Clinical and Dermoscopic Features of Melanocytic Lesions on the Face Versus the External Ear.

INTRODUCTION: Melanoma of the external ear is a rare condition accounting for 7-20% of all melanomas of the head and neck region. They present classical features of extra-facial melanomas clinically and dermoscopically. In contrast, facial melanomas show peculiar patterns in dermoscopy. OBJECTIVES: To evaluate whether there are clinical and/or dermoscopic differences in melanocytic lesions located either at the external ear or on the face. METHODS: In this retrospective study we reviewed an image database for clinical and dermoscopic images of melanomas and nevi located either on the face or at the level of the external ear. RESULTS: 65 patients (37 men; 63.8%) with 65 lesions were included. We found no significant differences in comparing face melanomas with melanomas at the level of the external ear, neither clinically nor dermoscopically. However, we provided evidence for differences in some clinical and dermoscopic features of melanomas and nevi of the external ear. CONCLUSIONS: In this study, we reported no significant differences in comparing melanomas on the face with melanomas of the external ear, both clinically and dermoscopically. Furthermore, we provided data on clinical and dermoscopic differences comparing nevi and melanoma of the external ear.

Skin lesions of face and scalp - Classification by a market-approved convolutional neural network in comparison with 64 dermatologists.

BACKGROUND: The clinical differentiation of face and scalp lesions (FSLs) is challenging even for trained dermatologists. Studies comparing the diagnostic performance of a convolutional neural network (CNN) with dermatologists in FSL are lacking. METHODS: A market-approved CNN (Moleanalyzer-Pro, FotoFinder Systems) was used for binary classifications of 100 dermoscopic images of FSL. The same lesions were used in a two-level reader study including 64 dermatologists (level I: dermoscopy only; level II: dermoscopy, clinical close-up images, textual information). Primary endpoints were the CNN's sensitivity and specificity in comparison with the dermatologists' management decisions in level II. Generalizability of the CNN results was tested by using four additional external data sets. RESULTS: The CNN's sensitivity, specificity and ROC AUC were 96.2% [87.0%-98.9%], 68.8% [54.7%-80.1%] and 0.929 [0.880-0.978], respectively. In level II, the dermatologists' management decisions showed a mean sensitivity of 84.2% [82.2%-86.2%] and specificity of 69.4% [66.0%-72.8%]. When fixing the CNN's specificity at the dermatologists' mean specificity (69.4%), the CNN's sensitivity (96.2% [87.0%-98.9%]) was significantly higher than that of dermatologists (84.2% [82.2%-86.2%]; p < 0.001). Dermatologists of all training levels were outperformed by the CNN (all p < 0.001). In confirmation, the CNN's accuracy (83.0%) was significantly higher than dermatologists' accuracies in level II management decisions (all p < 0.001). The CNN's performance was largely confirmed in three additional external data sets but particularly showed a reduced specificity in one Australian data set including FSL on severely sun-damaged skin. CONCLUSIONS: When applied as an assistant system, the CNN's higher sensitivity at an equivalent specificity may result in an improved early detection of face and scalp skin cancers.

Melanoma in pregnancy: certainties unborn.

Melanoma diagnosed during childbearing period or up to 1 year after delivery is defined as pregnancy-associated melanoma (PAM). There is some evidence that PAM has worse prognosis if compared with melanoma in nonpregnant women, although literature is still inconclusive. Many biological mechanisms could explain this behavior, such as hormonal and immune status, increased lymphangiogenesis but also delay in diagnostic and therapeutic management. If PAM is suspected, a prompt excisional biopsy under local anesthesia can be performed regardless of the gestational period. Conversely, additional staging procedures (such as sentinel lymph node biopsy or imaging) and systemic therapy are still debatable during pregnancy. A multidisciplinary tailored approach should be preferred, together with exhaustive counseling of the mother.

The importance of total-body photography and sequential digital dermatoscopy for monitoring patients at increased melanoma risk.

BACKGROUND AND OBJECTIVES: The incidence of melanoma is rising and prevention plays an important role. Multiple nevi as well as a medical history of melanoma are important risk factors. In affected patients, a two-step algorithm consisting of total-body photography (TBP) and sequential digital dermatoscopy (SDD) is a helpful diagnostic tool. PATIENTS AND METHODS: This was a retrospective observational study that lasted six years in order to evaluate the significance of the two-step algorithm. Cases were evaluated based on distinct dermoscopic patterns and statistical analyses were performed with the latest version of SPSS. RESULTS: 6020 dermoscopic images of 214 patients were included. TBP was performed at a mean interval of 16.9 months (SD ± 1.43 months), while SDD was performed every 9.9 months (SD ± 1.68 months). The number needed to excise was 4.6 and the number needed to monitor was 548. Excisions were mostly performed because dynamic changes were observed. A total of eleven melanomas were detected and had a mean tumor thickness of 0.44 mm (SD ± 0.15 mm; range 0.2-0.6 mm). CONCLUSIONS: Invasive melanomas had a tumor thickness of less than 0.6 mm, thus providing evidence of an effective strategy for early melanoma detection. Excisions of benign nevi were minimized as indicated by a low number needed to excise.

