In Vivo Evaluation of Melanoma Thickness by Multispectral Imaging and An Artificial Neural Network. A Retrospective Study on 250 Cases of Cutaneous Melanoma

Multispectral Imaging Algorithm Predicts Breslow Thickness of Melanoma

Breslow thickness is a major prognostic factor for melanoma. It is based on histopathological evaluation, and thus it is not available to aid clinical decision making at the time of the initial melanoma diagnosis. In this work, we assessed the efficacy of multispectral imaging (MSI) to predict Breslow thickness and developed a classification algorithm to determine optimal safety margins of the melanoma excision. First, we excluded nevi from the analysis with a novel quantitative parameter. Parameter s’ could differentiate nevi from melanomas with a sensitivity of 89.60% and specificity of 88.11%. Following this step, we have categorized melanomas into three different subgroups based on Breslow thickness (≤1 mm, 1–2 mm and >2 mm) with a sensitivity of 78.00% and specificity of 89.00% and a substantial agreement (κ = 0.67; 95% CI, 0.58–0.76). We compared our results to the performance of dermatologists and dermatology residents who assessed dermoscopic and clinical images of these melanomas, and reached a sensitivity of 60.38% and specificity of 80.86% with a moderate agreement (κ = 0.41; 95% CI, 0.39–0.43). Based on our findings, this novel method may help predict the appropriate safety margins for curative melanoma excision.

Metamorphosis of melanoma. Trends in size and thickness of cutaneous melanoma over one decade at the Istituto Nazionale Tumori, Milan

Aims and background

Messages about the description of the clinical features of cutaneous melanoma (CM) have remained unchanged since 1985, when the ABCD (Asymmetry, Border irregularity, Color variegation, Diameter >6 mm) rule for melanoma detection was formulated. Given the significant shift to the diagnosis of earlier-stage CMs over the past decades, it is reasonable to think that also the clinical aspects of the disease might have changed. The aim of this study was to examine trends in the presentation of CM over the last decade at our Institution, focusing on two characteristics of the disease: size and thickness.

Methods

A retrospective study was conducted including 1,603 primary invasive CMs seen and treated at the Unit for Melanoma Detection at our Institute between January 1997 and December 2006.

Results

The results showed a trend towards smaller CMs, with a difference of 3 mm in median size from the beginning to the end of the period. Detection of small (≤6 mm) CMs increased at a rate of about 1.5% per year, with a current ratio of 25% with respect to all CMs. Thickness remained substantially unchanged over time.

Conclusions

Physicians must be aware that the characteristics of melanoma have undergone a metamorphosis over the years and the ABCD signs cannot be relied on for adequate sensitivity to further the early detection of CM.

Band selection in spectral imaging for non-invasive melanoma diagnosis

A method consisting of the combination of the Synthetic Minority Over-Sampling TEchnique (SMOTE) and the Sequential Forward Floating Selection (SFFS) technique is used to do band selection in a highly imbalanced, small size, two-class multispectral dataset of melanoma and non-melanoma lesions. The aim is to improve classification rate and help to identify those spectral bands that have a more important role in melanoma detection. All the processing steps were designed taking into account the low number of samples in the dataset, situation that is quite common in medical cases. The training/test sets are built using a Leave-One-Out strategy. SMOTE is applied in order to deal with the imbalance problem, together with the Qualified Majority Voting scheme (QMV). Support Vector Machines (SVM) is the classification method applied over each balanced set. Results indicate that all melanoma lesions are correctly classified, using a low number of bands, reaching 100% sensitivity and 72% specificity when considering nine (out of a total of 55) spectral bands.

Evaluation of cutaneous melanoma thickness by digital dermoscopy analysis: a retrospective study

Digital dermoscopy analysis (DDA) exploits computerized analysis of digital images and offers the possibility of parametric analysis of morphological aspects of pigmented skin lesions by means of integration with dedicated software. We conducted a study by DDA in 141 melanomas, with the aim assessing whether the numerical variables extrapolated by univariate logistic analysis could be used in a system of multivariate analysis to predict melanoma thickness before surgery. Melanoma images were evaluated for 49 DDA parameters. Logistic analysis was conducted to identify statistically significant variables. The leave-one-out method was used to evaluate the predictive representations of rules for stepwise logistic classification. The percentage of correctly classified cases was calculated by a classification matrix. Melanomas less than 1 mm had a smaller area, faded borders and were more symmetrical than melanomas greater than 1 mm. The latter had a bluer colour and more random disposition of elements. The accuracy was 86.5%. Specifically, 97 of 108 thin melanomas (specificity 89.8%) and 25 of 33 thick melanomas (sensitivity 75.7%) were correctly classified. In conclusion, the predictive value of DDA for melanoma thickness was quite good. Moreover, DDA allowed us to know objectively those dermoscopic features important in the differentiation between thick and thin melanoma. However, further studies should be performed in a prospective setting before the clinical application.

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.

In vivo optical properties of melanocytic skin lesions: common nevi, dysplastic nevi and malignant melanoma

We present an in vivo study of the optical properties of common nevi, dysplastic nevi and malignant melanoma skin lesions in human subjects. Reflectance spectra were measured on 1379 skin lesions, in the visible and near-infrared spectral regions, using a spectral imaging system, in a clinical setting. Analysis of the data using a reflectance model revealed differences between the optical properties of melanin present in nevi and melanoma lesions. These differences, which are in agreement with our previous observations on average reflectance spectra, may be potentially useful for the noninvasive characterization of pigmented skin lesions and the early diagnosis of melanoma.

Current and emerging technologies in melanoma diagnosis: the state of the art

Relative to other specialties, dermatologists have been slow to adopt advanced technologic diagnostic aids. Most skin disease can be diagnosed by simple visual inspection, and the skin is readily accessible for a diagnostic biopsy. Diagnostic aids, such as total body photography and dermoscopy, improve the clinician's ability to diagnose melanoma beyond unaided visual inspection, however, and are now considered mainstream methods for early detection. Emerging technologies such as in vivo reflectance confocal microscopy are currently being investigated to determine their utility for noninvasive diagnosis of melanoma. This review summarizes the currently available cutaneous imaging devices and new frontiers in noninvasive diagnosis of skin disease. We anticipate that multimodal systems that combine different imaging technologies will further improve our ability to detect, at the bedside, melanoma at an earlier stage.

In vivo characterization of melanin in melanocytic lesions: spectroscopic study on 1671 pigmented skin lesions

The purpose of this study is to determine the role of melanin in the various steps of progression of melanocytic neoplasia. To this aim, we perform a retrospective analysis on 1671 multispectral images of in vivo pigmented skin lesions previously recruited in the framework of a study focused on the computer-assisted diagnosis of melanoma. The series included 288 melanomas in different phases of progression, i.e., in situ, horizontal and vertical growth phase invasive melanomas, 424 dysplastic nevi, and other 957 melanocytic lesions. Analysis of the absorbance spectra in the different groups shows that the levels of eumelanin and pheomelanin increase and decrease, respectively, from dysplastic nevi to invasive melanomas. In both cases, the trend of melanin levels is associated to the progression from dysplastic nevi to vertical growth phase melanomas, reflecting a possible hierarchy in the natural history of the early phases of the disease. Our results suggest that diffuse reflectance spectroscopy used to differentiate eumelanin and pheomelanin in in vivo lesions is a promising technique useful to develop better strategies for the characterization of various melanocytic lesions, for instance, by monitoring melanin in a time-lapse study of a lesion that was supposed to be benign.