Skin Neoplasms; Telemedicine
PubMed: 38696032
DOI: 10.1007/s00403-024-02884-7 -
Scientific Reports Apr 2024Recently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin...
Recently, skin cancer is one of the spread and dangerous cancers around the world. Early detection of skin cancer can reduce mortality. Traditional methods for skin cancer detection are painful, time-consuming, expensive, and may cause the disease to spread out. Dermoscopy is used for noninvasive diagnosis of skin cancer. Artificial Intelligence (AI) plays a vital role in diseases' diagnosis especially in biomedical engineering field. The automated detection systems based on AI reduce the complications in the traditional methods and can improve skin cancer's diagnosis rate. In this paper, automated early detection system for skin cancer dermoscopic images using artificial intelligent is presented. Adaptive snake (AS) and region growing (RG) algorithms are used for automated segmentation and compared with each other. The results show that AS is accurate and efficient (accuracy = 96%) more than RG algorithm (accuracy = 90%). Artificial Neural networks (ANN) and support vector machine (SVM) algorithms are used for automated classification compared with each other. The proposed system with ANN algorithm shows high accuracy (94%), precision (96%), specificity (95.83%), sensitivity (recall) (92.30%), and F1-score (0.94). The proposed system is easy to use, time consuming, enables patients to make early detection for skin cancer and has high efficiency.
Topics: Humans; Skin Neoplasms; Early Detection of Cancer; Neural Networks, Computer; Artificial Intelligence; Algorithms; Support Vector Machine; Dermoscopy; Sensitivity and Specificity
PubMed: 38679633
DOI: 10.1038/s41598-024-59783-0 -
Biomedicines Apr 2024Bowen's disease represents the in situ form of cutaneous squamous cell carcinoma; although it has an excellent prognosis, 3-5% of lesions progress to invasive cutaneous... (Review)
Review
Bowen's disease represents the in situ form of cutaneous squamous cell carcinoma; although it has an excellent prognosis, 3-5% of lesions progress to invasive cutaneous squamous cell carcinoma, with a higher risk in immunocompromised patients. Treatment is therefore always necessary, and conventional photodynamic therapy is a first-line option. The aim of this review is to provide an overview of the clinical response, recurrence rates, safety, and cosmetic outcome of photodynamic therapy in the treatment of Bowen's disease, considering different protocols in terms of photosensitizers, light source, and combination treatments. Photodynamic therapy is a valuable option for tumors at sites where wound healing is poor/delayed, in the case of multiple and/or large tumors, and where surgery would be difficult or invasive. Dermoscopy and reflectance confocal microscopy can be used as valuable tools for monitoring the therapeutic response. The treatment is generally well tolerated, with mild side effects, and is associated with a good/excellent cosmetic outcome. Periodic follow-up after photodynamic therapy is essential because of the risk of recurrence and progression to cSCC. As the incidence of keratinocyte tumors increases, the therapeutic space for photodynamic therapy will further increase.
PubMed: 38672152
DOI: 10.3390/biomedicines12040795 -
Journal of Cancer Research and Clinical... Apr 2024Merkel cell carcinoma (MCC) is a rare neuroendocrine tumor of the skin, which mainly occurs in the sun exposed sites of white patients over 65 years, with a higher... (Review)
Review
PURPOSE
Merkel cell carcinoma (MCC) is a rare neuroendocrine tumor of the skin, which mainly occurs in the sun exposed sites of white patients over 65 years, with a higher recurrence and metastasis rate. Clinically, MCC overlapping Bowen's disease (BD) is a very rare subtype of MCC. Few cases in the literature have been described and the management is not well defined. We summarize and update the epidemiology, clinical and histopathological features, metastasis characteristics, local recurrence rate and management of it by presenting two cases of MCC overlapping BD and reviewing the literature over the last 11 years.
DESIGN
We consulted databases from PubMed, ResearchGate and Google Scholar by MeSh "Merkel cell carcinoma" and "Bowen's disease", "Bowen disease" or "squamous cell carcinoma in situ", from January 2013 to December 2023 and reviewed the literatures. We reported two additional cases.
RESULTS
Total 13 cases of MCC overlapping BD were retrospectively analyzed, in whom mainly in elderly women over 70 years, the skin lesions were primarily located on the faces, followed by the extremities and trunk. Most of them were asymptomatic, firm, dark red nodules arising on rapidly growing red or dark brown patches, or presenting as isolated nodules. Dermoscopy evaluation was rarely performed in the pre-operative diagnostic setting. All cases were confirmed by histopathology and immunohistochemistry. The most definitive treatment was extended local excision, but local recurrences were common. Of the 13 cases, 4 cases experienced local or distant metastasis. One suffered from an in-transit recurrence of MCC on the ipsilateral leg after local excision and lymph node dissection, whose metastasis completely subsided after avelumab treatment and without recurrence or metastasis during 6 months of follow-up.
