Modified ABC-point list of dermoscopy: A simplified and highly accurate dermoscopic algorithm for the diagnosis of cutaneous melanocytic lesions

Understanding the anatomy of dermoscopy of melanocytic skin tumours: Correlation in vivo with line-field optical coherence tomography

BACKGROUND

Early melanoma detection is the main factor affecting prognosis and survival. For that reason, non-invasive technologies have been developed to provide a more accurate diagnosis. Recently, line-field confocal optical coherence tomography (LC-OCT) was developed to provide an in vivo, imaging device, with deep penetration and cellular resolution in three dimensions. Combining the advantages of conventional OCT and reflectance confocal microscopy, this tool seems to be particularly suitable for melanocytic lesions.

OBJECTIVES

The objective of this study was to identify and describe the correlation between specific dermoscopic criteria and LC-OCT features in three dimensions associated with melanocytic lesions.

METHODS

Dermoscopic and LC-OCT images of 126 melanocytic lesions were acquired in three different centres. The following dermoscopic criteria have been considered: reticular pattern, dots and globules, structureless areas, blue-whitish veil, regression structures, negative network, homogeneous pattern, streaks and blotches.

RESULTS

69 (55%) benign and 57 (45%) malignant lesions were analysed. A regular reticular pattern was found associated in the 75% of the cases with the presence of elongated rete ridges with pigmented cells along the basal layer, while atypical reticular pattern showed an irregular organization of rete ridges with melanocytic hyperplasia, broadened and fused ridges and elongated nests. Both typical and atypical dots and globules were found associated with melanocytic nests in the dermis or at the dermoepidermal junction (DEJ), as well as with keratin cysts/pseudocysts. Grey globules corresponded to the presence of melanin-containing dermal inflammatory cells (melanophages) within the papillae. Structureless brown/black areas correlated with alterations of the DEJ. We observed the same DEJ alterations, but with the presence of dermal melanophages, in 36% of the cases of blue/white/grey structureless areas. A description of each LC-OCT/dermoscopy correlation was made.

CONCLUSIONS

LC-OCT permitted for the first time to perform an in vivo, 3D correlation between dermoscopic criteria and pathological-like features of melanocytic lesions.

Improving Skin Cancer Diagnostics Through a Mobile App With a Large Interactive Image Repository: Randomized Controlled Trial

BACKGROUND

Skin cancer diagnostics is challenging, and mastery requires extended periods of dedicated practice.

OBJECTIVE

The aim of the study was to determine if self-paced pattern recognition training in skin cancer diagnostics with clinical and dermoscopic images of skin lesions using a large-scale interactive image repository (LIIR) with patient cases improves primary care physicians' (PCPs') diagnostic skills and confidence.

METHODS

A total of 115 PCPs were randomized (allocation ratio 3:1) to receive or not receive self-paced pattern recognition training in skin cancer diagnostics using an LIIR with patient cases through a quiz-based smartphone app during an 8-day period. The participants' ability to diagnose skin cancer was evaluated using a 12-item multiple-choice questionnaire prior to and 8 days after the educational intervention period. Their thoughts on the use of dermoscopy were assessed using a study-specific questionnaire. A learning curve was calculated through the analysis of data from the mobile app.

RESULTS

On average, participants in the intervention group spent 2 hours 26 minutes quizzing digital patient cases and 41 minutes reading the educational material. They had an average preintervention multiple choice questionnaire score of 52.0% of correct answers, which increased to 66.4% on the postintervention test; a statistically significant improvement of 14.3 percentage points (P<.001; 95% CI 9.8-18.9) with intention-to-treat analysis. Analysis of participants who received the intervention as per protocol (500 patient cases in 8 days) showed an average increase of 16.7 percentage points (P<.001; 95% CI 11.3-22.0) from 53.9% to 70.5%. Their overall ability to correctly recognize malignant lesions in the LIIR patient cases improved over the intervention period by 6.6 percentage points from 67.1% (95% CI 65.2-69.3) to 73.7% (95% CI 72.5-75.0) and their ability to set the correct diagnosis improved by 10.5 percentage points from 42.5% (95% CI 40.2%-44.8%) to 53.0% (95% CI 51.3-54.9). The diagnostic confidence of participants in the intervention group increased on a scale from 1 to 4 by 32.9% from 1.6 to 2.1 (P<.001). Participants in the control group did not increase their postintervention score or their diagnostic confidence during the same period.

CONCLUSIONS

Self-paced pattern recognition training in skin cancer diagnostics through the use of a digital LIIR with patient cases delivered by a quiz-based mobile app improves the diagnostic accuracy of PCPs.

TRIAL REGISTRATION

ClinicalTrials.gov NCT05661370; https://classic.clinicaltrials.gov/ct2/show/NCT05661370.

Do not PASS any melanoma without diagnosis: a new simplified dermoscopic algorithm

INTRODUCTION

Dermoscopic algorithms for melanoma diagnosis could be time-expending, and their reliability in daily practice lower than expected.

OBJECTIVE

To propose a simplified dermoscopic algorithm for melanoma diagnosis.

MATERIAL AND METHODS

A multicenter retrospective analysis of 1,120 dermoscopic images of atypical melanocytic tumors (320 melanomas and 800 non-melanomas) was performed. An algorithm based on polychromia, asymmetry in colors or structures, and some melanoma-specific structures was designed. Univariate and multivariate logistic regression analysis was calculated to estimate the coefficients of each potential predictor for melanoma diagnosis. A score was developed based on the dermoscopic evaluations performed by four experts blinded to histological diagnosis.

RESULTS

Most melanomas had ≥3 colors (280; 84.5%), asymmetry in colors or structures (289; 90.3%), and at least one melanoma-specific structure (316; 98.7%). PASS score ≥3 had a 91.9% sensibility, 87% specificity, and 88.4% diagnostic accuracy for melanoma. PASS algorithm showed an area under the curve (AUC) of 0.947 (95% CI 0.935-0.959).

LIMITATIONS

This study was retrospective. A comparison between the performances of different dermoscopic algorithms is difficult because of their designs.

CONCLUSION

PASS algorithm showed a very good diagnostic accuracy, independently of the observers' experience, and it seems easier to perform than previous dermoscopic algorithms.

Melanoma classification from dermatoscopy images using knowledge distillation for highly imbalanced data

Melanoma is a deadly malignant skin cancer that generally grows and spreads rapidly. Early detection of melanoma can improve the prognosis of a patient. However, large-scale screening for melanoma is arduous due to human error and the unavailability of trained experts. Accurate automatic melanoma classification from dermoscopy images can help mitigate such issues. However, the classification task is challenging due to class-imbalance, high inter-class, and low intra-class similarity problems. It results in poor sensitivity scores when it comes to the disease classification task. The work proposes a novel knowledge-distilled lightweight Deep-CNN-based framework for melanoma classification to tackle the high inter-class and low intra-class similarity problems. To handle the high class-imbalance problem, the work proposes using Cost-Sensitive Learning with Focal Loss, to achieve better sensitivity scores. As a pre-processing step, an in-painting algorithm is used to remove artifacts from dermoscopy images. New CutOut variants, namely, Sprinkled and microscopic Cutout augmentations, have been employed as regularizers to avoid over-fitting. The robustness of the model has been studied through stratified K-fold cross-validation. Ablation studies with test time augmentation (TTA) and the addition of various noises like salt & pepper, pepper-only, and Gaussian noises have been studied. All the models trained in the work have been evaluated on the SIIM-ISIC Melanoma Classification Challenge - ISIC-2020 dataset. With our EfficientNet-B5 (FL) teacher model, the EfficientNet-B2 student model achieved an Area under the Curve (AUC) of 0.9295, and a sensitivity of 0.8087 on the ISIC-2020 test data. The sensitivity value of 0.8087 for melanoma classification is the current state-of-the-art result in the literature for the ISIC-2020 dataset which is a significant 49.48% increase from the best non-distilled standalone model, EfficientNet B5 (FL) teacher with 0.5410.

