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Dermatology Practical & Conceptual Oct 2023Hair and scalp disorders are of significant interest for physicians dealing with dark phototypes due to their prevalence and potential aesthetic impact resulting from a... (Review)
Review
Hair and scalp disorders are of significant interest for physicians dealing with dark phototypes due to their prevalence and potential aesthetic impact resulting from a higher tendency for scarring. In order to facilitate their non-invasive diagnosis, several dermoscopic studies have been published, yet data are sparse and no systematic analysis of the literature has been performed so far. This systematic literature review summarizes published data on trichoscopy of hair and scalp diseases (trichoscopic findings, used setting, pathological correlation, and level of evidence of studies). A total of 60 papers addressing 19 different disorders (eight non-cicatricial alopecias, nine cicatricial alopecias, and two hair shaft disorders) were assessed, for a total of 2636 instances. They included one cross-sectional analysis, 20 case-control studies, 25 case-series, and 14 single case-reports, so the level of evidence was V and IV in 65% and 33% of cases, respectively, with only one study showing a level of evidence of III. Notably, although there is a considerable body of literature on trichoscopy of hair/scalp diseases, our review underlined that potentially significant variables (e.g., disease stage or hair texture) are often not taken into account in published analyses, with possible biases on trichoscopic patterns, especially when it comes to hair shaft changes. Further analyses considering all such issues are therefore needed.
PubMed: 37874991
DOI: 10.5826/dpc.1304S1a310S -
Dermatology Practical & Conceptual Oct 2023Over the last few decades, dermoscopy has been showed to facilitate the non-invasive diagnosis of both benign and malignant skin tumors, yet literature data mainly comes... (Review)
Review
Over the last few decades, dermoscopy has been showed to facilitate the non-invasive diagnosis of both benign and malignant skin tumors, yet literature data mainly comes from studies on light photo-types. However, there is growing evidence that skin neoplasms may benefit from dermoscopic assessment even for skin of color. This systematic literature review evaluated published data in dark-skinned patients (dermoscopic features, used setting, pathological correlation, and level of evidence of studies), also providing a standardized and homogeneous terminology for reported dermoscopic findings. A total of 20 articles describing 46 different tumors (four melanocytic neoplasms, eight keratinocytic tumors, 15 adnexal cutaneous neoplasms, seven vascular tumors, four connective tissue tumors, and eight cystic neoplasms/others) for a total of 1724 instances were included in the analysis. Most of them showed a level of evidence of V (12 single case reports and six case series), with only two studies featuring a level of evidence of IV (case-control analysis). Additionally, this review also underlined that some neoplasms and phototypes are underrepresented in published analyses as they included only small samples and mainly certain tones of "dark skin" spectrum (especially phototype IV). Therefore, further studies considering such limitations are required for a better characterization.
PubMed: 37874990
DOI: 10.5826/dpc.1304S1a308S -
Cancers Sep 2023Melanoma, the deadliest form of skin cancer, poses a significant public health challenge worldwide. Early detection is crucial for improved patient outcomes.... (Review)
Review
BACKGROUND
Melanoma, the deadliest form of skin cancer, poses a significant public health challenge worldwide. Early detection is crucial for improved patient outcomes. Non-invasive skin imaging techniques allow for improved diagnostic accuracy; however, their use is often limited due to the need for skilled practitioners trained to interpret images in a standardized fashion. Recent innovations in artificial intelligence (AI)-based techniques for skin lesion image interpretation show potential for the use of AI in the early detection of melanoma.
OBJECTIVE
The aim of this study was to evaluate the current state of AI-based techniques used in combination with non-invasive diagnostic imaging modalities including reflectance confocal microscopy (RCM), optical coherence tomography (OCT), and dermoscopy. We also aimed to determine whether the application of AI-based techniques can lead to improved diagnostic accuracy of melanoma.
METHODS
A systematic search was conducted via the Medline/PubMed, Cochrane, and Embase databases for eligible publications between 2018 and 2022. Screening methods adhered to the 2020 version of the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines. Included studies utilized AI-based algorithms for melanoma detection and directly addressed the review objectives.
RESULTS
We retrieved 40 papers amongst the three databases. All studies directly comparing the performance of AI-based techniques with dermatologists reported the superior or equivalent performance of AI-based techniques in improving the detection of melanoma. In studies directly comparing algorithm performance on dermoscopy images to dermatologists, AI-based algorithms achieved a higher ROC (>80%) in the detection of melanoma. In these comparative studies using dermoscopic images, the mean algorithm sensitivity was 83.01% and the mean algorithm specificity was 85.58%. Studies evaluating machine learning in conjunction with OCT boasted accuracy of 95%, while studies evaluating RCM reported a mean accuracy rate of 82.72%.
