Enhancing assisted diagnostic accuracy in scalp psoriasis: A Multi-Network Fusion Object Detection Framework for dermoscopic pattern diagnosis.

BACKGROUND: Dermoscopy is a common method of scalp psoriasis diagnosis, and several artificial intelligence techniques have been used to assist dermoscopy in the diagnosis of nail fungus disease, the most commonly used being the convolutional neural network algorithm; however, convolutional neural networks are only the most basic algorithm, and the use of object detection algorithms to assist dermoscopy in the diagnosis of scalp psoriasis has not been reported. OBJECTIVES: Establishment of a dermoscopic modality diagnostic framework for scalp psoriasis based on object detection technology and image enhancement to improve diagnostic efficiency and accuracy. METHODS: We analyzed the dermoscopic patterns of scalp psoriasis diagnosed at 72nd Group army hospital of PLA from January 1, 2020 to December 31, 2021, and selected scalp seborrheic dermatitis as a control group. Based on dermoscopic images and major dermoscopic patterns of scalp psoriasis and scalp seborrheic dermatitis, we investigated a multi-network fusion object detection framework based on the object detection technique Faster R-CNN and the image enhancement technique contrast limited adaptive histogram equalization (CLAHE), for assisting in the diagnosis of scalp psoriasis and scalp seborrheic dermatitis, as well as to differentiate the major dermoscopic patterns of the two diseases. The diagnostic performance of the multi-network fusion object detection framework was compared with that between dermatologists. RESULTS: A total of 1876 dermoscopic images were collected, including 1218 for scalp psoriasis versus 658 for scalp seborrheic dermatitis. Based on these images, training and testing are performed using a multi-network fusion object detection framework. The results showed that the test accuracy, specificity, sensitivity, and Youden index for the diagnosis of scalp psoriasis was: 91.0%, 89.5%, 91.0%, and 0.805, and for the main dermoscopic patterns of scalp psoriasis and scalp seborrheic dermatitis, the diagnostic results were: 89.9%, 97.7%, 89.9%, and 0.876. Comparing the diagnostic results with those of five dermatologists, the fusion framework performs better than the dermatologists' diagnoses. CONCLUSIONS: Studies have shown some differences in dermoscopic patterns between scalp psoriasis and scalp seborrheic dermatitis. The proposed multi-network fusion object detection framework has higher diagnostic performance for scalp psoriasis than for dermatologists.

DVFNet: A deep feature fusion-based model for the multiclassification of skin cancer utilizing dermoscopy images.

Skin cancer is a common cancer affecting millions of people annually. Skin cells inside the body that grow in unusual patterns are a sign of this invasive disease. The cells then spread to other organs and tissues through the lymph nodes and destroy them. Lifestyle changes and increased solar exposure contribute to the rise in the incidence of skin cancer. Early identification and staging are essential due to the high mortality rate associated with skin cancer. In this study, we presented a deep learning-based method named DVFNet for the detection of skin cancer from dermoscopy images. To detect skin cancer images are pre-processed using anisotropic diffusion methods to remove artifacts and noise which enhances the quality of images. A combination of the VGG19 architecture and the Histogram of Oriented Gradients (HOG) is used in this research for discriminative feature extraction. SMOTE Tomek is used to resolve the problem of imbalanced images in the multiple classes of the publicly available ISIC 2019 dataset. This study utilizes segmentation to pinpoint areas of significantly damaged skin cells. A feature vector map is created by combining the features of HOG and VGG19. Multiclassification is accomplished by CNN using feature vector maps. DVFNet achieves an accuracy of 98.32% on the ISIC 2019 dataset. Analysis of variance (ANOVA) statistical test is used to validate the model's accuracy. Healthcare experts utilize the DVFNet model to detect skin cancer at an early clinical stage.

Analysis of dermoscopy images of multi-class for early detection of skin lesions by hybrid systems based on integrating features of CNN models.