Hybrid Melanoma Classification System Using Multi-Layer Fuzzy C-Means Clustering and Deep Convolutional Neural Network

Skin cancer is considered one of the most common type of cancer in several countries. Due to the difficulty and subjectivity in the clinical diagnosis of skin lesions, Computer-Aided Diagnosis systems are being developed for assist experts to perform more reliable diagnosis. The clinical analysis and diagnosis of skin lesions relies not only on the visual information but also on the context information provided by the patient. Skin lesion segmentation plays a significant part in the earlier and precise identification of skin cancer using computer aided diagnosis (CAD) models. But, the segmentation of skin lesions in dermoscopic images is a difficult process due to the constraints of artefacts (hairs, gel bubbles, ruler markers), unclear boundaries, poor and so on. In this work, multi class skin lesion classification system is developed based on multi layered Fuzzy C-means clustering and deep convolutional neural networks. Evaluate the performance of the proposed MLFCM with DCNN model on multi class skin cancer Dermoscopy images. Our results suggest that it is possible to boost the performance of skin lesion segmentation and classification simultaneously via training a unified model to perform both tasks in a mutual bootstrapping way.

Non-invasive diagnostic techniques in pigmentary skin disorders and skin cancer

BACKGROUND

Diagnosis of pigmentary skin disorders, pre-cancerous and cancerous skin diseases is traditionally relied on visual assessment. The most widely applied invasive diagnostic technique is the skin biopsy. There have been significant technological advances in non-invasive diagnostic methods for skin disorders.

OBJECTIVE

The objective of this article is to discuss different non-invasive diagnostic modalities, used in the diagnosis of pigmentary skin disorders and cutaneous cancers.

METHODS

Comprehensive literature search was performed to screen articles related to non-invasive diagnostic techniques in pigmentary skin disorders and cutaneous cancers. Articles published in journals indexed in PubMed were searched along with those in Google Scholar. Clinical trials, review articles, case series, case reports and other relevant articles were considered for review. References of relevant articles were also considered for review.

RESULTS

Dermoscopy and ultrasonography were the only non-invasive diagnostic and imaging techniques available to dermatologists for many years. The advent of computed tomography (CT) and magnetic resonance imaging (MRI) augmented the visualization of deeper structures. Confocal laser microscopy (CLM) and reflectance spectrophotometers have showed promising results in the non-invasive detection of pigmented lesions. Optical coherence tomography (OCT), electrical impedance spectroscopy (EIS), multispectral imaging, high frequency ultrasonography (HFUS) and adhesive patch biopsy aid in the accurate diagnosis of benign, as well as neoplastic skin diseases.

CONCLUSION

There have been significant advancements in non-invasive methods for diagnosis of dermatological diseases. These techniques can be repeatedly used in a comfort manner for the patient, and may offer an objective way to follow the course of a disease.

Melanocytic lesions ≤ 6mm: Prospective series of 481 melanocytic trunk and limb lesions in Brazil

Early diagnosis when melanoma is still small and thin is essential for improving mortality and morbidity. However, the diagnosis of small size melanoma might be particularly difficult, not only clinically but also dermoscopically. This study aimed to define clinical and dermatoscopic parameters in the diagnosis of suspicious pigmented cutaneous lesions with a diameter of ≤ 6mm and determine the sensitivity, specificity, positive and negative predictive values as well as the accuracy of each clinical and dermatoscopic criterion. This is a transversal, descriptive and analytical study of dermatoscopic analysis with the gold standard being the pathologic examination obtained from the excisional biopsy of suspicious melanocytic lesions with a diameter of ≤ 6mm. Trunk and limb lesion data from a public health service and a private clinic were prospectively collected from 2011 to 2017 by a unique observer. In total, 481 melanocytic lesions were included, with 73.8% being ≤ 4mm in diameter. Overall, 123 were diagnosed as melanoma, 56.0% in situ and 22.0% as thin melanomas (Breslow index 0.1 to 1.0mm). Melanoma presented symmetry in 53.7% of cases, regular borders in 54.5% and a single color in 60.2%. Regarding evolution, 13.8% of melanomas versus 10.9% of benign lesions (p = 0.116) were new by comparing photos from baseline with photos from the follow-up. The majority of melanomas (65%) were found on the limbs compared to 37.2% of the benign lesions at this location (p<0.001). A multiple logistic regression model adjusted for age, gender and location was created. The independent variables associated with the diagnosis of melanoma ≤ 6mm, adjusted for age, gender and location, were: streaks (adjusted Odds Ratio [aOR] 2.5; 95% CI 1.3-4.7; p = 0.006), and the presence of a structureless area (aOR 2.2, 95% CI 1.2-4.0, p = 0.011). Conversely, a symmetric typical pigment network was a protection variable (aOR 0.4, 95% 0.7-0.9, p = 0.040). In conclusion, dermatoscopic criteria have been identified which help to diagnose cases of small size melanoma. These include streaks and structureless areas that can be taken, particularly in consideration for the diagnosis of this subset of small difficult melanomas.

An Efficient Melanoma Diagnosis Approach Using Integrated HMF Multi-Atlas Map Based Segmentation

Melanoma is a life threading disease when it grows outside the corium layer of the skin. Mortality rates of the Melanoma cases are maximum among the skin cancer patients. The cost required for the treatment of advanced melanoma cases is very high and the survival rate is low. Numerous computerized dermoscopy systems are developed based on the combination of shape, texture and color features to facilitate early diagnosis of melanoma. The availability and cost of the dermoscopic imaging system is still an issue. To mitigate this issue, this paper presented an integrated segmentation and Third Dimensional (3D) feature extraction approach for the accurate diagnosis of melanoma. A multi-atlas method is applied for the image segmentation. The patch-based label fusion model is expressed in a Bayesian framework to improve the segmentation accuracy. A depth map is obtained from the Two-dimensional (2D) dermoscopic image for reconstructing the 3D skin lesion represented as structure tensors. The 3D shape features including the relative depth features are obtained. Streaks are the significant morphological terms of the melanoma in the radial growth phase. The proposed method yields maximum segmentation accuracy, sensibility, specificity and minimum cost function than the existing segmentation technique and classifier.

Visual inspection and dermoscopy, alone or in combination, for diagnosing keratinocyte skin cancers in adults

BACKGROUND

Early accurate detection of all skin cancer types is important to guide appropriate management, to reduce morbidity and to improve survival. Basal cell carcinoma (BCC) is almost always a localised skin cancer with potential to infiltrate and damage surrounding tissue, whereas a minority of cutaneous squamous cell carcinomas (cSCCs) and invasive melanomas are higher-risk skin cancers with the potential to metastasise and cause death. Dermoscopy has become an important tool to assist specialist clinicians in the diagnosis of melanoma, and is increasingly used in primary-care settings. Dermoscopy is a precision-built handheld illuminated magnifier that allows more detailed examination of the skin down to the level of the superficial dermis. Establishing the value of dermoscopy over and above visual inspection for the diagnosis of BCC or cSCC in primary- and secondary-care settings is critical to understanding its potential contribution to appropriate skin cancer triage, including referral of higher-risk cancers to secondary care, the identification of low-risk skin cancers that might be treated in primary care and to provide reassurance to those with benign skin lesions who can be safely discharged.

OBJECTIVES

To determine the diagnostic accuracy of visual inspection and dermoscopy, alone or in combination, for the detection of (a) BCC and (b) cSCC, in adults. We separated studies according to whether the diagnosis was recorded face-to-face (in person) or based on remote (image-based) assessment.

SEARCH METHODS

We undertook a comprehensive search of the following databases from inception up to August 2016: Cochrane Central Register of Controlled Trials; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles.

