Diagnosis Of Dermatological Conditions Research Articles

4D spectral-spatial computational photoacoustic dermoscopy

Photoacoustic dermoscopy (PAD) is an emerging non-invasive imaging technology aids in the diagnosis of dermatological conditions by obtaining optical absorption information of skin tissues. Despite advances in PAD, it remains unclear how to obtain quantitative accuracy of the reconstructed PAD images according to the optical and acoustic properties of multilayered skin, the wavelength and distribution of excitation light, and the detection performance of ultrasound transducers. In this work, a computing method of four-dimensional (4D) spectral-spatial imaging for PAD is developed to enable quantitative analysis and optimization of structural and functional imaging of skin. This method takes the optical and acoustic properties of heterogeneous skin tissues into account, which can be used to correct the optical field of excitation light, detectable ultrasonic field, and provide accurate single-spectrum analysis or multi-spectral imaging solutions of PAD for multilayered skin tissues. A series of experiments were performed, and simulation datasets obtained from the computational model were used to train neural networks to further improve the imaging quality of the PAD system. All the results demonstrated the method could contribute to the development and optimization of clinical PADs by datasets with multiple variable parameters, and provide clinical predictability of photoacoustic (PA) data for human skin.

Performance of ChatGPT on dermatology Specialty Certificate Examination multiple choice questions.

ChatGPT is a large language model trained on increasingly large datasets by OpenAI to perform language-based tasks. It is capable of answering multiple-choice questions, such as those posed by the dermatology SCE examination. We asked two iterations of ChatGPT: ChatGPT-3.5 and ChatGPT-4 84 multiple-choice sample questions from the sample dermatology SCE question bank. ChatGPT-3.5 achieved an overall score of 63.1%, and ChatGPT-4 scored 90.5% (a significant improvement in performance (p<0.001)). The typical pass mark for the dermatology SCE is 70-72%. ChatGPT-4 is therefore capable of answering clinical questions and achieving a passing grade in these sample questions. There are many possible educational and clinical implications for increasingly advanced artificial intelligence (AI) and its use in medicine, including in the diagnosis of dermatological conditions. Such advances should be embraced provided that patient safety is a core tenet, and the limitations of AI in the nuances of complex clinical cases are recognised.

Analyzing the Predictability of an Artificial Intelligence App (Tibot) in the Diagnosis of Dermatological Conditions: A Cross-sectional Study.

Artificial intelligence (AI) aims to create programs that reproduce human cognition and processes involved in interpreting complex data. Dermatology relies on morphological features and is ideal for applying AI image recognition for assisted diagnosis. Tibot is an AI app that analyzes skin conditions and works on the principle of a convolutional neural network. Appropriate research analyzing the accuracy of such apps is necessary. This study aims to analyze the predictability of the Tibot AI app in the identification of dermatological diseases as compared to a dermatologist. This is a cross-sectional study. After taking informed consent, photographs of lesions of patients with different skin conditions were uploaded to the app. In every condition, the AI predicted three diagnoses based on probability, and these were compared with that by a dermatologist. The ability of the AI app to predict the actual diagnosis in the top one and top three anticipated diagnoses (prediction accuracy) was used to evaluate the app's effectiveness. Sensitivity, specificity, and positive predictive value were also used to assess the app's performance. Chi-square test was used to contrast categorical variables. P<.05 was considered statistically significant. A total of 600 patients were included. Clinical conditions included alopecia, acne, eczema, immunological disorders, pigmentary disorders, psoriasis, infestation, tumors, and infections. In the anticipated top three diagnoses, the app's mean prediction accuracy was 96.1% (95% CI 94.3%-97.5%), while for the exact diagnosis, it was 80.6% (95% CI 77.2%-83.7%). The prediction accuracy (top one) for alopecia, acne, pigmentary disorders, and fungal infections was 97.7%, 91.7%, 88.5%, and 82.9%, respectively. Prediction accuracy (top three) for alopecia, eczema, and tumors was 100%. The sensitivity and specificity of the app were 97% (95% CI 95%-98%) and 98% (95% CI 98%-99%), respectively. There is a statistically significant association between clinical and AI-predicted diagnoses in all conditions (P<.001). The AI app has shown promising results in diagnosing various dermatological conditions, and there is great potential for practical applicability.

Esophageal Manifestations of Dermatological Diseases, Diagnosis and Management.

