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JMIR Medical Informatics Jun 2024Dermoscopy is a growing field that uses microscopy to allow dermatologists and primary care physicians to identify skin lesions. For a given skin lesion, a wide variety...
BACKGROUND
Dermoscopy is a growing field that uses microscopy to allow dermatologists and primary care physicians to identify skin lesions. For a given skin lesion, a wide variety of differential diagnoses exist, which may be challenging for inexperienced users to name and understand.
OBJECTIVE
In this study, we describe the creation of the dermoscopy differential diagnosis explorer (D3X), an ontology linking dermoscopic patterns to differential diagnoses.
METHODS
Existing ontologies that were incorporated into D3X include the elements of visuals ontology and dermoscopy elements of visuals ontology, which connect visual features to dermoscopic patterns. A list of differential diagnoses for each pattern was generated from the literature and in consultation with domain experts. Open-source images were incorporated from DermNet, Dermoscopedia, and open-access research papers.
RESULTS
D3X was encoded in the OWL 2 web ontology language and includes 3041 logical axioms, 1519 classes, 103 object properties, and 20 data properties. We compared D3X with publicly available ontologies in the dermatology domain using a semiotic theory-driven metric to measure the innate qualities of D3X with others. The results indicate that D3X is adequately comparable with other ontologies of the dermatology domain.
CONCLUSIONS
The D3X ontology is a resource that can link and integrate dermoscopic differential diagnoses and supplementary information with existing ontology-based resources. Future directions include developing a web application based on D3X for dermoscopy education and clinical practice.
PubMed: 38904996
DOI: 10.2196/49613 -
Archives of Dermatological Research Jun 2024High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of... (Review)
Review
High-frequency ultrasound has been used to visualize depth and vascularization of cutaneous neoplasms, but little has been synthesized as a review for a robust level of evidence about the diagnostic accuracy of high-frequency ultrasound in dermatology. A narrative review of the PubMed database was performed to establish the correlation between ultrasound findings and histopathologic/dermoscopic findings for cutaneous neoplasms. Articles were divided into the following four categories: melanocytic, keratinocytic/epidermal, appendageal, and soft tissue/neural neoplasms. Review of the literature revealed that ultrasound findings and histopathology findings were strongly correlated regarding the depth of a cutaneous neoplasm. Morphological characteristics were correlated primarily in soft tissue/neural neoplasms. Overall, there is a paucity of literature on the correlation between high-frequency ultrasound and histopathology of cutaneous neoplasms. Further studies are needed to investigate this correlation in various dermatologic conditions.
Topics: Humans; Skin Neoplasms; Ultrasonography; Skin; Dermoscopy; Melanoma
PubMed: 38904763
DOI: 10.1007/s00403-024-03179-7 -
Ugeskrift For Laeger Jun 2024
Topics: Humans; Dermoscopy; Acanthoma; Skin Neoplasms; Male; Female
PubMed: 38904287
DOI: 10.61409/V72030 -
Skin Research and Technology : Official... Jun 2024Ultraviolet (UV)-induced fluorescence technology is widely used in dermatology to identify microbial infections. Our clinical observations under an ultraviolet-induced...
BACKGROUND
Ultraviolet (UV)-induced fluorescence technology is widely used in dermatology to identify microbial infections. Our clinical observations under an ultraviolet-induced fluorescent dermatoscope (UVFD) showed red fluorescence on the scalps of androgenetic alopecia (AGA) patients. In this study, based on the hypothesis that microbes are induced to emit red fluorescence under UV light, we aimed to explore the microbial disparities between the AGA fluorescent area (AF group) and AGA non-fluorescent area (ANF group).
METHODS
Scalp swab samples were collected from 36 AGA patients, including both fluorescent and non-fluorescent areas. The bacterial communities on the scalp were analyzed by 16S rRNA gene sequencing and bioinformatics analysis, as well as through microbial culture methods.