SELECTION CRITERIA

Studies of any design that evaluated visual inspection or dermoscopy or both in adults with lesions suspicious for skin cancer, compared with a reference standard of either histological confirmation or clinical follow-up.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic thresholds were missing. We estimated accuracy using hierarchical summary ROC methods. We undertook analysis of studies allowing direct comparison between tests. To facilitate interpretation of results, we computed values of sensitivity at the point on the SROC curve with 80% fixed specificity and values of specificity with 80% fixed sensitivity. We investigated the impact of in-person test interpretation; use of a purposely-developed algorithm to assist diagnosis; and observer expertise.

MAIN RESULTS

We included 24 publications reporting on 24 study cohorts, providing 27 visual inspection datasets (8805 lesions; 2579 malignancies) and 33 dermoscopy datasets (6855 lesions; 1444 malignancies). The risk of bias was mainly low for the index test (for dermoscopy evaluations) and reference standard domains, particularly for in-person evaluations, and high or unclear for participant selection, application of the index test for visual inspection and for participant flow and timing. We scored concerns about the applicability of study findings as of 'high' or 'unclear' concern for almost all studies across all domains assessed. Selective participant recruitment, lack of reproducibility of diagnostic thresholds and lack of detail on observer expertise were particularly problematic.The detection of BCC was reported in 28 datasets; 15 on an in-person basis and 13 image-based. Analysis of studies by prior testing of participants and according to observer expertise was not possible due to lack of data. Studies were primarily conducted in participants referred for specialist assessment of lesions with available histological classification. We found no clear differences in accuracy between dermoscopy studies undertaken in person and those which evaluated images. The lack of effect observed may be due to other sources of heterogeneity, including variations in the types of skin lesion studied, in dermatoscopes used, or in the use of algorithms and varying thresholds for deciding on a positive test result.Meta-analysis found in-person evaluations of dermoscopy (7 evaluations; 4683 lesions and 363 BCCs) to be more accurate than visual inspection alone for the detection of BCC (8 evaluations; 7017 lesions and 1586 BCCs), with a relative diagnostic odds ratio (RDOR) of 8.2 (95% confidence interval (CI) 3.5 to 19.3; P < 0.001). This corresponds to predicted differences in sensitivity of 14% (93% versus 79%) at a fixed specificity of 80% and predicted differences in specificity of 22% (99% versus 77%) at a fixed sensitivity of 80%. We observed very similar results for the image-based evaluations.When applied to a hypothetical population of 1000 lesions, of which 170 are BCC (based on median BCC prevalence across studies), an increased sensitivity of 14% from dermoscopy would lead to 24 fewer BCCs missed, assuming 166 false positive results from both tests. A 22% increase in specificity from dermoscopy with sensitivity fixed at 80% would result in 183 fewer unnecessary excisions, assuming 34 BCCs missed for both tests. There was not enough evidence to assess the use of algorithms or structured checklists for either visual inspection or dermoscopy.Insufficient data were available to draw conclusions on the accuracy of either test for the detection of cSCCs.

AUTHORS' CONCLUSIONS

Dermoscopy may be a valuable tool for the diagnosis of BCC as an adjunct to visual inspection of a suspicious skin lesion following a thorough history-taking including assessment of risk factors for keratinocyte cancer. The evidence primarily comes from secondary-care (referred) populations and populations with pigmented lesions or mixed lesion types. There is no clear evidence supporting the use of currently-available formal algorithms to assist dermoscopy diagnosis.

Dermoscopy, with and without visual inspection, for diagnosing melanoma in adults

BACKGROUND

Melanoma has one of the fastest rising incidence rates of any cancer. It accounts for a small percentage of skin cancer cases but is responsible for the majority of skin cancer deaths. Although history-taking and visual inspection of a suspicious lesion by a clinician are usually the first in a series of 'tests' to diagnose skin cancer, dermoscopy has become an important tool to assist diagnosis by specialist clinicians and is increasingly used in primary care settings. Dermoscopy is a magnification technique using visible light that allows more detailed examination of the skin compared to examination by the naked eye alone. Establishing the additive value of dermoscopy over and above visual inspection alone across a range of observers and settings is critical to understanding its contribution for the diagnosis of melanoma and to future understanding of the potential role of the growing number of other high-resolution image analysis techniques.

OBJECTIVES

To determine the diagnostic accuracy of dermoscopy alone, or when added to visual inspection of a skin lesion, for the detection of cutaneous invasive melanoma and atypical intraepidermal melanocytic variants in adults. We separated studies according to whether the diagnosis was recorded face-to-face (in-person), or based on remote (image-based), assessment.

SEARCH METHODS

We undertook a comprehensive search of the following databases from inception up to August 2016: CENTRAL; MEDLINE; Embase; CINAHL; CPCI; Zetoc; Science Citation Index; US National Institutes of Health Ongoing Trials Register; NIHR Clinical Research Network Portfolio Database; and the World Health Organization International Clinical Trials Registry Platform. We studied reference lists and published systematic review articles.

SELECTION CRITERIA

Studies of any design that evaluated dermoscopy in adults with lesions suspicious for melanoma, compared with a reference standard of either histological confirmation or clinical follow-up. Data on the accuracy of visual inspection, to allow comparisons of tests, was included only if reported in the included studies of dermoscopy.

DATA COLLECTION AND ANALYSIS

Two review authors independently extracted all data using a standardised data extraction and quality assessment form (based on QUADAS-2). We contacted authors of included studies where information related to the target condition or diagnostic threshold were missing. We estimated accuracy using hierarchical summary receiver operating characteristic (SROC),methods. Analysis of studies allowing direct comparison between tests was undertaken. To facilitate interpretation of results, we computed values of sensitivity at the point on the SROC curve with 80% fixed specificity and values of specificity with 80% fixed sensitivity. We investigated the impact of in-person test interpretation; use of a purposely developed algorithm to assist diagnosis; observer expertise; and dermoscopy training.

MAIN RESULTS

We included a total of 104 study publications reporting on 103 study cohorts with 42,788 lesions (including 5700 cases), providing 354 datasets for dermoscopy. The risk of bias was mainly low for the index test and reference standard domains and mainly high or unclear for participant selection and participant flow. Concerns regarding the applicability of study findings were largely scored as 'high' concern in three of four domains assessed. Selective participant recruitment, lack of reproducibility of diagnostic thresholds and lack of detail on observer expertise were particularly problematic.The accuracy of dermoscopy for the detection of invasive melanoma or atypical intraepidermal melanocytic variants was reported in 86 datasets; 26 for evaluations conducted in person (dermoscopy added to visual inspection), and 60 for image-based evaluations (diagnosis based on interpretation of dermoscopic images). Analyses of studies by prior testing revealed no obvious effect on accuracy; analyses were hampered by the lack of studies in primary care, lack of relevant information and the restricted inclusion of lesions selected for biopsy or excision. Accuracy was higher for in-person diagnosis compared to image-based evaluations (relative diagnostic odds ratio (RDOR) 4.6, 95% confidence interval (CI) 2.4 to 9.0; P < 0.001).We compared accuracy for (a), in-person evaluations of dermoscopy (26 evaluations; 23,169 lesions and 1664 melanomas),versus visual inspection alone (13 evaluations; 6740 lesions and 459 melanomas), and for (b), image-based evaluations of dermoscopy (60 evaluations; 13,475 lesions and 2851 melanomas),versus image-based visual inspection (11 evaluations; 1740 lesions and 305 melanomas). For both comparisons, meta-analysis found dermoscopy to be more accurate than visual inspection alone, with RDORs of (a), 4.7 (95% CI 3.0 to 7.5; P < 0.001), and (b), 5.6 (95% CI 3.7 to 8.5; P < 0.001). For a), the predicted difference in sensitivity at a fixed specificity of 80% was 16% (95% CI 8% to 23%; 92% for dermoscopy + visual inspection versus 76% for visual inspection), and predicted difference in specificity at a fixed sensitivity of 80% was 20% (95% CI 7% to 33%; 95% for dermoscopy + visual inspection versus 75% for visual inspection). For b) the predicted differences in sensitivity was 34% (95% CI 24% to 46%; 81% for dermoscopy versus 47% for visual inspection), at a fixed specificity of 80%, and predicted difference in specificity was 40% (95% CI 27% to 57%; 82% for dermoscopy versus 42% for visual inspection), at a fixed sensitivity of 80%.Using the median prevalence of disease in each set of studies ((a), 12% for in-person and (b), 24% for image-based), for a hypothetical population of 1000 lesions, an increase in sensitivity of (a), 16% (in-person), and (b), 34% (image-based), from using dermoscopy at a fixed specificity of 80% equates to a reduction in the number of melanomas missed of (a), 19 and (b), 81 with (a), 176 and (b), 152 false positive results. An increase in specificity of (a), 20% (in-person), and (b), 40% (image-based), at a fixed sensitivity of 80% equates to a reduction in the number of unnecessary excisions from using dermoscopy of (a), 176 and (b), 304 with (a), 24 and (b), 48 melanomas missed.The use of a named or published algorithm to assist dermoscopy interpretation (as opposed to no reported algorithm or reported use of pattern analysis), had no significant impact on accuracy either for in-person (RDOR 1.4, 95% CI 0.34 to 5.6; P = 0.17), or image-based (RDOR 1.4, 95% CI 0.60 to 3.3; P = 0.22), evaluations. This result was supported by subgroup analysis according to algorithm used. We observed higher accuracy for observers reported as having high experience and for those classed as 'expert consultants' in comparison to those considered to have less experience in dermoscopy, particularly for image-based evaluations. Evidence for the effect of dermoscopy training on test accuracy was very limited but suggested associated improvements in sensitivity.