CONCLUSIONS
MCC overlapping BD is a very rare skin tumor mainly predisposed on the faces, with high misdiagnosis rate and recurrence rate. Advanced disease at diagnosis is a poor prognostic factor, suggesting that earlier detection may improve outcome. The acronym, AEIOUN, has been proposed to aid in clinical identification. Our reports and the literature review can provide a better awareness and management of it.
Topics: Aged, 80 and over; Female; Humans; Male; Middle Aged; Bowen's Disease; Carcinoma, Merkel Cell; Neoplasm Recurrence, Local; Skin Neoplasms
PubMed: 38668799
DOI: 10.1007/s00432-024-05743-0 -
Frontiers in Medicine 2024In this report, a female patient suffering from pigment retention caused by a skin marking pen was elucidated. The patient underwent blepharoplasty 6 months ago and...
In this report, a female patient suffering from pigment retention caused by a skin marking pen was elucidated. The patient underwent blepharoplasty 6 months ago and presented with blue-black linear marks at the upper eyelid incision 2 weeks after surgery. Under dermoscopy, scattered pigments were observed to accumulate in the epidermis of the upper eyelid. The patient was diagnosed with iatrogenic tattoo by a surgical marking pen. We chose surgical excision of the skin with the pigmentation. Previous studies have established that the risk of bacterial contamination, contact dermatitis, and allergies may increase with the surgical marking pens, while pigment retention has not yet been mentioned yet. Here, we present a case with a pigment retention in the incision. The selection of the surgical labelling methods and the management of the pigmentation were also addressed. According to our clinical findings, the risk of pigment retention by marking pens needs to be mentioned in the patient's informed consent. Therefore, the practitioner should ensure that the ink is cleaned by the end of each invasive procedure.
PubMed: 38665293
DOI: 10.3389/fmed.2024.1387773 -
Photodiagnosis and Photodynamic Therapy Jun 2024Actinic keratosis (AK) is a precancerous lesion that occurs in areas that are chronically exposed to sunlight and has the potential to develop into invasive cutaneous...
BACKGROUND
Actinic keratosis (AK) is a precancerous lesion that occurs in areas that are chronically exposed to sunlight and has the potential to develop into invasive cutaneous squamous cell carcinoma (cSCC). We investigated the efficacy of 20 % 5-aminolevulinic acid-photodynamic therapy (ALA-PDT) with LED red light for the treatment of AK in Chinese patients by examining changes in dermoscopic features, histopathology and fluorescence after treatment.
METHODS
Twenty-eight patients with fourty-six AK lesions from March 2022 to September 2023 were treated with 20 % ALA, and 3 h later, they were irradiated with LED red light (80-100 mW/cm) for 20 min. A session of 20 % ALA-PDT was performed once a week for three consecutive weeks, and the dermoscopic, histopathological, fluorescent and photoaging outcomes were measured one week after the treatment.
RESULTS
One week after ALA-PDT, complete remission (CR) was reached in 53.6 % of patients. The CR of Grade I AK lesions was 100 %, that of Grade II lesions was 71.4 %, and that of Grade III lesions was 38.1 %. There was a significant improvement in the dermoscopic features, epidermal thickness and fluorescence of the AK lesions. The presence of red fluorescence decreased, and there was an association between CR and post-PDT fluorescence intensity. ALA-PDT also exhibited efficacy in treating photoaging, including fine lines, sallowness, mottled pigmentation, erythema, and telangiectasias, and improved the global score for photoaging. There were no serious adverse effects during or after ALA-PDT, and 82.1 % of the patients were satisfied with the treatment.
CONCLUSION
AK lesions can be safely and effectively treated with 20 % ALA-PDT with LED red light, which also alleviates photoaging in Chinese patients, including those with multiple AKs. This study highlights the possibility that fluorescence could be used to diagnose AK with peripheral field cancerization and evaluate the efficacy of ALA-PDT.
Topics: Keratosis, Actinic; Aminolevulinic Acid; Humans; Photochemotherapy; Photosensitizing Agents; Female; Male; Aged; Middle Aged; Dermoscopy; Aged, 80 and over; Fluorescence
PubMed: 38663488
DOI: 10.1016/j.pdpdt.2024.104100 -
Anais Brasileiros de Dermatologia 2024
Topics: Humans; Dermoscopy; Eczema; Tinea Pedis; Psoriasis; Hand Dermatoses; Female; Male; Adult; Middle Aged
PubMed: 38658237
DOI: 10.1016/j.abd.2023.05.008 -
Heliyon Apr 2024Dermoscopy has emerged as a useful diagnostic tool to evaluate skin lesions, including psoriasis. We aimed to compare the clinical examination and digital dermoscopy...
BACKGROUND
Dermoscopy has emerged as a useful diagnostic tool to evaluate skin lesions, including psoriasis. We aimed to compare the clinical examination and digital dermoscopy findings of nail involvement in patients with psoriatic nails.
METHODS
This study included 60 patients with clinically diagnosed psoriasis. The nail findings and NAPSI were evaluated clinically and via dermoscopy, and then the severity of the disease was calculated using PASI criteria.
