Dermoscopy is a noninvasive technique that enables the clinician to perform direct microscopic examination of diagnostic features, not seen by the naked eye, in pigmented skin lesions. Diagnostic accuracy of dermoscopy has previously been assessed in meta-analyses including studies performed in experimental and clinical settings.
To assess the diagnostic accuracy of dermoscopy for the diagnosis of melanoma compared with naked eye examination by performing a meta-analysis exclusively on studies performed in a clinical setting.
We searched for publications from 1987 to January 2008 and found nine eligible studies. The selected studies compare diagnostic accuracy of dermoscopy with naked eye examination using a valid reference test on consecutive patients with a defined clinical presentation, performed in a clinical setting. Hierarchical summary receiver operator curve analysis was used to estimate the relative diagnostic accuracy for clinical examination with, and without, the use of dermoscopy.
We found the relative diagnostic odds ratio for melanoma, for dermoscopy compared with naked eye examination, to be 15.6 [95% confidence interval (CI) 2.9-83.7, P = 0.016]; removal of two outlier studies changed this to 9.0 (95% CI 1.5-54.6, P = 0.03).
Dermoscopy is more accurate than naked eye examination for the diagnosis of cutaneous melanoma in suspicious skin lesions when performed in the clinical setting.
[Show abstract][Hide abstract] ABSTRACT: In recent years, the incidence of skin cancer cases has risen, worldwide, mainly due to the prolonged exposure to harmful ultraviolet radiation. Concurrently, the computer-assisted medical diagnosis of skin cancer has undergone major advances, through an improvement in the instrument and detection technology, and the development of algorithms to process the information. Moreover, because there has been an increased need to store medical data, for monitoring, comparative and assisted-learning purposes, algorithms for data processing and storage have also become more efficient in handling the increase of data. In addition, the potential use of common mobile devices to register high-resolution images of skin lesions has also fueled the need to create real-time processing algorithms that may provide a likelihood for the development of malignancy. This last possibility allows even non-specialists to monitor and follow-up suspected skin cancer cases. In this review, we present the major steps in the pre-processing, processing and post-processing of skin lesion images, with a particular emphasis on the quantification and classification of pigmented skin lesions. We further review and outline the future challenges for the creation of minimum-feature, automated and real-time algorithms for the detection of skin cancer from images acquired via common mobile devices.
Journal of Medical Systems 11/2015; 39(177). DOI:10.1007/s10916-015-0354-8 · 2.21 Impact Factor
"Dermoscopy is an important in-vivo, non-invasive diagnostic technique that permits visualization of morphological features not visible with the naked eye. It greatly enhances the diagnostic accuracy for pigmented skin lesions [4–6]. Recent studies have shown that it also aids in the diagnosis of non-pigmented keratinizing skin lesions, including actinic keratosis and Bowen’s disease [7–15]. "
[Show abstract][Hide abstract] ABSTRACT: Nodular squamous cell carcinoma (SCC) and keratoacanthoma (KA) may mimic a variety of other benign and malignant non-pigmented nodules.
To analyze the dermoscopic characteristics of nodular SCC and KA.
Retrospective analysis of 50 nodular SCCs and 8 KAs collected from a tertiary dermatology referral center and a private dermatology practice in Melbourne, Australia, between 1 September 2009 and 1 October 2012. All lesions were nodules; defined as firm, elevated, round, palpable tumors with a diameter of 5 mm or more. Clinical and dermoscopic images were evaluated by two examiners in consensus.
Signs of keratinization were frequently observed and included keratin crust/scale (90% of SCCs, 100% of KAs), central keratin mass (32% of SCCs, 88% of KAs), white structureless areas (66% of SCCs, 50% of KAs), white circles (32% of SCCs, 38% of KAs) and white keratin pearls (14% of SCCs, 12% of KAs). Hemorrhage was present in 72% of SCCs and 88% of KAs and preferentially occurred centrally and in areas of keratinization. For nodular SCCs and KAs, we observed glomerular vessels (42% and 25% respectively), linear irregular vessels (36% and 25% respectively), atypical vessels (30% and 38% respectively) and hairpin vessels (30% and 25% respectively).
Hemorrhage, keratinization and vascular features (glomerular, hairpin and linear irregular morphologies) are useful in diagnosing both nodular SCC and KA. Further research on the comparative dermoscopic characteristics of a range of amelanotic nodules is important in order to improve diagnosis of these clinically challenging tumors.
"Thus, they provide additional diagnostic criteria to the dermatolo- gist. Dermoscopy enables better diagnosis as compared to unaided eye    with an improvement in diagnostic sensitivity of 10–30% . However, it has also been demonstrated that dermoscopy may actually lower the diagnostic accuracy in the hands of inexperienced dermatologists [10, 18–20], since this method requires great deal of experience to differentiate skin lesions . "
[Show abstract][Hide abstract] ABSTRACT: Image-based computer aided diagnosis systems have significant potential for screening and early detection of malignant melanoma. We review the state of the art in these systems and examine current practices, problems, and prospects of image acquisition, pre-processing, segmentation, feature extraction and selection, and classification of dermoscopic images. This paper reports statistics and results from the most important implementations reported to date. We compared the performance of several classifiers specifically developed for skin lesion diagnosis and discussed the corresponding findings. Whenever available, indication of various conditions that affect the technique's performance is reported. We suggest a framework for comparative assessment of skin cancer diagnostic models and review the results based on these models. The deficiencies in some of the existing studies are highlighted and suggestions for future research are provided.
International Journal of Biomedical Imaging 12/2013; 2013(7):323268. DOI:10.1155/2013/323268
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