AUTHORS' CONCLUSIONS

Despite the observed limitations in the evidence base, dermoscopy is a valuable tool to support the visual inspection of a suspicious skin lesion for the detection of melanoma and atypical intraepidermal melanocytic variants, particularly in referred populations and in the hands of experienced users. Data to support its use in primary care are limited, however, it may assist in triaging suspicious lesions for urgent referral when employed by suitably trained clinicians. Formal algorithms may be of most use for dermoscopy training purposes and for less expert observers, however reliable data comparing approaches using dermoscopy in person are lacking.

Diagnosing malignant melanoma in ambulatory care: a systematic review of clinical prediction rules

OBJECTIVES

Malignant melanoma has high morbidity and mortality rates. Early diagnosis improves prognosis. Clinical prediction rules (CPRs) can be used to stratify patients with symptoms of suspected malignant melanoma to improve early diagnosis. We conducted a systematic review of CPRs for melanoma diagnosis in ambulatory care.

DESIGN

Systematic review.

DATA SOURCES

A comprehensive search of PubMed, EMBASE, PROSPERO, CINAHL, the Cochrane Library and SCOPUS was conducted in May 2015, using combinations of keywords and medical subject headings (MeSH) terms.

STUDY SELECTION AND DATA EXTRACTION

Studies deriving and validating, validating or assessing the impact of a CPR for predicting melanoma diagnosis in ambulatory care were included. Data extraction and methodological quality assessment were guided by the CHARMS checklist.

RESULTS

From 16 334 studies reviewed, 51 were included, validating the performance of 24 unique CPRs. Three impact analysis studies were identified. Five studies were set in primary care. The most commonly evaluated CPRs were the ABCD, more than one or uneven distribution of Colour, or a large (greater than 6 mm) Diameter (ABCD) dermoscopy rule (at a cut-point of >4.75; 8 studies; pooled sensitivity 0.85, 95% CI 0.73 to 0.93, specificity 0.72, 95% CI 0.65 to 0.78) and the 7-point dermoscopy checklist (at a cut-point of ≥1 recommending ruling in melanoma; 11 studies; pooled sensitivity 0.77, 95% CI 0.61 to 0.88, specificity 0.80, 95% CI 0.59 to 0.92). The methodological quality of studies varied.

CONCLUSIONS

At their recommended cut-points, the ABCD dermoscopy rule is more useful for ruling out melanoma than the 7-point dermoscopy checklist. A focus on impact analysis will help translate melanoma risk prediction rules into useful tools for clinical practice.

Melanoma Is Skin Deep: A 3D Reconstruction Technique for Computerized Dermoscopic Skin Lesion Classification

Melanoma mortality rates are the highest amongst skin cancer patients. Melanoma is life threating when it grows beyond the dermis of the skin. Hence, depth is an important factor to diagnose melanoma. This paper introduces a non-invasive computerized dermoscopy system that considers the estimated depth of skin lesions for diagnosis. A 3-D skin lesion reconstruction technique using the estimated depth obtained from regular dermoscopic images is presented. On basis of the 3-D reconstruction, depth and 3-D shape features are extracted. In addition to 3-D features, regular color, texture, and 2-D shape features are also extracted. Feature extraction is critical to achieve accurate results. Apart from melanoma, in-situ melanoma the proposed system is designed to diagnose basal cell carcinoma, blue nevus, dermatofibroma, haemangioma, seborrhoeic keratosis, and normal mole lesions. For experimental evaluations, the PH2, ISIC: Melanoma Project, and ATLAS dermoscopy data sets is considered. Different feature set combinations is considered and performance is evaluated. Significant performance improvement is reported the post inclusion of estimated depth and 3-D features. The good classification scores of sensitivity = 96%, specificity = 97% on PH2 data set and sensitivity = 98%, specificity = 99% on the ATLAS data set is achieved. Experiments conducted to estimate tumor depth from 3-D lesion reconstruction is presented. Experimental results achieved prove that the proposed computerized dermoscopy system is efficient and can be used to diagnose varied skin lesion dermoscopy images.

The invisible basal cell carcinoma: how reflectance confocal microscopy improves the diagnostic accuracy of clinically unclear facial macules and papules

Difficult to diagnose and early non-melanoma skin cancer lesions are frequently seen in daily clinical practice. Besides precancerous lesions such as actinic keratosis, basal cell carcinomas (BCCs) score the highest frequency in skin tumors. While infiltrative and nodular BCCs require a surgical treatment with a significant impact on the patients' quality of life, early and superficial BCCs might benefit from numerous conservative treatments, such as topical immune-modulators or photodynamic therapy. Dermoscopy has shown a high sensitivity and specificity in the diagnosis of early BCCs, and non-invasive imaging techniques like reflectance confocal microscopy (RCM) have proven to be helpful. The aim of our study was to investigate the importance of RCM in the diagnosis of BCCs with indistinct clinical and dermoscopic features. We retrospectively examined 27 histologically proven BCCs in which diagnosis was not possible based on naked eye examination; we separately reviewed clinical, dermoscopic, and confocal microscopy features and evaluated the lesions meeting the common diagnostic criteria for BCCs, and our diagnostic confidence. All lesions were clinically unclear, with no characteristic features suggestive for BCC; dermoscopy showed in most cases unspecific teleangiectasias (74 %) and micro-erosions (52 %). Confocal microscopy revealed in most of the cases the presence of specific criteria: peripheral palisading of the nuclei (89 %), clefting (70 %), stromal reaction (70 %), dark silhouettes (70 %), inflammatory particles (70 %), and tumor islands (67 %). In the absence of significant diagnostic clinical signs and with unclear dermoscopic features, specific confocal patterns were present in most of the lesions and enabled a correct diagnosis. In the absence of significant clinical features of BCC and in the case of uncertain dermoscopy, striking confocal features are detectable and easy to recognize in most cases. Confocal microscopy can therefore be instrumentful in the diagnosis of the so-called invisible BCCs.

Modified Dermoscopic Algorithm for the Differentiation between Melanocytic and Nonmelanocytic Skin Tumors

Background:

The use of dermoscopy (dermatoscopy, epiluminescence microscopy, surface microscopy) improves the clinical diagnostic accuracy of skin tumors by applying different algorithms or scores. The first step in the dermoscopic evaluation is the differentiation between melanocytic and nonmelanocytic skin tumors.

