Multispectral Fundus Photography of Choroidal Nevi With Trans-Palpebral Illumination.

Purpose: The purpose of this study was to investigate the spectral characteristics of choroidal nevi and assess the feasibility of quantifying the basal diameter of choroidal nevi using multispectral fundus images captured with trans-palpebral illumination. Methods: The study used a widefield fundus camera with multispectral (625 nm, 780 nm, 850 nm, and 970 nm) trans-palpebral illumination to examine eight subjects diagnosed with choroidal nevi. Geometric features of nevi, including border clarity, overlying drusen, and lesion basal diameter, were characterized. Clinical imagers, including scanning laser ophthalmoscopy (SLO), autofluorescence (AF), and optical coherence tomography (OCT), were utilized for comparative assessment. Results: Fundus images depicted nevi as dark regions with high contrast against the background. Near-infrared (NIR) fundus images provided enhanced visibility of lesion borders compared to visible fundus images and SLO images. Lesion-background contrast measurements revealed 635 nm SLO at 11% and 625 nm fundus at 42%. Significantly enhanced contrasts were observed in NIR fundus images at 780 nm (73%), 850 nm (63%), and 970 nm (67%). For quantifying the diameter of nevi, NIR fundus images at 780 nm and 850 nm yielded a deviation of less than 10% when compared to OCT measurements. Conclusions: NIR fundus photography with trans-palpebral illumination enhances nevi visibility and boundary definition compared to SLO. Agreement in diameter measurements with OCT validates the accuracy and reliability of this method for choroidal nevi assessment. Translational Relevance: Multispectral fundus imaging with trans-palpebral illumination improves choroidal nevi visibility and accurately measures basal diameter, promising to enhance clinical practices in screening, diagnosis, and monitoring of choroidal nevi.

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)

Understanding choroidal nevus risk factors for transformation into melanoma.

A choroidal nevus is a common intraocular tumor in the United States, found in approximately 5% of Caucasian adults. The three main risks of melanocytic choroidal nevus include vision loss from a subfoveal nevus, development of subretinal fluid, and transformation of nevus into melanoma, a malignant counterpart. We explore clinical risk factors that predict benign melanocytic choroidal nevus transformation into a malignant choroidal melanoma. Based on a large analysis of 2,355 cases that were monitored longitudinally using multimodal imaging, the most recent list of clinical features includes tumor Thickness greater than 2 mm on ultrasonography, subretinal Fluid on optical coherence tomography, Symptomatic vision loss 20/50 or worse, Orange pigment on fundus autofluorescence, Melanoma hollow on ultrasonography, and DIaMeter greater than 5 mm on fundus photography. These factors are remembered with a mnemonic of the capital letters TFSOM-DIM for "To Find Small Ocular Melanoma Doing Imaging." Analysis of these factors demonstrated a Kaplan-Meier mean five-year risk of 1% with no risk factors, 11% with any one factor, 22% with any two factors, 34% with any three factors, 51% with any four factors, and 55% with any five factors. There was no patient with six risk factors. Of those with combinations of four risk factors, six of 15 combinations yielded a 70%-100% rate of transformation; of those with combinations of five risk factors, two of five combinations yielded a 70%-100% rate of transformation. Choroidal nevus carries a risk for evolving into melanoma, and understanding of clinical and imaging features predictive of this outcome is highly important.

Melanoma clinicopathological groups characterized and compared with dermoscopy and reflectance confocal microscopy.

BACKGROUND: Dermoscopic and reflectance confocal microscopy (RCM) correlations between morphologic groups of melanoma have not yet been described. OBJECTIVE: Describe and compare dermoscopic and RCM features of cutaneous melanomas with histopathological confirmation. METHODS: Single center, retrospective analysis of consecutive melanomas evaluated with RCM (2015-2019). Lesions were clinically classified as typical, nevus-like, amelanotic/nonmelanoma skin cancer (NMSC)-like, seborrheic keratosis (SK)-like and lentigo/lentigo maligna (LM)-like. Presence or absence of common facial and nonfacial melanoma dermoscopic and RCM patterns were recorded. Clusters were compared with typical lesions by multivariate logistic regression. RESULTS: Among 583 melanoma lesions, significant differences between clusters were evident (compared to typical lesions). Observation of dermoscopic features (>50% of lesions) in amelanotic/NMSC-like lesions consistently displayed 3 patterns (atypical network, atypical vascular pattern + regression structures), and nevus-like and SK-like lesions and lentigo/LM-like lesions consistently displayed 2 patterns (atypical network + regression structures, and nonevident follicles + heavy pigmentation intensity). Differences were less evident with RCM, as almost all lesions were consistent with melanoma diagnosis. LIMITATIONS: Small SK-like lesions sample, single RCM analyses (no reproduction of outcome). CONCLUSION: RCM has the potential to augment our ability to consistently and accurately diagnose melanoma independently of clinical and dermoscopic features.

