Marco Burroni

Automated diagnosis of pigmented skin lesions.

Since advanced melanoma remains practically incurable, early detection is an important step toward a reduction in mortality. High expectations are entertained for a technique known as dermoscopy or epiluminescence light microscopy; however, evaluation of pigmented skin lesions by this method is often extremely complex and subjective. To obviate the problem of qualitative interpretation, methods based on mathematical analysis of pigmented skin lesions, such as digital dermoscopy analysis, have been developed. In the present study, we used a digital dermoscopy analyzer (DBDermo‐Mips system) to evaluate a series of 588 excised, clinically atypical, flat pigmented skin lesions (371 benign, 217 malignant). The analyzer evaluated 48 parameters grouped into 4 categories (geometries, colors, textures and islands of color), which were used to train an artificial neural network. To evaluate the diagnostic performance of the neural network and to check it during the training process, we used the error area over the receiver operating characteristic curve. The discriminating power of the digital dermoscopy analyzer plus artificial neural network was compared with histologic diagnosis. A feature selection procedure indicated that as few as 13 of the variables were sufficient to discriminate the 2 groups of lesions, and this also ensured high generalization power. The artificial neural network designed with these variables enabled a diagnostic accuracy of about 94%. In conclusion, the good diagnostic performance and high speed in reading and analyzing lesions (real time) of our method constitute an important step in the direction of automated diagnosis of pigmented skin lesions.

Melanoma Computer-Aided Diagnosis Reliability and Feasibility Study

Background: Differential diagnosis of melanoma from melanocytic nevi is often not straightforward. Thus, a growing interest has developed in the last decade in the automated analysis of digitized images obtained by epiluminescence microscopy techniques to assist clinicians in differentiating early melanoma from benign skin lesions. Purpose: The aim of this study was to evaluate diagnostic accuracy provided by different statistical classifiers on a large set of pigmented skin lesions grabbed by four digital analyzers located in two different dermatological units. Experimental Design: Images of 391melanomas and 449 melanocytic nevi were included in the study. A linear classifier was built by using the method of receiver operating characteristic curves to identify a threshold value for a fixed sensitivity of 95%. A K-nearest-neighbor classifier, a nonparametric method of pattern recognition, was constructed using all available image features and trained for a sensitivity of 98% on a large exemplar set of lesions. Results: On independent test sets of lesions, the linear classifier and the K-nearest-neighbor classifier produced a mean sensitivity of 95% and 98% and a mean specificity of 78% and of 79%, respectively. Conclusions: In conclusion, our study suggests that computer-aided differentiation of melanoma from benign pigmented lesions obtained with DB-Mips is feasible and, above all, reliable. In fact, the same instrumentations used in different units provided similar diagnostic accuracy. Whether this would improve early diagnosis of melanoma and/or reducing unnecessary surgery needs to be demonstrated by a randomized clinical trial.

Computerized evaluation of pigmented skin lesion images recorded by a videomicroscope: comparison between polarizing mode observation and oil/slide mode observation.

Background/aims: It has now been established that ELM significantly improves the clinical diagnosis of pigmented skin lesions, particularly when associated with image analysis on digital pictures.

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.

Digital dermoscopy in clinical practise: a three-centre analysis.

Background: Early detection of cutaneous melanoma is the most important step to improve prognosis. In recent years objective techniques have been developed to improve diagnostics of pigmented lesions superior to the naked eye. Digital dermoscopy offers several advantages such as independence from the investigator, format ready for teledermatology and image storage, and comparability.

Digital epiluminescence microscopy: usefulness in the differential diagnosis of cutaneous pigmentary lesions. A statistical comparison between visual and computer inspection.

Epiluminescence light microscopy (ELM) has been confirmed to be a useful tool for the diagnosis of pigmented skin lesions. The application of digital systems to epiluminescence represents the latest attempt to improve the diagnosis of cutaneous melanoma. The aim of this study was to compare the diagnostic accuracy of one of these systems, the DB-Dermo MIPS, with the accuracy of well-trained dermatologists using the ELM technique in order to establish the real usefulness of this instrument and to verify how much it can help the clinician make a diagnosis in a clinical setting. During a campaign for the early diagnosis of cutaneous melanoma, 311 patients with non-melanocytic lesions, common naevi, dysplastic naevi and melanomas underwent clinical diagnosis using ELM, computerized evaluation with DB-Dermo MIPS and skin biopsy. Sensitivity, specificity, true and negative predictive value were evaluated for epiluminescence and digital epiluminescence. Our study revealed that the inspection of pigmented skin lesions by digital epiluminescence has a better diagnostic accuracy than that of a trained dermatologist using the epiluminescence technique only. In our experience, this computerized system can play an essential role in the detection of early melanomas.

Melanocytic skin lesions and pregnancy: digital dermoscopy analysis.

Background: Very few studies have tried to clarify how pregnancy influences the morphology of pigmented skin lesions (PSL). Our purpose was to objectively determine, by digital dermoscopy analysis (DDA), any dermoscopic changes of acquired melanocitic nevi during pregnancy and after 1 year from delivery.

Impact of digital dermoscopy analysis on the decision to follow up or to excise a pigmented skin lesion: a multicentre study.

Background: The quality of early malignant melanoma (MM) diagnosis is dependent on the experience of dermatologists, tools like dermoscopy and histopathology, and awareness and education of the studied population. Does a higher rate of excision of pigmented skin lesions (PSL) increase the rate of detected melanomas?

Digital dermoscopy analysis for automated diagnosis of pigmented skin lesions1

Melanoma is increasing in frequency worldwide. In Italy the current incidence of this tumor is about 10–15 new cases per year per 100,000 population.1 Despite much research into the field of melanoma biology and treatment that has already been done, this tumor is still practically incurable when diagnosed in an advanced stage. Early diagnosis is therefore of utmost importance to reduce the mortality rate.2 Clinical recognition of melanoma is, however, not always easy. Conventional clinical criteria for early diagnosis of melanoma are summarized by the ABCDE formula: A stands for asymmetry, B for border irregularity, C for color variegation, D for diameter 5 mm, and E for evolution (morphologic changes of the lesion). Although ABCDE clinical criteria represent a simple and reliable guide for self-examination, they cannot always be considered an effective approach to reach high diagnostic accuracy for melanoma, since numerous benign, pigmented skin lesions (PSLs) may mimic melanoma by using this method. From a diagnostic viewpoint, accuracy has greatly been improved since dermatologists have started to use new techniques, such as epiluminescence light microscopy (ELM), which magnifies lesions and enable them to be examined down to the dermo-epidermal junction.3,4 By ELM, new morphologic features of melanoma can be visualized, facilitating early diagnosis in most cases.5,6 Many studies have provided specific epiluminescence diagnostic criteria, paving the way for a new semeiology of patterns, colors, pigmentation intensity, configuration, regularity, and margin and surface characteristics. Qualitative evaluation of the many morphologic characteristics of PSLs observable by ELM, however, is often extremely complex and subjective.7 With the aim of obviating the problem of qualitative interpretation of dermatoscopic features, methods and instruments based on mathematical analysis of PSLs have recently been developed (Table 1).8–12 These methods are based on computerized analysis of digital images that are obtained by ELM. An example is digital dermoscopy analysis (DDA), which gathers numerical data and enables PSL images to be described objectively.

Digital dermoscopy analysis of atypical pigmented skin lesions: a stepwise logistic discriminant analysis approach

Background: Digital microscopy is a non‐invasive diagnostic technique enabling determination of characteristics that cannot be appreciated by direct observation. If correctly applied, this technique can be useful for the diagnosis of pigmented skin lesions.