Clinical and dermoscopic characteristics of congenital and noncongenital nevus-associated melanomas.

BACKGROUND: No specific features of nevus-associated melanoma (NAM) are currently defined. OBJECTIVE: To identify clinical/dermoscopic features of NAM. METHODS: Retrospective evaluation of histopathologically diagnosed NAM. RESULTS: Eighty of 165 NAMs had a clinically recognizable nevus component, often raised or nodular, most frequently characterized by different morphologic clones and/or colors. In 111 of 165 NAMs, dermoscopy showed a nevus component, prevalently characterized by regular dots/clods and structureless brown areas. Clinically, the melanoma component was eccentric/peripheral in 45 of 80 cases and central in 35 of 80; dermoscopically, the figures were 59 of 111 and 52 of 111, respectively. Melanomas associated with congenital nevi (C-NAMs) occur at a younger age and have a thicker Breslow depth than melanomas associated with acquired nevi (NC-NAMs). Dermoscopically, regular dots/globules characterize C-NAMs, and hypopigmented structureless areas characterize NC-NAMs. LIMITATIONS: Retrospective analysis. CONCLUSION: C-NAMs are more often central to a congenital nevus, with a clod/globular or structureless brown pattern, typical of young patients. NC-NAMs are frequently hypopigmented nodules/plaques, eccentric/peripheral, with hypopigmented structureless areas, typical of older patients.

Benign dermatoses of the male genital areas: A review of the literature.

The male genitalia are a common site of dermatoses. Patients with penile diseases often delay or avoid medical care due to anxiety and embarrassment. In this narrative review, we describe some of the main benign dermatoses localized to male genital, focusing on their epidemiology, clinical and dermoscopic features, as well as available therapies.

Melanoma recognition by a deep learning convolutional neural network-Performance in different melanoma subtypes and localisations.

BACKGROUND: Deep learning convolutional neural networks (CNNs) show great potential for melanoma diagnosis. Melanoma thickness at diagnosis among others depends on melanoma localisation and subtype (e.g. advanced thickness in acrolentiginous or nodular melanomas). The question whether CNN may counterbalance physicians' diagnostic difficulties in these melanomas has not been addressed. We aimed to investigate the diagnostic performance of a CNN with approval for the European market across different melanoma localisations and subtypes. METHODS: The current market version of a CNN (Moleanalyzer-Pro®, FotoFinder Systems GmbH, Bad Birnbach, Germany) was used for classifications (malignant/benign) in six dermoscopic image sets. Each set included 30 melanomas and 100 benign lesions of related localisations and morphology (set-SSM: superficial spreading melanomas and macular nevi; set-LMM: lentigo maligna melanomas and facial solar lentigines/seborrhoeic keratoses/nevi; set-NM: nodular melanomas and papillomatous/dermal/blue nevi; set-Mucosa: mucosal melanomas and mucosal melanoses/macules/nevi; set-AMskin: acrolentiginous melanomas and acral (congenital) nevi; set-AMnail: subungual melanomas and subungual (congenital) nevi/lentigines/ethnical type pigmentations). RESULTS: The CNN showed a high-level performance in set-SSM, set-NM and set-LMM (sensitivities >93.3%, specificities >65%, receiver operating characteristics-area under the curve [ROC-AUC] >0.926). In set-AMskin, the sensitivity was lower (83.3%) at a high specificity (91.0%) and ROC-AUC (0.928). A limited performance was found in set-mucosa (sensitivity 93.3%, specificity 38.0%, ROC-AUC 0.754) and set-AMnail (sensitivity 53.3%, specificity 68.0%, ROC-AUC 0.621). CONCLUSIONS: The CNN may help to partly counterbalance reduced human accuracies. However, physicians need to be aware of the CNN's limited diagnostic performance in mucosal and subungual lesions. Improvements may be expected from additional training images of mucosal and subungual sites.

Use of noninvasive imaging in the management of skin cancer.

PURPOSE OF REVIEW: To evaluate noninvasive imaging techniques in the management of skin cancers. RECENT FINDINGS: In the last decades, a wide range of noninvasive imaging methods has been developed in the field of dermatooncology with the aim to detect and assess the several structural and molecular changes that characterize skin cancer development and progression. SUMMARY: In this review, we discuss the current and emerging applications of noninvasive imaging approaches in skin cancer management, such as digital photography, dermoscopy, ultrasound sonography, reflectance confocal microscopy, optical coherence tomography, electrical impedance techniques, Raman spectroscopy, multispectral imaging, fluorescence imaging, and multispectral optoacustic tomography.

Rate of growth-A novel surrogate marker for high-risk cutaneous squamous cell carcinoma? A case report and review of the literature.

Cutaneous squamous cell carcinoma (cSCC) is one of the most common nonmelanoma skin cancer worldwilde, with a more invasive growth pattern and higher potential to metastatize than basal cell carcinoma. Although several risk factors have been linked to a high metastatic potential of cSCC, no widely accepted classification system for this common subtype of cancer exists. Herein we report an emblematic case of rapidly growing and metastatic cSCC and discuss the rate of growth of the tumour (ROG) as novel prognostic high risk surrogate marker.