Ultrasonographic findings in nevus lipomatosus cutaneous superficialis: What differentiates this tumor from other soft tissue tumors?

Nevus lipomatosus cutaneous superficialis is a rare, benign hamartoma characterized by mature adipocyte proliferation in the dermis. It is frequently difficult to distinguish clinically from soft tissue tumors, including lipoma, neurofibroma, venous malformation, and angiolipoma. Notably, the classical form, which shows multiple and sometimes enlarged nodules, is difficult to differentiate from liposarcoma based on clinical examination, computed tomography, and magnetic resonance imaging findings. Therefore, to ascertain the utility of ultrasonography in diagnosing nevus lipomatosus cutaneous superficialis, sonographic examinations were performed on eight patients with nevus lipomatosus cutaneous superficialis. All patients had ill-defined hyperechoic masses in the dermis or from the dermis to the subcutis, and the posterior echoes were attenuated in seven patients. Color Doppler sonography revealed no blood flow to the lesions. Ultrasound images were created using the reflections of ultrasound waves at interfaces with different acoustic impedances. Therefore, it is assumed that, in nevus lipomatosus cutaneous superficialis, the ultrasound beam is scattered by ectopic mature adipocytes intermingled with collagen bundles, which are shown as hyperechoic masses. Furthermore, the scattering of the ultrasound beam is thought to reduce tissue penetration, which may attenuate the posterior echo.

Polarization-Diversity Optical Coherence Tomography Assessment of Choroidal Nevi.

Purpose: The purpose of this study was to demonstrate the utility of polarization-diversity optical coherence tomography (PD-OCT), a noninvasive imaging technique with melanin-specific contrast, in the quantitative and qualitative assessment of choroidal nevi. Methods: Nevi were imaged with a custom-built 55-degree field-of-view (FOV) 400 kHz PD-OCT system. Imaging features on PD-OCT were compared to those on fundus photography, auto-fluorescence, ultrasound, and non-PD-OCT images. Lesions were manually segmented for size measurement and metrics for objective assessment of melanin distributions were calculated, including degree of polarization uniformity (DOPU), attenuation coefficient, and melanin occupancy rate (MOR). Results: We imaged 17 patients (mean age = 69.5 years, range = 37-90) with 11 pigmented, 3 non-pigmented, and 3 mixed pigmentation nevi. Nevi with full margin acquisition had an average longest basal diameter of 5.1 mm (range = 2.99-8.72 mm) and average height of 0.72 mm (range = 0.37 mm-2.09 mm). PD-OCT provided clear contrast of choroidal melanin content, distribution, and delineation of nevus margins for melanotic nevi. Pigmented nevi were found to have lower DOPU, higher attenuation coefficient, and higher MOR than non-pigmented lesions. Melanin content on PD-OCT was consistent with pigmentation on fundus in 15 of 17 nevi (88%). Conclusions: PD-OCT allows objective assessment of choroidal nevi melanin content and distribution. In addition, melanin-specific contrast by PD-OCT enables clear nevus margin delineation and may improve serial growth surveillance. Further investigation is needed to determine the clinical significance and prognostic value of melanin characterization by PD-OCT in the evaluation of choroidal nevi.

Refining skin lesions classification performance using geometric features of superpixels.

This paper introduces superpixels to enhance the detection of skin lesions and to discriminate between melanoma and nevi without false negatives, in dermoscopy images. An improved Simple Linear Iterative Clustering (iSLIC) superpixels algorithm for image segmentation in digital image processing is proposed. The local graph cut method to identify the region of interest (i.e., either the nevi or melanoma lesions) has been adopted. The iSLIC algorithm is then exploited to segment sSPs. iSLIC discards all the SPs belonging to image background based on assigned labels and preserves the segmented skin lesions. A shape and geometric feature extraction task is performed for each segmented SP. The extracted features are fed into six machine learning algorithms such as: random forest, support vector machines, AdaBoost, k-nearest neighbor, decision trees (DT), Gaussian Naïve Bayes and three neural networks. These include Pattern recognition neural network, Feed forward neural network, and 1D Convolutional Neural Network for classification. The method is evaluated on the 7-Point MED-NODE and PAD-UFES-20 datasets and the results have been compared to the state-of-art findings. Extensive experiments show that the proposed method outperforms the compared existing methods in terms of accuracy.