Objective:

To evaluate the diagnostic accuracy of the established dermoscopic algorithm (EDA) and the modified dermoscopic algorithm (MDA) for melanocytic versus nonmelanocytic skin tumors.

Methods:

Two hundred forty-nine patients with melanocytic and nonmelanocytic skin lesions were included. Dermoscopic images of the tumors were taken with 10-fold magnification, followed by surgery and histopathology at the departments of Dermatology at the universities of Tuebingen, in Germany, and Naples, in Italy. Each lesion was classified using the EDA and MDA. In the MDA, accessory nipples and dermatofibromas were considered in particular.

Results:

With the EDA, 225 of 249 (90.4%) skin tumors were correctly classified in one of the six groups. With the MDA, 237 of 249 (95.2%) were correctly classified. Improvement was achieved in 12 (4.8%) better classified skin tumors. In both algorithms, no melanoma was classified as a nonmalignant melanocytic tumor. All melanomas were classified in the group of melanocytic tumors and one melanoma was classified in the group of basal cell carcinomas.

Conclusion:

Both dermoscopic algorithms for the differentiation between melanocytic and nonmelanocytic skin tumors were simple and effective when applied step by step. The MDA is an improvement on the EDA with the classification of accessory nipples and dermatofibromas.

Classification of reticular pattern and streaks in dermoscopic images based on texture analysis

The early detection of melanoma is one of the greatest challenges in clinical practice of dermatology, and the reticular pattern is one of the most important dermoscopic structures to improve melanocytic lesion diagnosis. A texture-based approach is developed for the automatic detection of reticular patterns, whose output will assist clinical decision-making. Feature selection was based on the use of two algorithms by means of the classical graylevel co-occurrence matrix and Laws energy masks optimized on a set of 104 dermoscopy images. The AdaBoost (adaptive boosting) approach to machine learning was used within this strategy. Results suggest superiority of LEM for reticular pattern detection in dermoscopic images, achieving a sensitivity of 90.16% and a specificity of 86.67%. The use of automatic classification in dermoscopy to support clinicians is a strong tool to assist diagnosis; however, the use of automatic classification as a complementary tool in clinical routine requires algorithms with high levels of sensitivity and specificity. The results presented in this work will contribute to achieving this goal.

In vivo study for the discrimination of cancerous and normal skin using fibre probe-based Raman spectroscopy

Raman spectroscopy has proved its capability as an objective, non-invasive tool for the detection of various melanoma and non-melanoma skin cancers (NMSC) in a number of studies. Most publications are based on a Raman microspectroscopic ex vivo approach. In this in vivo clinical evaluation, we apply Raman spectroscopy using a fibre-coupled probe that allows access to a multitude of affected body sites. The probe design is optimized for epithelial sensitivity, whereby a large part of the detected signal originates from within the epidermal layer's depth down to the basal membrane where early stages of skin cancer develop. Data analysis was performed on measurements of 104 subjects scheduled for excision of lesions suspected of being malignant melanoma (MM) (n = 36), basal cell carcinoma (BCC) (n = 39) and squamous cell carcinoma (SCC) (n = 29). NMSC were discriminated from normal skin with a balanced accuracy of 73% (BCC) and 85% (SCC) using partial least squares discriminant analysis (PLS-DA). Discriminating MM and pigmented nevi (PN) resulted in a balanced accuracy of 91%. These results lie within the range of comparable in vivo studies and the accuracies achieved by trained dermatologists using dermoscopy. Discrimination proved to be unsuccessful between cancerous lesions and suspicious lesions that had been histopathologically verified as benign by dermoscopy.

Pilot study on the bioactivity of vitamin d in the skin after oral supplementation

Laboratory studies suggest that vitamin D (VD) supplementation inhibits skin carcinogenesis. However, epidemiologic studies report mixed findings in the association between circulating VD levels and skin cancer risk. We conducted a clinical study to determine whether oral cholecalciferol supplementation would exert direct bioactivity in human skin through modulation of the VD receptor (VDR). We enrolled 25 individuals with serum 25-hydroxyvitamin-D levels <30 ng/mL and with skin photodamage to take 50,000 IU of cholecalciferol biweekly for 8 to 9 weeks. Then, we obtained baseline and end-of-study skin biopsies from photodamaged (PD) and photoprotected (PP) skin, and from benign nevi (BN) and tested for mRNA expression of VDR and cytochrome P450-24 (CYP24), and markers of keratinocytic differentiation. High-dose cholecalciferol supplementation significantly elevated circulating levels of 25-hydroxyvitamin-D (P < 0.0001) and 1,25-dihydroxyvitamin-D (P < 0.0001). VDR expression in PD- and PP-skin showed minimum changes after supplementation. CYP24 expression in PD- and PP-skin was increased after supplementation by 186%, P = 0.08, and 134%, P = 0.07, respectively. In BNs from 11 participants, a trend for higher VDR and CYP24 expression was observed (average of 20%, P = 0.08, and 544%, P = 0.09, respectively). Caspase-14 expression at the basal layer in PD skin samples was the only epidermal differentiation marker that was significantly increased (49%, P < 0.0001). High-dose cholecalciferol supplementation raised serum VD metabolite levels concurrently with CYP24 mRNA and caspase-14 levels in the skin. Our findings of significant variability in the range of VDR and CYP24 expression across study samples represent an important consideration in studies evaluating the role of VD as a skin cancer chemopreventive agent.

The most common mistakes on dermatoscopy of melanocytic lesions

Dermatoscopy is a method of in vivo evaluation of the structures within the epidermis and dermis. Currently, it may be the most precise pre-surgical method of diagnosing melanocytic lesions. Diagnostic errors may result in unnecessary removal of benign lesions or what is even worse, they can cause early and very early melanomas to be overlooked. Errors in assessment of dermatoscopy can be divided into those arising from failure to maintain proper test procedures (procedural and technical errors) and knowledge based mistakes related to the lack of sufficient familiarity and experience in dermatoscopy. The article discusses the most common mistakes made by beginner or inexperienced dermatoscopists.

Melanoma: diagnosis, staging, and treatment. Consensus group recommendations

The incidence of malignant melanoma is increasing worldwide. In Spain, its incidence is increasing faster than any other cancer type, with a 5-year survival rate of about 85%. The impact and characteristics of malignant melanoma in the Spanish population can be ascertained from the national melanoma registry of the Academia Española de Dermatología y Venereología. This review presents consensus group recommendations for the diagnosis, staging and treatment of malignant melanoma in Spain. Incidence and mortality are discussed, as well as evaluation of various prevention and treatment strategies. Prognostic factors, such as BRAF and C-KIT mutations, which are expected to become routine staging procedures over the next few years, are outlined, especially in relation to treatment options. The use of recently approved targeted agents such as ipilimumab, a cytotoxic T lymphocyte-associated antigen 4 (CTLA-4) inhibitor, and vemurafenib, a BRAF inhibitor, in metastatic disease are also discussed.

Comparison of dermatoscopic diagnostic algorithms based on calculation: The ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm in dermatoscopic evaluation of melanocytic lesions

Dermatoscopic analysis of melanocytic lesions using the CASH algorithm has rarely been described in the literature. The purpose of this study was to compare the sensitivity, specificity, and diagnostic accuracy rates of the ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist, and the CASH algorithm in the diagnosis and dermatoscopic evaluation of melanocytic lesions on the hairy skin. One hundred and fifteen melanocytic lesions of 115 patients were examined retrospectively using dermatoscopic images and compared with the histopathologic diagnosis. Four dermatoscopic algorithms were carried out for all lesions. The ABCD rule of dermatoscopy showed sensitivity of 91.6%, specificity of 60.4%, and diagnostic accuracy of 66.9%. The seven-point checklist showed sensitivity, specificity, and diagnostic accuracy of 87.5, 65.9, and 70.4%, respectively; the three-point checklist 79.1, 62.6, 66%; and the CASH algorithm 91.6, 64.8, and 70.4%, respectively. To our knowledge, this is the first study that compares the sensitivity, specificity and diagnostic accuracy of the ABCD rule of dermatoscopy, the three-point checklist, the seven-point checklist, and the CASH algorithm for the diagnosis of melanocytic lesions on the hairy skin. In our study, the ABCD rule of dermatoscopy and the CASH algorithm showed the highest sensitivity for the diagnosis of melanoma.