RESULTS
Significant variations were observed in microbial evenness, abundance composition, and functional predictions between fluorescent and non-fluorescent areas. Sequencing results highlighted significant differences in Cutibacterium abundance between these areas (34.06% and 21.36%, respectively; p < 0.05). Furthermore, cultured red fluorescent colonies primarily consisted of Cutibacterium spp., Cutibacterium acnes, Staphylococcus epidermidis, and Micrococcus spp.
CONCLUSIONS
This is the first study to investigate scalp red fluorescence, highlighting microbial composition variability across different scalp regions. These findings may provide novel insights into the microbiological mechanisms of AGA.
Topics: Humans; Alopecia; Ultraviolet Rays; Male; Adult; Middle Aged; Scalp; Female; Dermoscopy; Fluorescence; Microbiota; RNA, Ribosomal, 16S; Bacteria
PubMed: 38899718
DOI: 10.1111/srt.13777 -
Diagnostics (Basel, Switzerland) May 2024This survey represents the first endeavor to assess the clarity of the dermoscopic language by a chatbot, unveiling insights into the interplay between dermatologists...
This survey represents the first endeavor to assess the clarity of the dermoscopic language by a chatbot, unveiling insights into the interplay between dermatologists and AI systems within the complexity of the dermoscopic language. Given the complex, descriptive, and metaphorical aspects of the dermoscopic language, subjective interpretations often emerge. The survey evaluated the completeness and diagnostic efficacy of chatbot-generated reports, focusing on their role in facilitating accurate diagnoses and educational opportunities for novice dermatologists. A total of 30 participants were presented with hypothetical dermoscopic descriptions of skin lesions, including dermoscopic descriptions of skin cancers such as BCC, SCC, and melanoma, skin cancer mimickers such as actinic and seborrheic keratosis, dermatofibroma, and atypical nevus, and inflammatory dermatosis such as psoriasis and alopecia areata. Each description was accompanied by specific clinical information, and the participants were tasked with assessing the differential diagnosis list generated by the AI chatbot in its initial response. In each scenario, the chatbot generated an extensive list of potential differential diagnoses, exhibiting lower performance in cases of SCC and inflammatory dermatoses, albeit without statistical significance, suggesting that the participants were equally satisfied with the responses provided. Scores decreased notably when practical descriptions of dermoscopic signs were provided. Answers to BCC scenario scores in the diagnosis category (2.9 ± 0.4) were higher than those with SCC (2.6 ± 0.66, = 0.005) and inflammatory dermatoses (2.6 ± 0.67, = 0). Similarly, in the teaching tool usefulness category, BCC-based chatbot differential diagnosis received higher scores (2.9 ± 0.4) compared to SCC (2.6 ± 0.67, = 0.001) and inflammatory dermatoses (2.4 ± 0.81, = 0). The abovementioned results underscore dermatologists' familiarity with BCC dermoscopic images while highlighting the challenges associated with interpreting rigorous dermoscopic images. Moreover, by incorporating patient characteristics such as age, phototype, or immune state, the differential diagnosis list in each case was customized to include lesion types appropriate for each category, illustrating the AI's flexibility in evaluating diagnoses and highlighting its value as a resource for dermatologists.
PubMed: 38893694
DOI: 10.3390/diagnostics14111165 -
Journal of Clinical Medicine Jun 2024The rising incidence of Basal Cell Carcinoma (BCC), especially among individuals with significant sun exposure, underscores the need for effective and minimally...