RESULTS
About 32 patients were males, with a median PASI score of 4.4, and pitting and subungual hyperkeratosis were the most common findings. The clinical and dermoscopic examination had a moderate diagnostic resemblance regarding onycholysis, subungual hyperkeratosis, and leukonychia. The resemblance between the two methods for the diagnosis of leukonychia in patients with a duration of disease <2 years (Kappa = 0.59) and 2-6 years was moderate (Kappa = 0.48), and for 6 years< was perfect (Kappa = 0.62). The resemblance for the diagnosis of subungual hyperkeratosis and onycholysis in subjects with a duration of disease <2 years was slight, and for 2-6 years and 6 years< were moderate. The resemblance between the NAPSI score by the two methods was also moderate (95%CI -0.89-0.81, < 0.001).
CONCLUSION
Dermoscopy is an efficient, supportive, and non-invasive method providing a better diagnosis of nail psoriasis.
PubMed: 38655347
DOI: 10.1016/j.heliyon.2024.e29608 -
Frontiers in Medicine 2024Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert...
INTRODUCTION
Artificial Intelligence (AI) has proven effective in classifying skin cancers using dermoscopy images. In experimental settings, algorithms have outperformed expert dermatologists in classifying melanoma and keratinocyte cancers. However, clinical application is limited when algorithms are presented with 'untrained' or out-of-distribution lesion categories, often misclassifying benign lesions as malignant, or misclassifying malignant lesions as benign. Another limitation often raised is the lack of clinical context (e.g., medical history) used as input for the AI decision process. The increasing use of Total Body Photography (TBP) in clinical examinations presents new opportunities for AI to perform holistic analysis of the whole patient, rather than a single lesion. Currently there is a lack of existing literature or standards for image annotation of TBP, or on preserving patient privacy during the machine learning process.
METHODS
This protocol describes the methods for the acquisition of patient data, including TBP, medical history, and genetic risk factors, to create a comprehensive dataset for machine learning. 500 patients of various risk profiles will be recruited from two clinical sites (Australia and Spain), to undergo temporal total body imaging, complete surveys on sun behaviors and medical history, and provide a DNA sample. This patient-level metadata is applied to image datasets using DICOM labels. Anonymization and masking methods are applied to preserve patient privacy. A two-step annotation process is followed to label skin images for lesion detection and classification using deep learning models. Skin phenotype characteristics are extracted from images, including innate and facultative skin color, nevi distribution, and UV damage. Several algorithms will be developed relating to skin lesion detection, segmentation and classification, 3D mapping, change detection, and risk profiling. Simultaneously, explainable AI (XAI) methods will be incorporated to foster clinician and patient trust. Additionally, a publicly released dataset of anonymized annotated TBP images will be released for an international challenge to advance the development of new algorithms using this type of data.
CONCLUSION
The anticipated results from this protocol are validated AI-based tools to provide holistic risk assessment for individual lesions, and risk stratification of patients to assist clinicians in monitoring for skin cancer.
PubMed: 38654834
DOI: 10.3389/fmed.2024.1380984 -
Scientific Reports Apr 2024Skin cancer is the most prevalent kind of cancer in people. It is estimated that more than 1 million people get skin cancer every year in the world. The effectiveness of...
Skin cancer is the most prevalent kind of cancer in people. It is estimated that more than 1 million people get skin cancer every year in the world. The effectiveness of the disease's therapy is significantly impacted by early identification of this illness. Preprocessing is the initial detecting stage in enhancing the quality of skin images by removing undesired background noise and objects. This study aims is to compile preprocessing techniques for skin cancer imaging that are currently accessible. Researchers looking into automated skin cancer diagnosis might use this article as an excellent place to start. The fully convolutional encoder-decoder network and Sparrow search algorithm (FCEDN-SpaSA) are proposed in this study for the segmentation of dermoscopic images. The individual wolf method and the ensemble ghosting technique are integrated to generate a neighbour-based search strategy in SpaSA for stressing the correct balance between navigation and exploitation. The classification procedure is accomplished by using an adaptive CNN technique to discriminate between normal skin and malignant skin lesions suggestive of disease. Our method provides classification accuracies comparable to commonly used incremental learning techniques while using less energy, storage space, memory access, and training time (only network updates with new training samples, no network sharing). In a simulation, the segmentation performance of the proposed technique on the ISBI 2017, ISIC 2018, and PH2 datasets reached accuracies of 95.28%, 95.89%, 92.70%, and 98.78%, respectively, on the same dataset and assessed the classification performance. It is accurate 91.67% of the time. The efficiency of the suggested strategy is demonstrated through comparisons with cutting-edge methodologies.
Topics: Humans; Skin Neoplasms; Algorithms; Neural Networks, Computer; Dermoscopy; Image Processing, Computer-Assisted; Image Interpretation, Computer-Assisted; Skin
PubMed: 38653997
DOI: 10.1038/s41598-024-57393-4