Dermatoscopy for melanoma and pigmented lesions

This article presents an overview of the history and development of dermatoscopy over the last 2 decades. The common dermatoscopic diagnostic algorithms are discussed, including classic pattern analysis, the ABCD rule (asymmetry, border, color, and dermatoscopic structures), 7-point checklist, and Menzies method, as well as a new method by the authors (ASAP: a simple and practical approach). In addition, evidence on the clinical impact and challenges of dermatoscopy for the diagnosis and management of pigmented lesions and the importance of training are reviewed.

A simple scoring system for the diagnosis of palmo-plantar pigmented skin lesions by digital dermoscopy analysis

BACKGROUND

Many research groups have recently developed equipments and statistical methods enabling pattern classification of pigmented skin lesions. To differentiate between benign and malignant ones, the mathematical extraction of digital patterns together with the use of appropriate statistical approaches is a challenging task.

OBJECTIVE

To design a simple scoring model that provides accurate classification of benign and malignant palmo-plantar pigmented skin lesions, by evaluation of parameters obtained by digital dermoscopy analysis (DDA).

PATIENTS AND METHODS

In the present study we used a digital dermoscopy analyser to evaluate a series of 445 palmo-plantar melanocytic skin lesion images (25 melanomas 420 nevi). Area under the receiver operator curve, sensitivity and specificity were calculated to evaluate the diagnostic performance of our scoring model for the differentiation of benign and malignant palmo-plantar melanocytic lesions.

RESULTS

Model performance reached a very high value (0.983). The DDA parameters selected by the model that proved statistically significant were: area, peripheral dark regions, total imbalance of colours, entropy, dark area and red and blue multicomponent. When all seven model variables were used in a multivariate mode, setting sensitivity at 100% to avoid false negatives, we estimated a minimum specificity of about 80%.

CONCLUSIONS

Simplicity of use and effectiveness of implementation are important requirements for the success of quantitative methods in routine clinical practice. Scoring systems meet these requirements. Their outcomes are accessible in real time without the use of any data processing system, thus allowing decisions to be made quickly and effectively.

The role of spectrophotometry in the diagnosis of melanoma

Background

Spectrophotometry (SPT) could represent a promising technique for the diagnosis of cutaneous melanoma (CM) at earlier stages of the disease. Starting from our experience, we further assessed the role of SPT in CM early detection.

Methods

During a health campaign for malignant melanoma at National Cancer Institute of Naples, we identified a subset of 54 lesions to be addressed to surgical excision and histological examination. Before surgery, all patients were investigated by clinical and epiluminescence microscopy (ELM) screenings; selected lesions underwent spectrophotometer analysis. For SPT, we used a video spectrophotometer imaging system (Spectroshade^® MHT S.p.A., Verona, Italy).

Results

Among the 54 patients harbouring cutaneous pigmented lesions, we performed comparison between results from the SPT screening and the histological diagnoses as well as evaluation of both sensitivity and specificity in detecting CM using either SPT or conventional approaches. For all pigmented lesions, agreement between histology and SPT classification was 57.4%. The sensitivity and specificity of SPT in detecting melanoma were 66.6% and 76.2%, respectively.

Conclusions

Although SPT is still considered as a valuable diagnostic tool for CM, its low accuracy, sensitivity, and specificity represent the main hamper for the introduction of such a methodology in clinical practice. Dermoscopy remains the best diagnostic tool for the preoperative diagnosis of pigmented skin lesions.

Strategies for early melanoma detection: Approaches to the patient with nevi

Given its propensity to metastasize and the lack of effective therapies for most patients with advanced disease, early detection of melanoma is a clinical imperative. Although there are no noninvasive techniques for the definitive diagnosis of melanoma, and the "gold standard" remains biopsy with histologic examination, a variety of modalities may facilitate early melanoma diagnosis and the detection of new and changing nevi. This article reviews the general clinical principles of early melanoma detection and various modalities that are currently available or on the horizon, providing the clinician with an up to date understanding of management strategies for their patients with numerous or atypical nevi.

LEARNING OBJECTIVE

After completing this learning activity, participants should understand the clinical importance of early melanoma detection, appreciate the challenges of early melanoma diagnosis and which patients are at highest risk, know the general principles of early melanoma detection, be familiar with current and emerging modalities that may facilitate early melanoma diagnosis and the detection of new and changing nevi, know the advantages and limitations of each modality, and be able to practice a combined approach to the patient with numerous or clinically atypical nevi.

Systematic review of dermoscopy and digital dermoscopy/ artificial intelligence for the diagnosis of melanoma

BACKGROUND

Dermoscopy improves diagnostic accuracy of the unaided eye for melanoma, and digital dermoscopy with artificial intelligence or computer diagnosis has also been shown useful for the diagnosis of melanoma. At present there is no clear evidence regarding the diagnostic accuracy of dermoscopy compared with artificial intelligence.

OBJECTIVES

To evaluate the diagnostic accuracy of dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis and to compare the diagnostic accuracy of the different dermoscopic algorithms with each other and with digital dermoscopy/artificial intelligence for the detection of melanoma.

METHODS

A literature search on dermoscopy and digital dermoscopy/artificial intelligence for melanoma diagnosis was performed using several databases. Titles and abstracts of the retrieved articles were screened using a literature evaluation form. A quality assessment form was developed to assess the quality of the included studies. Heterogeneity among the studies was assessed. Pooled data were analysed using meta-analytical methods and comparisons between different algorithms were performed.

RESULTS

Of 765 articles retrieved, 30 studies were eligible for meta-analysis. Pooled sensitivity for artificial intelligence was slightly higher than for dermoscopy (91% vs. 88%; P = 0.076). Pooled specificity for dermoscopy was significantly better than artificial intelligence (86% vs. 79%; P < 0.001). Pooled diagnostic odds ratio was 51.5 for dermoscopy and 57.8 for artificial intelligence, which were not significantly different (P = 0.783). There were no significance differences in diagnostic odds ratio among the different dermoscopic diagnostic algorithms.

CONCLUSIONS

Dermoscopy and artificial intelligence performed equally well for diagnosis of melanocytic skin lesions. There was no significant difference in the diagnostic performance of various dermoscopy algorithms. The three-point checklist, the seven-point checklist and Menzies score had better diagnostic odds ratios than the others; however, these results need to be confirmed by a large-scale high-quality population-based study.

Towards oncological application of Raman spectroscopy

As the possibilities in the treatment of cancer continue to evolve, its early detection and correct diagnosis are becoming increasingly important. From the early detection of cancer to the guidance of oncosurgical procedures new sensitive in vivo diagnostic tools are much needed. Many studies report the Raman spectroscopic detection of malignant and premalignant tissues in different sites of the body with high sensitivities. The great appeal of this technique lies in its potential for in vivo clinical implementation. We present an overview of the in vitro and in vivo work on the oncological application of Raman spectroscopy and discuss its potential as a new tool in the clinico-oncological practice. Opportunities for integration of Raman spectroscopy in oncological cure and care as a real-time guidance tool during diagnostic (i.e. biopsy) and therapeutic (surgical resection) modalities as well as technical shortcomings are discussed from a clinician's point of view.

Dermoscopy report: Proposal for standardization

BACKGROUND

Dermoscopy can assist clinicians in the evaluation and diagnosis of skin tumors. Since dermoscopy is becoming widely accepted and used in the medical community, there is now the need for a standardized method for documenting dermoscopic findings so as to be able to effectively communicate such information among colleagues.