CONCLUSIONS
Our results demonstrate the robust potential of AI-based techniques to improve diagnostic accuracy and patient outcomes through the early identification of melanoma. Further studies are needed to assess the generalizability of these AI-based techniques across different populations and skin types, improve standardization in image processing, and further compare the performance of AI-based techniques with board-certified dermatologists to evaluate clinical applicability.
PubMed: 37835388
DOI: 10.3390/cancers15194694 -
Frontiers in Medicine 2023Vitiligo is a multifaceted autoimmune depigmenting disorder affecting around 0.5 to 2.0% of individuals globally. Standardizing diagnosis and therapy tracking can be...
UNLABELLED
Vitiligo is a multifaceted autoimmune depigmenting disorder affecting around 0.5 to 2.0% of individuals globally. Standardizing diagnosis and therapy tracking can be arduous, as numerous clinical evaluation methods are subject to interobserver variability and may not be validated. Therefore, there is a need for diagnostic tools that are objective, dependable, and preferably non-invasive.
AIMS
This systematic review provides a comprehensive overview of the non-invasive objective skin measurement methods that are currently used to evaluate the diagnosis, severity, and progression of vitiligo, as well as the advantages and limitations of each technique.
METHODS
The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) checklist was used for the systematic review. Scopus, Embase, Cochrane Library, and Web of Science databases were comprehensively searched for non-invasive imaging and biophysical skin measuring methods to diagnose, evaluate the severity of, or monitor the effects of vitiligo treatment. The risk of bias in included articles was assessed using the QUADAS-2 quality assessment scale.
RESULTS
An extensive literature search resulted in 64 studies for analysis, describing eight imaging techniques (reflectance confocal microscopy, computer-aided imaging analysis, optical coherence tomography, infrared photography, third-harmonic generation microscopy, multiphoton microscopy, ultraviolet light photography, and visible light/digital photograph), and three biophysical approaches (dermoscopy, colorimetry, spectrometry) used in diagnosing and assessing vitiligo. Pertinent information about functionality, mechanisms of action, sensitivity, and specificity was obtained for all studies, and insights into the strengths and limitations of each diagnostic technique were addressed. Methodological study quality was adequate; however, statistical analysis was not achievable because of the variety of methods evaluated and the non-standardized reporting of diagnostic accuracy results.
CONCLUSIONS
The results of this systematic review can enhance clinical practice and research by providing a comprehensive overview of the spectrum of non-invasive imaging and biophysical techniques in vitiligo assessment. Studies with larger sample sizes and sound methodology are required to develop verified methods for use in future practice and research.
SYSTEMATIC REVIEW REGISTRATION
(PROSPERO) database, (CRD42023395996).
PubMed: 37575985
DOI: 10.3389/fmed.2023.1200963 -
Frontiers in Artificial Intelligence 2023Detecting and accurately diagnosing early melanocytic lesions is challenging due to extensive intra- and inter-observer variabilities. Dermoscopy images are widely used...
INTRODUCTION
Detecting and accurately diagnosing early melanocytic lesions is challenging due to extensive intra- and inter-observer variabilities. Dermoscopy images are widely used to identify and study skin cancer, but the blurred boundaries between lesions and besieging tissues can lead to incorrect identification. Artificial Intelligence (AI) models, including vision transformers, have been proposed as a solution, but variations in symptoms and underlying effects hinder their performance.
OBJECTIVE
This scoping review synthesizes and analyzes the literature that uses vision transformers for skin lesion detection.
METHODS
The review follows the PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses Extension for Scoping Revise) guidelines. The review searched online repositories such as IEEE Xplore, Scopus, Google Scholar, and PubMed to retrieve relevant articles. After screening and pre-processing, 28 studies that fulfilled the inclusion criteria were included.
RESULTS AND DISCUSSIONS
The review found that the use of vision transformers for skin cancer detection has rapidly increased from 2020 to 2022 and has shown outstanding performance for skin cancer detection using dermoscopy images. Along with highlighting intrinsic visual ambiguities, irregular skin lesion shapes, and many other unwanted challenges, the review also discusses the key problems that obfuscate the trustworthiness of vision transformers in skin cancer diagnosis. This review provides new insights for practitioners and researchers to understand the current state of knowledge in this specialized research domain and outlines the best segmentation techniques to identify accurate lesion boundaries and perform melanoma diagnosis. These findings will ultimately assist practitioners and researchers in making more authentic decisions promptly.
PubMed: 37529760
DOI: 10.3389/frai.2023.1202990