Skin cancer is one of the most fatal skin lesions, capable of leading to fatality if not detected in its early stages. The characteristics of skin lesions are similar in many of the early stages of skin lesions. The AI in categorizing diverse types of skin lesions significantly contributes to and helps dermatologists to preserve patients' lives. This study introduces a novel approach that capitalizes on the strengths of hybrid systems of Convolutional Neural Network (CNN) models to extract intricate features from dermoscopy images with Random Forest (Rf) and Feed Forward Neural Networks (FFNN) networks, leading to the development of hybrid systems that have superior capabilities early detection of all types of skin lesions. By integrating multiple CNN features, the proposed methods aim to improve the robustness and discriminatory capabilities of the AI system. The dermoscopy images were optimized for the ISIC2019 dataset. Then, the area of the lesions was segmented and isolated from the rest of the image by a Gradient Vector Flow (GVF) algorithm. The first strategy for dermoscopy image analysis for early diagnosis of skin lesions is by the CNN-RF and CNN-FFNN hybrid models. CNN models (DenseNet121, MobileNet, and VGG19) receive a region of interest (skin lesions) and produce highly representative feature maps for each lesion. The second strategy to analyze the area of skin lesions and diagnose their type by means of CNN-RF and CNN-FFNN hybrid models based on the features of the combined CNN models. Hybrid models based on combined CNN features have achieved promising results for diagnosing dermoscopy images of the ISIC 2019 dataset and distinguishing skin cancers from other skin lesions. The Dense-Net121-MobileNet-RF hybrid model achieved an AUC of 95.7%, an accuracy of 97.7%, a precision of 93.65%, a sensitivity of 91.93%, and a specificity of 99.49%.

Photoaging assessment by Glogau classification: correlation of dermoscopy findings in the coastal population of Indonesia.

INTRODUCTION: To date, there is no gold standard for identifying photoaging. This study investigates the correlation of photoaging profiles based on the Glogau scale and the dermoscopy photoaging scale (DPAS) in a coastal population. METHODS: An analytical cross-sectional study was conducted at Cilincing Municipal Health Center in Jakarta in October 2022. Individuals living in the coastal area, 20 years and older, with Fitzpatrick skin types III-V, and with a mean daily sun exposure of ≥ 3 hours were included. The Glogau scale and DPAS were assessed through history taking, physical examination, and dermoscopic examination. A Spearman correlation test was used to assess the correlation between the Glogau scale and DPAS. RESULTS: Thirty individuals with a mean age of 41.5 ± 11.5 years participated in the study. The median Glogau score was 3 (range: 2-4). The mean DPAS score was 28.5 ± 5.6. Lentigo, hypo-hyperpigmented macules, telangiectasia, deep wrinkles, and superficial wrinkles were observed in all subjects. There was a moderate positive correlation between the Glogau scale and DPAS (r = 0.536, p = 0.002). CONCLUSIONS: The Glogau scale has a significant correlation with DPAS. DPAS can serve as a reliable, easy, practical, and fast diagnostic tool to assess the severity of aging.

Diagnostic and grading criteria for androgenetic alopecia using dermoscopy.

OBJECTIVES: To establish accurate and objective dermoscopic diagnostic criteria and grading standards for males and females with androgenetic alopecia (AGA). METHODS: Twenty patients each with AGA, diffuse alopecia areata, telogen effluvium, and healthy controls were enrolled in the current study. In addition, 60 patients with grades F1/V1, F2/V2, and F3/V3 AGA (20 cases each) were enrolled. The patients underwent dermoscopic examinations. The sensitivity and specificity of the diagnostic criteria were based on the 60 AGA and 60 non-AGA. In addition, 150 patients diagnosed with AGA clinically and by dermoscopy were enrolled to calculate the accuracy of the grading criteria. RESULTS: The diagnostic criteria included primary, secondary, and exclusion criteria. The grading criteria included three indices, which divided the severity of AGA into grades 1, 2, and 3. The sensitivity and specificity of the diagnostic criteria were 98.3% and 96.7% respectively. The accuracy of grade 1, 2, and 3 dermoscopic grading criteria were 96%, 92%, and 100% respectively, with a total accuracy of 96%. LIMITATIONS: To test the diagnostic and grading criteria, more patients need to be collected. CONCLUSIONS: The dermoscopic diagnostic and grading criteria are objective with good accuracy, which could provide a reasonable basis for the early diagnosis, grading treatment, and improved prognosis for AGA.