Comparative dermoscopy assessment of nevus-associated versus de novo in situ melanoma.

BACKGROUND: Dermoscopic features differentiating in situ nevus-associated melanoma (NAM) versus in situ de novo melanoma (DNM) are inconclusive. OBJECTIVES: The aim of the study was to investigate the dermoscopic features associated with in situ NAM versus DNM. MATERIALS & METHODS: This was a retrospective observational study. All consecutive in situ melanomas diagnosed in adult patients were retrieved and stratified as NAM vs DNM, and clinical and dermoscopic data were compared between the two. RESULTS: A total of 183 patients with in situ melanoma were collected, of whom 98 (54%) were male with a mean age of 64±14 years. For 129 patients, standardized dermoscopic images were collected (51 for NAM and 78 for de novo MM). The most common dermoscopic features were an atypical pigment network (85%), atypical globules (63%) and regression (42%). No significant differences were found except for regression, which was detected in 54.9% NAM vs 33.3% DNM (p=0.016). Multivariate logistic regression confirmed the association between dermoscopic regression and NAM (OR=2.34, 95% CI: 1.15-4.91). CONCLUSION: Currently, the use of dermoscopy to determine whether a melanoma is associated with a nevus is unreliable, however, the presence of regression adjacent to atypical lesions may raise suspicion of in situ NAM.

Optical coherence tomography confirms non-malignant pigmented lesions in phacomatosis pigmentokeratotica using a support vector machine learning algorithm.

INTRODUCTION: Phacomatosis pigmentokeratotica (PPK), an epidermal nevus syndrome, is characterized by the coexistence of nevus spilus and nevus sebaceus. Within the nevus spilus, an extensive range of atypical nevi of different morphologies may manifest. Pigmented lesions may fulfill the ABCDE criteria for melanoma, which may prompt a physician to perform a full-thickness biopsy. MOTIVATION: Excisions result in pain, mental distress, and physical disfigurement. For patients with a significant number of nevi with morphologic atypia, it may not be physically feasible to biopsy a large number of lesions. Optical coherence tomography (OCT) is a non-invasive imaging modality that may be used to visualize non-melanoma and melanoma skin cancers. MATERIALS AND METHOD: In this study, we used OCT to image pigmented lesions with morphologic atypia in a patient with PPK and assessed their quantitative optical properties compared to OCT cases of melanoma. We implement a support vector machine learning algorithm with Gabor wavelet transformation algorithm during post-image processing to extract optical properties and calculate attenuation coefficients. RESULTS: The algorithm was trained and tested to extract and classify textural data. CONCLUSION: We conclude that implementing this post-imaging machine learning algorithm to OCT images of pigmented lesions in PPK has been able to successfully confirm benign optical properties. Additionally, we identified remarkable differences in attenuation coefficient values and tissue optical characteristics, further defining separating benign features of pigmented lesions in PPK from malignant features.

Survey of ophthalmic imaging use to assess risk of progression of choroidal nevus to melanoma.

BACKGROUND/OBJECTIVES: The aim of this study was to ascertain the use of ocular imaging and the updated screening criteria in the evaluation of choroidal nevus across the United States. METHODS: Sixty ophthalmologists completed an anonymous 21-question survey addressing their use of the screening criteria for evaluating choroidal nevi, as well as their use of ultrasonography (US), optical coherence tomography (OCT), and autofluorescence (AF) in daily practice. RESULTS: The majority of respondents were from the Northeast (55%), worked in private practice (83%), and practiced general ophthalmology (42%). The 2009 criteria TFSOM-UHHD was used by 39 (65%) respondents, while the 2019 criteria TFSOM-DIM was used by 29 (48%) respondents. Compared to anterior segment ophthalmologists, posterior segment ophthalmologists were more likely to use the TFSOM-UHHD criteria (94% vs. 53%, OR = 13.9, p = 0.014), the TFSOM-DIM criteria (88% vs. 33%, OR = 15.5, p < 0.001), fundus AF (82% vs. 19%, OR = 20.4, p < 0.001), and US (94% vs. 42%, OR = 22.2, p = 0.004) in daily practice. CONCLUSIONS: From the survey of current practice patterns, we learned that there is a general trend of underutilization of the proper imaging modalities - and thus the criteria - in evaluating choroidal nevus. More education about ocular cancer and its screening could improve patient outcomes in the future.