The purpose of this article is to discuss the diagnosis and treatment of diseases that affect both the skin and the esophagus. The diagnosis of dermatological conditions that affect the esophagus often requires endoscopy and biopsy with some conditions requiring further investigation with serology, immunofluorescence, manometry, or genetic testing. Many conditions that affect the skin and esophagus can be treated successfully with systemic steroids and immunosuppressants including pemphigus, pemphigoid, HIV, esophageal lichen planus, and Crohn's disease. Many conditions are associated with esophageal strictures which are treated with endoscopic dilation. Furthermore, many of the diseases are pre-malignant and require vigilance and surveillance endoscopy. Diseases that affect the skin and esophagus can be grouped by their underlying etiology: autoimmune (scleroderma, dermatomyositis, pemphigus, pemphigoid), infectious (herpes simplex virus, cytomegalovirus, human immunodeficiency virus), inflammatory (lichen planus and Crohn's disease), and genetic (epidermolysis bullosa, Cowden syndrome, focal dermal hypoplasia, and tylosis). It is important to consider primary skin conditions that affect the esophagus when patients present with dysphagia of unknown etiology and characteristic skin findings.

Multiscale confocal photoacoustic dermoscopy to evaluate skin health.

Photoacoustic dermoscopy (PAD) is a promising branch of photoacoustic microscopy (PAM) that can provide a range of functional and morphologic information for clinical assessment and diagnosis of dermatological conditions. However, most PAM setups are unsuitable for clinical dermatology because their single-scale mode and narrow frequency band result in insufficient imaging depth or poor spatiotemporal resolution when visualizing the internal texture of the skin. We developed a multiscale confocal photoacoustic dermoscopy (MC-PAD) with a multifunction opto-sono objective that could achieve high quality dermatological imaging. Using the objective to coordinate the spatial resolution and penetration depth, the MC-PAD was used to visualize pathophysiological biomarkers and vascular morphology from the epidermis (EP) to the dermis, which enabled us to quantify skin abnormalities without using exogenous contrast agents for human skin. The MC-PAD was shown to have the ability to differentiate between different types of cells (such as red blood cells and melanoma cells), image and quantify pigment of the skin, and visualize skin morphology and blood capillary landmarks. The MC-PAD detected a significant difference in the structures of some pigmented and vascular lesions of skin diseases compared with that of healthy skin (P<0.01). The café au lait macule (CALM) skin type was found to have a relatively higher melanin concentration and thicker stratum basale (SB) in the EP than healthy skin. The dermal vascular network of skin that had a port wine stain (PWS) had greater diameters and a denser distribution than healthy skin, as reported in clinical trials. The MC-PAD has a broad range of applications for the diagnosis of human skin diseases and evaluation of the curative effect of treatments, and it can offer new perspectives in biomedical sciences.

A multiyear cross-sectional study of U.S. national prescribing patterns of first-generation sedating antihistamines in older adults with skin disease.

First-generation antihistamines (FGAs) are classified as 'potentially inappropriate' for use in older patients (patients aged ≥ 65 years). However, the prevalence of and factors associated with FGA prescription have not been studied. To examine FGA prescription rates for older patients who visited dermatology offices, and compare them to those for younger patients (patients aged 18-65 years) who visited dermatology offices and those for older patients who visited primary-care physicians (PCPs). This was a multiyear cross-sectional observational study using data from the U.S. National Ambulatory Medical Care Survey(2006-2015). Visits by patients aged 18 years or older were included in the study; the data comprised 15243 dermatology office visits and 66036 PCP office visits. The main outcome was FGA prescription. Other variables included physician specialty (dermatologist or PCP), patient's age, diagnosis of dermatological conditions and reason for visit. For dermatology visits, the overall FGA prescription rate for older patients was similar to that for younger patients (1·5% vs. 1·2%; P = 0·19), even when the diagnosis was dermatitis or pruritus (3·7% vs. 4·8%; P = 0·21) or when itch was a complaint (7·6% vs. 6·7%; P = 0·64). However, the rate of FGA prescription for dermatology visits was lower than that for PCP visits, in analyses matched for patient and visit characteristics (3·9% vs. 7·4%; P = 0·02). Our findings suggest that FGAs are overprescribed to older patients but that dermatologists are less likely to prescribe FGAs than PCPs. What's already known about this topic? First-generation antihistamines (FGAs) have been shown to pose substantial risks to older adults, including cognitive impairment, falls, confusion, dry mouth and constipation. Therefore, FGAs have been classified as 'potentially inappropriate' for use in older patients by the American Geriatrics Society. It has also been shown that dermatologists do not always take patient characteristics (e.g. age or life expectancy) into account when deciding on a treatment, instead following a 'one-size-fits-all' approach. What does this study add? FGAs are often prescribed during dermatology visits, and prescription rates do not differ between older and younger patients. There were no significant differences in prescription rates when comparing younger and older adults with the same diagnosis or symptom (e.g. dermatitis, pruritus or itch). FGAs are prescribed at higher rates in primary-care offices than in dermatology offices.