Onychocytic Matricoma: A Clinical, Dermoscopic, and Pathological Analysis of 14 Cases.

ABSTRACT: Onychocytic matricoma (OCM) is a benign neoplasm of the nail matrix. Only 18 cases of this tumor have been reported in the literature to date. We retrospectively analyzed the clinical features of 14 patients with OCM. The most common clinical feature was longitudinal xanthopachyonychia (n = 9), followed by longitudinal leukopachyonychia (=3) and longitudinal pachymelanonychia (n = 2). The most common clinical findings identified following dermoscopy and analysis at high magnification of classical photographs were free-edge thickening of the nail plate without pitting (n = 14), longitudinal ridging (n = 7), round white clods (n = 7), white dots (n = 7), and filiform hemorrhages (n = 7), followed by oval and linear white clods (n = 5), fuzzy lateral border (n = 5), and red-purple blood clods (n = 3). Nail clipping histopathology showed a thickened nail plate with multiple, small, round-to-oval spaces. The tumor expressed immunopositivity for LEF-1. Dermoscopy of the nail plate and nail clipping histology provides useful information with regards to the differential diagnosis with subungual squamous cell carcinoma and nail melanoma. Ex vivo-in vivo correlation facilitates a better dermoscopic assessment of this unique underrecognized disease. However, the differential diagnosis between OCM and onychocytic carcinoma requires biopsy of the tumor. LEF-1 as an onychogenic marker can be used to resolve the differential diagnosis between OCM and subungual longitudinal acanthoma/seborrheic keratosis.

Cambios en la dermatoscopia digital en lesiones melanocíticas en 368 pacientes con diagnóstico de síndrome de nevus atípicos y su asociación con el desarrollo de melanoma: estudio de cohorte / Dermoscopic Changes in Melanocytic Lesions in 368 Patients With Atypical Nevus Syndrome and Their Association With Melanoma Incidence: A Cohort Study

Antecedentes y objetivo El síndrome de nevus atípico se ha considerado uno de los factores más importantes para el desarrollo de melanoma. El objetivo de este estudio fue describir los cambios dermatoscópicos de las lesiones melanocíticas en pacientes con diagnóstico de síndrome de nevus atípicos, durante el seguimiento digital en 5 años. Material y métodos Se realizó un estudio retrospectivo de seguimiento a una cohorte de pacientes atendidos en un consultorio particular, especializado en cáncer de piel y mapeo digital corporal, localizado en Medellín (Colombia), entre enero de 2017 y diciembre de 2022. Se analizaron las características dermatoscópicas encontradas y su relación con el diagnóstico de un melanoma. Resultados Se incluyeron 368 pacientes, con una mediana de edad de 43 años RIQ (37-51) de los cuales,187 fueron mujeres. Al finalizar el seguimiento, 222 (60,3%) presentaron red atípica, 163 (44,2%) glóbulos asimétricos, 105 (28,5%) regresión blanco gris, 72 (19,5%) regresión de la lesión, 59 (16%) retículo invertido, 28 (7,6%) pigmento excéntrico asimétrico, 21 (5,7%) proyecciones asimétricas y 8 (2,1%) asimetría en el patrón vascular. A los 60 meses de seguimiento a un 12,2% se les diagnosticó un melanoma. Las áreas blanco-grisáceas, los glóbulos asimétricos, el pigmento excéntrico asimétrico y el retículo invertido fueron las estructuras dermatoscópicas que se relacionaron significativamente con un tiempo menor para la presentación de melanoma (p<0,001, p=0,011, p=0,047 y p=0,001, respectivamente). Conclusiones En conclusión, se encontró que las principales características dermatoscópicas de las lesiones melanocíticas en pacientes con nevus displásicos relacionadas con la progresión a melanoma fueron la aparición de áreas blanco-grisáceas, los glóbulos asimétricos, las manchas asimétricas y el retículo invertido (AU)