Computer Aided Diagnosis of Melanoma Using Deep Neural Networks and Game Theory: Application on Dermoscopic Images of Skin Lesions.

Early detection of melanoma remains a daily challenge due to the increasing number of cases and the lack of dermatologists. Thus, AI-assisted diagnosis is considered as a possible solution for this issue. Despite the great advances brought by deep learning and especially convolutional neural networks (CNNs), computer-aided diagnosis (CAD) systems are still not used in clinical practice. This may be explained by the dermatologist's fear of being misled by a false negative and the assimilation of CNNs to a "black box", making their decision process difficult to understand by a non-expert. Decision theory, especially game theory, is a potential solution as it focuses on identifying the best decision option that maximizes the decision-maker's expected utility. This study presents a new framework for automated melanoma diagnosis. Pursuing the goal of improving the performance of existing systems, our approach also attempts to bring more transparency in the decision process. The proposed framework includes a multi-class CNN and six binary CNNs assimilated to players. The players' strategies is to first cluster the pigmented lesions (melanoma, nevus, and benign keratosis), using the introduced method of evaluating the confidence of the predictions, into confidence level (confident, medium, uncertain). Then, a subset of players has the strategy to refine the diagnosis for difficult lesions with medium and uncertain prediction. We used EfficientNetB5 as the backbone of our networks and evaluated our approach on the public ISIC dataset consisting of 8917 lesions: melanoma (1113), nevi (6705) and benign keratosis (1099). The proposed framework achieved an area under the receiver operating curve (AUROC) of 0.93 for melanoma, 0.96 for nevus and 0.97 for benign keratosis. Furthermore, our approach outperformed existing methods in this task, improving the balanced accuracy (BACC) of the best compared method from 77% to 86%. These results suggest that our framework provides an effective and explainable decision-making strategy. This approach could help dermatologists in their clinical practice for patients with atypical and difficult-to-diagnose pigmented lesions. We also believe that our system could serve as a didactic tool for less experienced dermatologists.

Three-dimensional representation of triple spectral line imaging data as an option for noncontact skin diagnostics.

SIGNIFICANCE: Skin malformations in dermatology are mostly evaluated subjectively, based on a doctor's experience and visual perception; an option for objective quantitative skin assessment is camera-based spectrally selective diagnostics. Multispectral imaging is a technique capable to provide information about concentrations of the absorbing chromophores and their distribution over the malformation in a noncontact way. Conversion of spectral images into distribution maps of chromophores can be performed by means of the modified Beer-Lambert law. However, such distribution maps represent only single specific cases, therefore, some extensive method for data comparison is needed. AIM: This study aims to develop a more informative approach for identification and characterization of skin malformations using three-dimensional (3D) representation of triple spectral line imaging data. APPROACH: The 3D-representation method is experimentally tested on eight different skin pathology types, including both benign and malignant pathologies; an imaging device ensuring uniform three laser line (448, 532, and 659 nm) illumination is used. Three spectral line images are extracted from a single snapshot RGB image data, with subsequent calculation of attenuation coefficients for each working wavelength at every image pixel and represented as 3D graphs. Skin chromophore content variations in malformations are represented in a similar way. RESULTS: Clinical measurement results for 99 skin pathologies, including basal cell carcinomas, melanoma, dermal nevi, combined nevi, junctional nevi, blue nevi, seborrheic keratosis, and hemangiomas. They are presented as 3D spectral attenuation maps exhibiting specific individual features for each group of pathologies. Along with intensity attenuation maps, 3D maps for content variations of three main skin chromophores (melanin, oxyhemoglobin, and deoxyhemoglobin), calculated in frame of a model based on modified Beer-Lambert law, are also presented. Advantages and disadvantages of the proposed data representation method are discussed. CONCLUSIONS: The described 3D-representation method of triple spectral line imaging data shows promising potential for objective quantitative noncontact diagnosis of skin pathologies.

Dermoscopic Image Classification of Pigmented Nevus under Deep Learning and the Correlation with Pathological Features.