Data augmentation in dermatology image recognition using machine learning.

Each year in the United States, over 80 million people are affected by acne, atopic dermatitis, rosacea, psoriasis, and impetigo. Artificial intelligence and machine learning could prove to be a good tool for assisting in the diagnosis of dermatological conditions. The objective of this study was to evaluate the use of data augmentation in machine learning image recognition of five dermatological disease manifestations-acne, atopic dermatitis, impetigo, psoriasis, and rosacea. Open-source dermatological images were gathered and used to retrain TensorFlow Inception version-3. Retraining was done twice-once with and once without data augmentation. Both models were tested with the same images, and R software was used to perform statistical analysis. The average of each of the statistical measures (sensitivity, specificity, PPV, NPN, MCC, and F1 Score) increased when data augmentation was added to the model. In particular, the average Matthews correlation coefficient increased by 7.7%. Each of the five dermatological manifestations had an increase in area under the curve (AUC) after data augmentation with the average increase in AUC of 0.132 and a standard deviation of 0.033. Atopic dermatitis had the highest increase in AUC of 0.18. With data augmentation, the lowest AUC was 0.87 for psoriasis and the highest was 0.97 for acne, indicating that the model performs well. With a deep learning-based approach, it is possible to differentiate dermatological images with appreciable MCC, F1 score, and AUC. Further, data augmentation can be used to increase the model's accuracy by a significant amount.

Ultrasound in dermatology: Principles and applications

Ultrasonic imaging has been used in the field of dermatology for nearly 30 years. In this review, we seek to explain the basic principles of ultrasound as they relate to the skin. Based on differences in keratin, collagen, and water content, ultrasonic waves are reflected back to a transducer and translated into a gray-scale image for interpretation. The technicalities of the process and its variations (power, continuous wave Doppler ultrasound, ultrasound elastography) are briefly reviewed, and we further highlight many of the applications for ultrasound in the treatment and diagnosis of dermatologic conditions, including melanoma and nonmelanoma skin cancer, benign tumors, inflammatory diseases, and lipoablation. Each of these entities is uniquely characterized using ultrasonic techniques. Based on published sources, we contend that although ultrasound is still being fine-tuned for application in dermatology and largely remains in experimental phases, it has potential for use in many arenas of our specialty.

Progressive Mucinous Histiocytosis: Importance of Electron Microscopy to Confirm Diagnosis

Progressive mucinous histiocytosis (PMH) is a benign, non-Langerhans cell histiocytosis with characteristic ultrastructural features that can be used for diagnosis. Once an important tool in dermatologic diagnosis, electron microscopy has been largely replaced by immunohistochemistry and immunofluorescence techniques today. However, electron microscopy occasionally still plays a crucial role in the diagnosis of dermatologic conditions. We report a case of PMH as an example of a dermatologic disorder that requires electron microscopy for its diagnosis. A 60-year-old woman presented to our clinic with a history of small, sharply demarcated, skin-colored papules ranging from 2 to 5 mm in diameter distributed over the arms, forearms, and dorsal hands. The results of light microscopy, immunohistochemical studies, and clinical examination were inconclusive. Another biopsy for electron microscopy showed the characteristic features of PMH. This case demonstrates that a dermatopathology service still needs to have access to electron microscopy for diagnostic purposes to successfully diagnose a small number of rare conditions.

Transillumination for Diagnosis of Mucinous Pseudocyst of the Finger

To the Editor.— One of the diagnostic aids now rarely used in dermatology is transillumination. A study has been underway for some years in the Department of Dermatology of the University of Cincinnati Medical Center to determine the value and limitations of transillumination techniques for diagnosis of dermatologic conditions by incoherent bright light and also by laser light. If the optical qualities of normal skin of an area are changed by any structures that affect light transmission, absorption, and reflectance, these changes may be shown in a general diffuse fashion by transillumination. Some examples are cysts with and without blood, tumors with and without cystic or calcium changes, foreign bodies, etc. A Welch Allyn transilluminator has been used in these examinations. One of the most constant and clear findings of the value of transillumination is the use of this technique for the examination of mucinous pseudocysts of the finger. In