The rising incidence of Basal Cell Carcinoma (BCC), especially among individuals with significant sun exposure, underscores the need for effective and minimally invasive treatment alternatives. Traditional surgical approaches, while effective, often result in notable cosmetic and functional limitations, particularly for lesions located on the face. This study explores High-Intensity Focused Ultrasound (HIFU) as a promising, non-invasive treatment option that aims to overcome these challenges, potentially revolutionizing BCC treatment by offering a balance between efficacy and cosmetic outcomes. Our investigation enrolled 8 patients, presenting a total of 15 BCC lesions, treated with a 20 MHz HIFU device. The selection of treatment parameters was precise, utilizing probe depths from 0.8 mm to 2.3 mm and energy settings ranging from 0.7 to 1.3 Joules (J) per pulse, determined by the lesion's infiltration depth as assessed via pre-procedure ultrasonography. A key component of our methodology included dermatoscopic monitoring, which allowed for detailed observation of the lesions' response to treatment over time. Patient-reported outcomes and satisfaction levels were systematically recorded, providing insights into the comparative advantages of HIFU. Initial responses after HIFU treatment included whitening and edema, indicative of successful lesion ablation. Early post-treatment observations revealed minimal discomfort and quick recovery, with crust formation resolving within two weeks for most lesions. Over a period of three to six months, patients reported significant improvement, with lesions becoming lighter and blending into the surrounding skin, demonstrating effective and aesthetically pleasing outcomes. Patient satisfaction surveys conducted six months post-treatment revealed high levels of satisfaction, with 75% of participants reporting very high satisfaction due to minimal scarring and the non-invasive nature of the procedure. No recurrences of BCC were noted, attesting to the efficacy of HIFU as a treatment option. The findings from this study confirm that based on dermoscopy analysis, HIFU is a highly effective and patient-preferred non-invasive treatment modality for Basal Cell Carcinoma. HIFU offers a promising alternative to traditional surgical and non-surgical treatments, reducing the cosmetic and functional repercussions associated with BCC management. Given its efficacy, safety, and favorable patient satisfaction scores, HIFU warrants further investigation and consideration for broader clinical application in the treatment of BCC, potentially setting a new standard in dermatologic oncology care. This work represents a pilot study that is the first to describe the use of HIFU in the treatment of BCC.
PubMed: 38892988
DOI: 10.3390/jcm13113277 -
Scientific Data Jun 2024Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a...
Advancements in dermatological artificial intelligence research require high-quality and comprehensive datasets that mirror real-world clinical scenarios. We introduce a collection of 18,946 dermoscopic images spanning from 2010 to 2016, collated at the Hospital Clínic in Barcelona, Spain. The BCN20000 dataset aims to address the problem of unconstrained classification of dermoscopic images of skin cancer, including lesions in hard-to-diagnose locations such as those found in nails and mucosa, large lesions which do not fit in the aperture of the dermoscopy device, and hypo-pigmented lesions. Our dataset covers eight key diagnostic categories in dermoscopy, providing a diverse range of lesions for artificial intelligence model training. Furthermore, a ninth out-of-distribution (OOD) class is also present on the test set, comprised of lesions which could not be distinctively classified as any of the others. By providing a comprehensive collection of varied images, BCN20000 helps bridge the gap between the training data for machine learning models and the day-to-day practice of medical practitioners. Additionally, we present a set of baseline classifiers based on state-of-the-art neural networks, which can be extended by other researchers for further experimentation.
Topics: Dermoscopy; Humans; Skin Neoplasms; Spain; Neural Networks, Computer; Artificial Intelligence; Machine Learning
PubMed: 38886204
DOI: 10.1038/s41597-024-03387-w -
Journal of Pharmacy & Bioallied Sciences Apr 2024Dermoscopy particularly could be helpful in patients with steroid damaged face to assess and look for the damage caused by the steroid creams as also in cases where the...
BACKGROUND AND OBJECTIVES
Dermoscopy particularly could be helpful in patients with steroid damaged face to assess and look for the damage caused by the steroid creams as also in cases where the patient provides improper history.
MATERIALS AND METHODS
Patients attending to dermatology OPD with suspected/diagnosed TSDF between the ages of 18 and 60 years were enrolled and assessed on the basis of age, gender, residence, duration, potency, brand of application topical steroid creams, clinical and dermoscopic features.
RESULTS
Majority abusing the topical steroid creams were females (n-14) with mean age with SD of 34 ± 11 and were from rural areas (57.8%). Red raised lesions were the most common clinical presentation (n-15) with telangiectasias as the most common dermoscopic feature (n-26). Triple combination creams containing hydroquinone 2%, tretinoin 0.025%, and 0.1% mometasone were on the top of the list (n-20).