The objective of this study was to explore the image classification and case characteristics of pigmented nevus (PN) diagnosed by dermoscopy under deep learning. 268 patients were included as the research objects and they were randomly divided into observation group (n = 134) and control group (n = 134). Image recognition algorithm was used for feature extraction, segmentation, and classification of dermoscopic images, and the image recognition and classification algorithm were studied as the performance and accuracy of fusion classifier were compared. The results showed that the classifier was optimized, and the linear kernel accuracy was 85.82%. The PN studied mainly included mixed nevus, junctional nevus, intradermal nevus, and acral nevus. The sensitivity under collaborative training was higher than that under feature training and fusion feature training, and the differences among three trainings were significant (P < 0.05). The sensitivity of the observation group was 88.65%, and the specificity was 90.26%, while the sensitivity and the specificity of the control group were 85.65% and 84.03%, respectively; there were significant differences between the two groups (P < 0.05). In conclusion, dermoscopy under deep learning could be applied as a diagnostic way of PN, which helped improve the accuracy of diagnosis. The dermoscopic manifestations of PN showed a certain corresponding relationship with the type of cases and could provide auxiliary diagnosis in clinical practice. It could be applied clinically.

Digital dermoscopy monitoring of melanocytic lesions: Two novel calculators combining static and dynamic features to identify melanoma.

BACKGROUND: Early diagnosis is the most effective intervention to improve the prognosis of cutaneous melanoma. Even though the introduction of dermoscopy has improved the diagnostic accuracy, it can still be difficult to distinguish some melanomas from benign melanocytic lesions. Digital dermoscopy monitoring can identify dynamic changes of melanocytic lesions: To date, some algorithms were proposed, but a universally accepted one is still lacking. OBJECTIVES: To identify independent predictive variables associated with the diagnosis of cutaneous melanoma and develop a multivariable dermoscopic prediction model able to discriminate benign from malignant melanocytic lesions undergoing digital dermoscopy monitoring. METHODS: We collected dermoscopic images of melanocytic lesions excised after dermoscopy monitoring and carried out static and dynamic evaluations of dermoscopic features. We built two multivariable predictive models based on logistic regression and random forest. RESULTS: We evaluated 173 lesions (65 cutaneous melanomas and 108 nevi). Forty-two melanomas were in situ, and the median thickness of invasive melanomas was 0.35 mm. The median follow-up time was 9.8 months for melanomas and 9.1 for nevi. The logistic regression and random forest models performed with AUC values of 0.87 and 0.89, respectively, were substantially higher than those of the static evaluation models (ABCD TDS score, 0.57; 7-point checklist, 0.59). Finally, we built two risk calculators, which translate the proposed models into user-friendly applications, to assist clinicians in the decision-making process. CONCLUSIONS: The present study demonstrates that the integration of dynamic and static evaluations of melanocytic lesions is a safe approach that can significantly boost the diagnostic accuracy for cutaneous melanoma. We propose two diagnostic tools that significantly increase the accuracy in discriminating melanoma from nevi during digital dermoscopy monitoring.

Reproducible Naevus Counts Using 3D Total Body Photography and Convolutional Neural Networks.

BACKGROUND: The number of naevi on a person is the strongest risk factor for melanoma; however, naevus counting is highly variable due to lack of consistent methodology and lack of inter-rater agreement. Machine learning has been shown to be a valuable tool for image classification in dermatology. OBJECTIVES: To test whether automated, reproducible naevus counts are possible through the combination of convolutional neural networks (CNN) and three-dimensional (3D) total body imaging. METHODS: Total body images from a study of naevi in the general population were used for the training (82 subjects, 57,742 lesions) and testing (10 subjects; 4,868 lesions) datasets for the development of a CNN. Lesions were labelled as naevi, or not ("non-naevi"), by a senior dermatologist as the gold standard. Performance of the CNN was assessed using sensitivity, specificity, and Cohen's kappa, and evaluated at the lesion level and person level. RESULTS: Lesion-level analysis comparing the automated counts to the gold standard showed a sensitivity and specificity of 79% (76-83%) and 91% (90-92%), respectively, for lesions ≥2 mm, and 84% (75-91%) and 91% (88-94%) for lesions ≥5 mm. Cohen's kappa was 0.56 (0.53-0.59) indicating moderate agreement for naevi ≥2 mm, and substantial agreement (0.72, 0.63-0.80) for naevi ≥5 mm. For the 10 individuals in the test set, person-level agreement was assessed as categories with 70% agreement between the automated and gold standard counts. Agreement was lower in subjects with numerous seborrhoeic keratoses. CONCLUSION: Automated naevus counts with reasonable agreement to those of an expert clinician are possible through the combination of 3D total body photography and CNNs. Such an algorithm may provide a faster, reproducible method over the traditional in person total body naevus counts.