Association Between Surgical Skin Markings in Dermoscopic Images and Diagnostic Performance of a Deep Learning Convolutional Neural Network for Melanoma Recognition.

IMPORTANCE: Deep learning convolutional neural networks (CNNs) have shown a performance at the level of dermatologists in the diagnosis of melanoma. Accordingly, further exploring the potential limitations of CNN technology before broadly applying it is of special interest. OBJECTIVE: To investigate the association between gentian violet surgical skin markings in dermoscopic images and the diagnostic performance of a CNN approved for use as a medical device in the European market. DESIGN AND SETTING: A cross-sectional analysis was conducted from August 1, 2018, to November 30, 2018, using a CNN architecture trained with more than 120 000 dermoscopic images of skin neoplasms and corresponding diagnoses. The association of gentian violet skin markings in dermoscopic images with the performance of the CNN was investigated in 3 image sets of 130 melanocytic lesions each (107 benign nevi, 23 melanomas). EXPOSURES: The same lesions were sequentially imaged with and without the application of a gentian violet surgical skin marker and then evaluated by the CNN for their probability of being a melanoma. In addition, the markings were removed by manually cropping the dermoscopic images to focus on the melanocytic lesion. MAIN OUTCOMES AND MEASURES: Sensitivity, specificity, and area under the curve (AUC) of the receiver operating characteristic (ROC) curve for the CNN's diagnostic classification in unmarked, marked, and cropped images. RESULTS: In all, 130 melanocytic lesions (107 benign nevi and 23 melanomas) were imaged. In unmarked lesions, the CNN achieved a sensitivity of 95.7% (95% CI, 79%-99.2%) and a specificity of 84.1% (95% CI, 76.0%-89.8%). The ROC AUC was 0.969. In marked lesions, an increase in melanoma probability scores was observed that resulted in a sensitivity of 100% (95% CI, 85.7%-100%) and a significantly reduced specificity of 45.8% (95% CI, 36.7%-55.2%, P < .001). The ROC AUC was 0.922. Cropping images led to the highest sensitivity of 100% (95% CI, 85.7%-100%), specificity of 97.2% (95% CI, 92.1%-99.0%), and ROC AUC of 0.993. Heat maps created by vanilla gradient descent backpropagation indicated that the blue markings were associated with the increased false-positive rate. CONCLUSIONS AND RELEVANCE: This study's findings suggest that skin markings significantly interfered with the CNN's correct diagnosis of nevi by increasing the melanoma probability scores and consequently the false-positive rate. A predominance of skin markings in melanoma training images may have induced the CNN's association of markings with a melanoma diagnosis. Accordingly, these findings suggest that skin markings should be avoided in dermoscopic images intended for analysis by a CNN. TRIAL REGISTRATION: German Clinical Trial Register (DRKS) Identifier: DRKS00013570.

Distinct Clinicopathological and Prognostic Features of Thin Nodular Primary Melanomas: An International Study from 17 Centers.

BACKGROUND: Nodular melanoma (NM) is more likely to be fatal compared with other melanoma subtypes, an effect attributed to its greater Breslow thickness. METHODS: Clinicopathological features of NM and superficial spreading melanoma (SSM) diagnosed in 17 centers in Europe (n = 15), the United States, and Australia between 2006 and 2015, were analyzed by multivariable logistic regression analysis, with emphasis on thin (T1 ≤ 1.0 mm) melanomas. Cox analysis assessed melanoma-specific survival. All statistical tests were two sided. RESULTS: In all, 20 132 melanomas (NM: 5062, SSM: 15 070) were included. Compared with T1 SSM, T1 NM was less likely to have regression (odds ratio [OR] = 0.46, 95% confidence interval [CI] = 0.29 to 0.72) or nevus remnants histologically (OR = 0.60, 95% CI = 0.42 to 0.85), and more likely to have mitoses (OR = 1.97, 95% CI = 1.33 to 2.93) and regional metastasis (OR = 1.77, 95% CI = 1.02 to 3.05). T1 NM had a higher mitotic rate than T1 SSM (adjusted geometric mean = 2.2, 95% CI = 1.9 to 2.5 vs 1.6, 95% CI = 1.5 to 1.7 per mm2, P < .001). Cox multivariable analysis showed a higher risk for melanoma-specific death for NM compared with SSM for T1 (HR = 2.10, 95% CI = 1.24 to 3.56) and T2 melanomas (HR = 1.30, 95% CI = 1.01 to 1.68), and after accounting for center heterogeneity, the difference was statistically significant only for T1 (HR = 2.20, 95% CI = 1.28 to 3.78). The NM subtype did not confer increased risk within each stratum (among localized tumors or cases with regional metastasis). CONCLUSIONS: T1 NM (compared with T1 SSM) was associated with a constellation of aggressive characteristics that may confer a worse prognosis. Our results indicate NM is a high-risk melanoma subtype that should be considered for inclusion in future prognostic classifications of melanoma.