OBJECTIVES

Toward this end, the International Dermoscopy Society embarked on creating a consensus document for the standardization and recommended criteria necessary to be able to effectively convey dermoscopic findings to consulting physicians and colleagues.

METHODS

The Dermoscopy Report Steering Committee created an extensive list of dermoscopic criteria obtained from an exhaustive search of the literature. A preliminary document listing all the dermoscopic criteria that could potentially be included in a standardized dermoscopy report was elaborated and presented to the members of the International Dermoscopy Society Board in two meetings of the Society and subsequently discussed via Internet communications between members and the Steering Committee.

RESULTS

A consensus document including 10 points categorized as either recommended or optional and a template of the dermoscopy report were obtained. The final items included in the document are as follows: (1) patient's age, relevant history pertaining to the lesion, pertinent personal and family history (recommended); (2) clinical description of the lesion (recommended); (3) the two-step method of dermoscopy differentiating melanocytic from nonmelanocytic tumors (recommended); (4) the use of standardized terms to describe structures as defined by the Dermoscopy Consensus Report published in 2003. For new terms it would be helpful to provide a working definition (recommended); (5) the dermoscopic algorithm used should be mentioned (optional); (6) information on the imaging equipment and magnification (recommended); (7) clinical and dermoscopic images of the tumor (recommended); (8) a diagnosis or differential diagnosis (recommended); (9) decision concerning the management (recommended); (10) specific comments for the pathologist when excision and histopathologic examination are recommended (optional).

LIMITATIONS

The limitations of this study are those that are intrinsic of a consensus document obtained from critical review of the literature and discussion by opinion leaders in the field.

CONCLUSIONS

Although it may be acceptable for a consulting physician to only state the dermoscopic diagnosis, the proposed standardized reporting system, if accepted and utilized, will make it easier for consultants to communicate with each other more effectively.

Sensitivity, specificity, and diagnostic accuracy of three dermoscopic algorithmic methods in the diagnosis of doubtful melanocytic lesions

BACKGROUND

Over the past decade numerous epiluminescence microscopy (ELM) criteria and algorithmic methods have been developed to improve the diagnosis of cutaneous melanocytic lesions.

OBJECTIVE

Our purpose was to compare the sensitivity, specificity, and diagnostic accuracy of 3 algorithmic methods (pattern analysis, ABCD rule of dermoscopy, and the 7-point checklist) on a series of highly atypical melanocytic lesions. We also determined the diagnostic value of distinct ELM structures by evaluating their frequency in these lesions.

METHODS

A total of 198 consecutive atypical macular melanocytic lesions were studied. ELM assessment was based on the presence or absence of 23 dermoscopic features. Two ELM-experienced dermatologists classified each lesion as benign or malignant using the pattern analysis, the ABCD rule of dermoscopy, and the 7-point checklist method. After surgical excision, 102 lesions were histologically diagnosed as Clark's nevi and 96 as thin melanomas (TMs) (mean tumor thickness, 0.3 mm). ELM and histologic diagnoses were then compared to assess the sensitivity, specificity, and diagnostic accuracy as well as positive and negative predictive values (PPV and NPV, respectively) for TMs of the 3 algorithmic methods. Univariate and multivariate analyses were performed to determine which ELM criteria were most strongly associated with TM.

RESULTS

Of the melanocytic lesions studied, 82.3% were correctly diagnosed by using pattern analysis (85.4% sensitivity, 79.4% specificity, 79.6% PPV, and 70.8% diagnostic accuracy), compared with correct diagnosis of 79.3% (84.4% sensitivity, 74.5% specificity, 75.7% PPV, and 67.8% diagnostic accuracy) and 71.2% (78.1% sensitivity, 64.7% specificity, 67.6% PPV, and 57.7% diagnostic accuracy) with the ABCD and the 7-point checklist methods, respectively. The 7-point checklist yielded the highest number of false-negative results (21.8%) with respect to the ABCD rule (15.6%) and pattern analysis (14.6%). Univariate analysis showed that an atypical pigment network, a pigment network with sharp margins, irregular nonuniform brown globules, a nonuniform pigment distribution, homogeneous areas, and light brown structureless areas were the most sensitive and specific ELM features for TM. A backward stepwise logistic regression analysis revealed that the criterion with the strongest TM association was light brown structureless areas (odds ratio = 27.9; 95% confidence interval, 8.6-90.9).

LIMITATIONS

The presence and value of light brown structureless areas should also be investigated in clinically nonatypical macular melanocytic lesions.

CONCLUSION

The pattern analysis method showed the highest sensitivity, specificity, and diagnostic accuracy for TM. Light brown structureless areas were both a statistically significant discriminator and the most reliable predictor of TM (PPV = 93.8%, positive likelihood ratio = 16). Therefore the use of this previously underestimated ELM criterion may not only improve diagnostic performance of equivocal macular melanocytic lesions but also significantly decrease the rate of false-negative results obtained with the 7-point checklist method.

Algorithmic reproduction of asymmetry and border cut-off parameters according to the ABCD rule for dermoscopy

BACKGROUND

Semiquantitative algorithms were applied to dermoscopic images to improve the clinical diagnosis for melanoma.

OBJECTIVE

The aim of the study was to develop a computerized method for automated quantification of the 'A' (asymmetry) and 'B' (border cut-off) parameters, according to the ABCD rule for dermoscopy, thus reproducing human evaluation.

METHODS

Three hundred and thirty-one melanocytic lesion images, referring to 113 melanomas and 218 melanocytic nevi, acquired by means of a digital videodermatoscope, were considered. Images were evaluated by two experienced observers and by using computer algorithms developed by us. Clinical evaluation of asymmetry was performed by attributing scores to shape asymmetry and asymmetry of pigment distribution and structures, whereas computer evaluation of shape and pigment distribution asymmetries were based on the assessment of differences in area and lightness in the two halves of the image, respectively. Borders were evaluated both by clinicians and by the computer, by attributing a score to each border segment ending abruptly. Differences between nevus and melanoma values were evaluated using the chi-square test, while Cohen's Kappa index for agreement was employed for the evaluation of the concordance between human and computer.

RESULTS

Pigment distribution asymmetry appears the most striking parameter for melanoma diagnosis both for human and for automated diagnosis. A good concordance between clinicians and computer evaluation was achieved for all asymmetry parameters, and was excellent for border cut-off evaluation.

CONCLUSIONS

These algorithms enable a good reproduction of the 'A' and 'B' parameters of the ABCD rule for dermoscopy, and appear useful for diagnostic and learning purposes.

Noninvasive techniques for the evaluation of skin color

Visual assessment remains one of the "gold standard" methods of assessing skin color and a number of tools are currently available to reduce the interobserver variability. Ultraviolet light examination remains a mainstay of the assessment of pigmentary disorders, while polarized light photography is useful for the appraisal of dermal changes, in particular those related to vascularity. With the introduction of modern instruments, reflectance spectroscopy using tristimulus colorimeters or narrowband spectrophotometers provides a convenient, objective, and reproducible methodology for the evaluation of pigmentation and skin color. In vivo confocal scanning laser microscopy is a powerful technique for the examination of pigmented lesions, which shows promise in the detection and diagnosis of early melanoma. Dermoscopy is also useful for the differential diagnosis of benign melanocytic lesions and melanoma, and its use has been shown to significantly improve diagnostic accuracy.

Instrument-, age- and site-dependent variations of dermoscopic patterns of congenital melanocytic naevi: a multicentre study

BACKGROUND

Recently, we identified and described dermoscopic aspects, present with a higher frequency in congenital melanocytic lesions with respect to acquired naevi. We also classified small- and medium-sized congenital naevi (CN) into nine subtypes according to their macroscopic and dermoscopic aspects.

OBJECTIVES

Because the recognition of dermoscopic features may be instrument dependent, in this study, we wanted to check whether dermoscopic patterns specific for CN can be identified in digital images acquired by means of different instruments. We also wanted to check the validity of our previously proposed classification and assess possible age- and site-dependent variations of dermoscopic patterns and naevus subtypes.