Background and objective Atypical nevus syndrome has been described as one of the main risk factors for melanoma. The aim of this study was to analyze dermoscopic changes observed in melanocytic lesions over a follow-up period of 5 years in patients with atypical nevus syndrome. Material and methods We conducted a retrospective follow-up study of a cohort of patients seen at a specialized skin cancer and digital body mapping clinic in Medellin, Colombia, between January 2017 and December 2022. We analyzed the dermoscopic changes observed during this period and explored their association with newly diagnosed melanoma. Results A total of 368 patients (187 women) with a median (interquartile range) age of 43 (37-51) years were included. The dermoscopic features observed at 5 years were an atypical network (222 patients, 60.3%), asymmetric globules (163, 44.2%), white-gray regression areas (105, 28.5%), lesion regression (72, 19.5%), a negative pigment network (59, 16%), asymmetric eccentric pigmentation (28, 7.6%), asymmetric projections (21, 5.7%), and asymmetric vascular patterns (8, 2.1%). Melanoma was diagnosed in 12.2% of patients during follow-up. Features significantly associated with a shorter time to melanoma onset were grayish-white areas (P <.001), asymmetric globules (P=.011), asymmetric eccentric pigmentation (P=.047), and a negative pigment network (P=.001). Conclusions The main dermoscopic features of melanocytic lesions in patients with atypical nevus syndrome associated with progression to melanoma were grayish-white areas, asymmetric globules, asymmetric spots, and a negative pigment network (AU)

[Translated article] Dermoscopic Changes in Melanocytic Lesions in 368 Patients With Atypical Nevus Syndrome and Their Association With Melanoma Incidence: A Cohort Study / Cambios en la dermatoscopia digital en lesiones melanocíticas en 368 pacientes con diagnóstico de síndrome de nevus atípicos y su asociación con el desarrollo de melanoma: estudio de cohorte

Background and objective Atypical nevus syndrome has been described as one of the main risk factors for melanoma. The aim of this study was to analyze dermoscopic changes observed in melanocytic lesions over a follow-up period of 5 years in patients with atypical nevus syndrome. Material and methods We conducted a retrospective follow-up study of a cohort of patients seen at a specialized skin cancer and digital body mapping clinic in Medellin, Colombia, between January 2017 and December 2022. We analyzed the dermoscopic changes observed during this period and explored their association with newly diagnosed melanoma. Results A total of 368 patients (187 women) with a median (interquartile range) age of 43 (37-51) years were included. The dermoscopic features observed at 5 years were an atypical network (222 patients, 60.3%), asymmetric globules (163, 44.2%), white-gray regression areas (105, 28.5%), lesion regression (72, 19.5%), a negative pigment network (59, 16%), asymmetric eccentric pigmentation (28, 7.6%), asymmetric projections (21, 5.7%), and asymmetric vascular patterns (8, 2.1%). Melanoma was diagnosed in 12.2% of patients during follow-up. Features significantly associated with a shorter time to melanoma onset were grayish-white areas (P <.001), asymmetric globules (P=.011), asymmetric eccentric pigmentation (P=.047), and a negative pigment network (P=.001). Conclusions The main dermoscopic features of melanocytic lesions in patients with atypical nevus syndrome associated with progression to melanoma were grayish-white areas, asymmetric globules, asymmetric spots, and a negative pigment network (AU)