CONCLUSION
In this study, the importance of dermoscopy in assessing the features of topical steroid damaged face and preventing further damage is highlighted. Various factors causing topical steroid creams misuse and the easy availability of the creams is to be kept on check.
PubMed: 38882848
DOI: 10.4103/jpbs.jpbs_1191_23 -
Skin Research and Technology : Official... Jun 2024Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays...
BACKGROUND
Melanoma is one of the most malignant forms of skin cancer, with a high mortality rate in the advanced stages. Therefore, early and accurate detection of melanoma plays an important role in improving patients' prognosis. Biopsy is the traditional method for melanoma diagnosis, but this method lacks reliability. Therefore, it is important to apply new methods to diagnose melanoma effectively.
AIM
This study presents a new approach to classify melanoma using deep neural networks (DNNs) with combined multiple modal imaging and genomic data, which could potentially provide more reliable diagnosis than current medical methods for melanoma.
METHOD
We built a dataset of dermoscopic images, histopathological slides and genomic profiles. We developed a custom framework composed of two widely established types of neural networks for analysing image data Convolutional Neural Networks (CNNs) and networks that can learn graph structure for analysing genomic data-Graph Neural Networks. We trained and evaluated the proposed framework on this dataset.
RESULTS
The developed multi-modal DNN achieved higher accuracy than traditional medical approaches. The mean accuracy of the proposed model was 92.5% with an area under the receiver operating characteristic curve of 0.96, suggesting that the multi-modal DNN approach can detect critical morphologic and molecular features of melanoma beyond the limitations of traditional AI and traditional machine learning approaches. The combination of cutting-edge AI may allow access to a broader range of diagnostic data, which can allow dermatologists to make more accurate decisions and refine treatment strategies. However, the application of the framework will have to be validated at a larger scale and more clinical trials need to be conducted to establish whether this novel diagnostic approach will be more effective and feasible.
Topics: Humans; Melanoma; Deep Learning; Skin Neoplasms; Dermoscopy; Neural Networks, Computer; Reproducibility of Results; Genomics; Female; Male; Middle Aged; Adult; Aged
PubMed: 38881051
DOI: 10.1111/srt.13770 -
Archives of Dermatological Research Jun 2024There are many therapeutic modalities for plantar warts, however treating it remains challenging. Intralesional injection of 5-fluorouarcil and combined digoxin and... (Randomized Controlled Trial)
Randomized Controlled Trial Comparative Study
There are many therapeutic modalities for plantar warts, however treating it remains challenging. Intralesional injection of 5-fluorouarcil and combined digoxin and furosemide were observed to be effective and safe, however no comparison study between them was done. Our study was conducted to evaluate the efficacy of both therapies in the treatment of plantar warts. 90 adult patients with multiple recalcitrant plantar warts were included in our study. They were randomly allocated to one of three groups; combined digoxin and furosemide, 5-fluorouarcil, or normal saline group. Fortnightly injections were done into all studied warts till complete clearance or up to 5 sessions. Warts were evaluated clinically and dermoscopically. Clinical response was reported in 24 patients (80%) of the combined digoxin and furosemide group with 40% complete response and in 24 patients (80%) of the 5-fluorouarcil group with 33.3% complete response. No statistically significant difference was observed between the two groups concerning efficacy and safety. Intralesional injection of 5-fluorouarcil and combined digoxin and furosemide are nearly equivalent in efficacy and safety for plantar wart treatment. Dermoscopy helps to take the truthful judgment about complete clearance of warts.
Topics: Humans; Furosemide; Male; Female; Adult; Warts; Digoxin; Injections, Intralesional; Treatment Outcome; Prospective Studies; Young Adult; Middle Aged; Drug Therapy, Combination; Adolescent; Dermoscopy; Flucytosine
PubMed: 38878078
DOI: 10.1007/s00403-024-03014-z