PATIENTS/METHODS

Images corresponding to 384 small- or medium-sized CN were collected in eight different centres employing four different instruments. Lesion images were evaluated and checked for the presence of specific dermoscopic criteria, classified, and compared with a database of 350 acquired naevi.

RESULTS

Specific and unspecific dermoscopic features were identifiable in images acquired by means of all four instrument types. The mean number of identified features per lesion did not vary according to the instrument employed for the acquisition of the images; however, it was lower for lesions recorded employing low magnifications. The previously proposed classification was easily applied to the whole image database. The variegated naevus type was identified as a highly specific clinical/dermoscopic pattern. Dermoscopic features varied according to age and location. The globular type prevailed in subjects under 11 years of age and on the trunk, whereas the majority of reticular lesions were located on the limbs.

CONCLUSIONS

Because definite clinical and histological criteria for the diagnosis of the congenital nature of naevi are lacking, the use of dermoscopy can be of great help in identifying those lesions where the presence of specific dermoscopic features makes the diagnosis of CN more likely. Moreover, dermoscopy can be useful both for the classification of lesions already identified as congenital according to definite clinical and anamnestic data and for a possible correlation of naevus phenotype and dermoscopic patterns to the risk of developing a malignant melanoma in prospective studies.

Pigment distribution in melanocytic lesion images: a digital parameter to be employed for computer-aided diagnosis

BACKGROUND/PURPOSE

Since in early melanoma (MM) and especially in in situ MM differential structures, which are diagnostic for MM may be lacking, pigment distribution asymmetry represents an important diagnostic feature. Our aim was to automatically assess pigment distribution in images referring to MMs, atypical nevi (AN) and clearly benign nevi (BN), and to evaluate the diagnostic capability of numerical parameters describing a non homogeneous distribution of pigmentation.

METHODS

An image analysis program enabling the numerical assessment of pigment distribution in melanocytic lesions (ML), based on evaluation and comparison of red, green, blue (RGB) colour components inside image colour blocks, was employed on 459 videomicroscopic digital images, referring to 95 MMs, 76 AN and 288 BN.

RESULTS

Significant differences in pigment distribution parameters (mean RGB distance, variance and maximum distance) between the three ML populations were observed, permitting a good discrimination of MMs. On the test set comprising 230 lesion images, the area under the curve value of the receiver operating characteristic curve was 0.933. For a D score equal to 0, corresponding to the best diagnostic accuracy (86.6%), a sensitivity of 87.5% and a specificity of 85.7% were obtained.

CONCLUSION

This original evaluation method for digital pigment distribution, based on mathematical description and comparison of colours in different image blocks, provides numerical parameters to be implemented in image analysis programs for computer-aided MM diagnosis.

Dysplastic naevus vs. in situ melanoma: digital dermoscopy analysis

BACKGROUND

To date, much confusion exists about the biological significance of dysplastic naevi and about the relationship between melanocytic dysplasia and clinical atypia.

OBJECTIVES

To use a digital dermoscopy analyser with a series of 'borderline' pigmented skin lesions (i.e. dysplastic naevi and in situ melanomas) to find correlation between the studied variables and to determine their discriminating power with respect to histological diagnosis.

METHODS

The pigmented skin lesions (n = 174) were histologically examined by three experienced dermatopathologists and identified as in situ melanomas (n = 38) and dysplastic naevi (n = 136). The system evaluated 48 parameters as possible discriminant variables, grouped into four categories: geometry, colours, textures and islands of colour. Once the lesions were analysed (stepwise discriminant analysis), sensitivity, specificity and accuracy were calculated.

RESULTS

At the end of the stepwise procedure the percentage of cases classified correctly was 71.8%. Of 136 dysplastic naevi only 98 were classified correctly, while 27 of 38 in situ melanomas were recognized correctly.

CONCLUSIONS

We conclude that there are so far no digital dermoscopic criteria that can clearly distinguish dysplastic naevi from in situ melanomas.

Acquired melanocytic lesions and the decision to excise: role of color variegation and distribution as assessed by dermoscopy

BACKGROUND

Because melanoma may sometimes be difficult to differentiate from nevi with clinical atypia, many benign lesions also undergo surgical removal.

OBJECTIVE

To assess color type and distribution in dermoscopic melanocytic lesion images and to analyze the influence of color parameters on the diagnostic process and the decision to excise.

METHODS

Overall, 603 images, referring to 112 melanomas and 491 nevi, were retrospectively subdivided into four groups: "clearly benign," "follow-up," "dermoscopic atypical nevi," and "dermoscopic melanomas," according to their dermoscopic aspects. The frequency of color type, number, and asymmetry were evaluated on digital images.

RESULTS

With respect to lesions not eligible for excision according to dermoscopy (but excised for cosmetic reasons), those excised with a suspicion of malignancy showed a higher number of colors, whose distribution was also more asymmetric. Moreover, the frequency of the presence of black and blue-gray progressively increased from clearly benign lesions to atypical nevi and dermoscopic melanomas.

CONCLUSION

In dermoscopic images, color parameters are essential elements for the diagnosis of atypical nevus, which can be differentiated from both a clearly benign lesion and a melanoma. Furthermore, pigmentation asymmetry and the presence of blue-gray represent the main color features, which should lead to the decision to excise.

Dermoscopy for skin cancer detection

PURPOSE OF REVIEW

The worldwide incidence of melanoma and nonmelanoma skin cancers is increasing alarmingly. The development of new techniques such as dermoscopy leads to a consequent progress in skin cancers screening. The purpose of this review is to highlight recent advances in dermoscopy, reviewing primary research articles published in the last year.

RECENT FINDINGS

With the recent standardization of diagnostic procedures obtained by the Consensus Net Meeting on Dermoscopy and the definition of new melanoma-specific criteria, the efficacy in early melanoma diagnosis is improved. Dermoscopy is cost effective, leading to a decreased number of excised benign lesions, and the dermoscopic follow-up allows early detection of melanomas. However, the technique must be performed by experts in order not to miss melanomas. For this reason, instruction in dermoscopy is mandatory. Moreover, computer-aided diagnosis has been tested to be a valid support for physicians. Teledermoscopy is a new tool that allows a second expert opinion to manage atypical lesions.

SUMMARY

Dermoscopy opens up a new dimension on clinical morphology of skin lesions. Digital follow-up examinations, computer-aided diagnosis, and teledermoscopy are new facilities that will change the current management of skin cancers in general and melanoma in particular. Dermoscopy in the hands of experienced physicians has higher discriminatory power than naked-eye examination to detect skin cancers.

Colors in atypical nevi: a computer description reproducing clinical assessment

BACKGROUND/PURPOSE

Atypical nevi (AN) share some dermoscopic features with early melanoma (MM), and computer elaboration of digital images could represent a useful support to diagnosis to assess automatically colors in AN, and to compare the data with those referring to clearly benign nevi (BN) and MMs.

METHODS

An image analysis program enabling the numerical description of color areas in melanocytic lesions was used on 459 videomicroscopic images, referring to 76 AN, 288 clearly BN and 95 MMs.

RESULTS

Black, white and blue-gray were more frequently found in AN than in clearly BN, but less frequently than in MMs. Color area values significantly differed between the three groups.

CONCLUSION

The clinical-morphological interpretation of the numerical data, based on the mathematical description of the aspect and distribution of different color areas in different lesion types may contribute to the characterization of AN and their distinction from MMs.

Diagnostisch-dermatoskopische Algorithmen

Dermatoscopy (reflective light microscopy, dermoscopy) is a noninvasive technique with high sensitivity and specificity for in vivo visualization of melanocytic and non-melanocytic pigmented and non-pigmented skin tumors. To this end, knowledge of various algorithms and scores is important. The first part of this contribution in continuing education deals with differentiation between melanocytic and non-melanocytic skin tumors on the trunk and extremities. The second part describes the different diagnostic dermatoscopic algorithms.