Antecedentes y objetivo El síndrome de nevus atípico se ha considerado uno de los factores más importantes para el desarrollo de melanoma. El objetivo de este estudio fue describir los cambios dermatoscópicos de las lesiones melanocíticas en pacientes con diagnóstico de síndrome de nevus atípicos, durante el seguimiento digital en 5 años. Material y métodos Se realizó un estudio retrospectivo de seguimiento a una cohorte de pacientes atendidos en un consultorio particular, especializado en cáncer de piel y mapeo digital corporal, localizado en Medellín (Colombia), entre enero de 2017 y diciembre de 2022. Se analizaron las características dermatoscópicas encontradas y su relación con el diagnóstico de un melanoma. Resultados Se incluyeron 368 pacientes, con una mediana de edad de 43 años RIQ (37-51) de los cuales,187 fueron mujeres. Al finalizar el seguimiento, 222 (60,3%) presentaron red atípica, 163 (44,2%) glóbulos asimétricos, 105 (28,5%) regresión blanco gris, 72 (19,5%) regresión de la lesión, 59 (16%) retículo invertido, 28 (7,6%) pigmento excéntrico asimétrico, 21 (5,7%) proyecciones asimétricas y 8 (2,1%) asimetría en el patrón vascular. A los 60 meses de seguimiento a un 12,2% se les diagnosticó un melanoma. Las áreas blanco-grisáceas, los glóbulos asimétricos, el pigmento excéntrico asimétrico y el retículo invertido fueron las estructuras dermatoscópicas que se relacionaron significativamente con un tiempo menor para la presentación de melanoma (p<0,001, p=0,011, p=0,047 y p=0,001, respectivamente). Conclusiones En conclusión, se encontró que las principales características dermatoscópicas de las lesiones melanocíticas en pacientes con nevus displásicos relacionadas con la progresión a melanoma fueron la aparición de áreas blanco-grisáceas, los glóbulos asimétricos, las manchas asimétricas y el retículo invertido (AU)

Clinicopathological, dermoscopic features and circumstances of diagnosis of amelanotic or hypomelanotic melanoma: A prospective multicentric study in the French private medical sector.

BACKGROUND: Amelanotic or hypomelanotic melanomas (AHM) are difficult to diagnose, and are often diagnosed late, with a high Breslow index and a poor prognosis. PATIENTS AND METHODS: A total of 226 volunteer dermatologists consulting in private practice in France completed an online form for each new histologically proven case of melanoma diagnosed at their clinic in 2020. This anonymised survey collected data on the clinical, dermoscopic, and histological features of melanoma, as well as the circumstances of diagnosis and initial management. A group of 145 AHM was single out and compared to the 1503 pigmented melanomas (PM) from the same cohort. RESULTS: 1503 pigmented melanomas (PM) and 145 AHM (8.8% of these melanomas) were identified and included. In the AHM group, the mean age at diagnosis was 65 ±â€¯16 years, with no significant difference from the PM control group. AHM were not predominantly on the face and neck area, and there were no differences based on gender. Warning signs (local progression and bleeding) were significantly more frequent in the AHM group than in the PM group. AHM were more frequently ulcerated and nodular, with a higher median Breslow thickness than in the PM group (1.56 vs. 0.5 mm), and mitoses were more frequent. Dermoscopy was widely used and proved useful for distinguishing benign lesions, and for highlighting the vascular polymorphous pattern of malignant lesions. Patients noticed the suspicious lesion themselves in most cases of AHM (73.2%), as opposed to their general practitioner (17.2%) or entourage (9.5%). A total body skin examination enabled detection of 19.3% of AHM and 21.3% of PM where the patient consulted for another lesion, or for an unrelated reason. CONCLUSION: AHM are difficult to diagnose for the clinician because of the paucity or absence of pigmentary criteria. Knowledge of dermoscopic vascular patterns is critical and could help reduce the median Breslow index of AHM at the time of detection. Self-examination of the skin should be encouraged, and simple algorithms for earlier detection of skin cancers should be promoted among health professionals and the general population.