Dermoscopy report: Proposal for standardization - Results of a consensus meeting of the International Dermoscopy Society
ABSTRACT 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.
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.
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.
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).
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.
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.
[Show abstract] [Hide abstract]
ABSTRACT: Dermoscopy has dramatically developed, becoming a well-established routine technique in many countries in the mid-1980s. Dermoscopy allows physicians to observe structures and colors otherwise not visible to unaided eyes, increasing melanoma diagnostic accuracy by up to 35%. Moreover, dermoscopy allows for increases in the number of diagnosed and excised melanomas together with a reduction in the number of unnecessary excisions. New data are continuously acquired mostly on melanoma diagnosis, follow-up of melanocytic lesions and nevogenesis. Short-term 3-month follow-up is the optimum time interval for identifying minimal changes in featureless melanomas. Nevertheless, long-term follow-up is similarly useful for the recognition of changes in melanomas with very low rates of growth. In the last few years a huge number of publications on dermoscopy have been published. The aim of this review is to summarize the most important recent advances in dermoscopy.Expert Review of Dermatology 01/2014; 7(5). DOI:10.1586/edm.12.47
[Show abstract] [Hide abstract]
ABSTRACT: By means of this study, a detection algorithm for the "pigment network" in dermoscopic images is presented, one of the most relevant indicators in the diagnosis of melanoma. The design of the algorithm consists of two blocks. In the first one, a machine learning process is carried out, allowing the generation of a set of rules which, when applied over the image, permit the construction of a mask with the pixels candidates to be part of the pigment network. In the second block, an analysis of the structures over this mask is carried out, searching for those corresponding to the pigment network and making the diagnosis, whether it has pigment network or not, and also generating the mask corresponding to this pattern, if any. The method was tested against a database of 220 images, obtaining 86% sensitivity and 81.67% specificity, which proves the reliability of the algorithm.Computers in biology and medicine 11/2013; 44. DOI:10.1016/j.compbiomed.2013.11.002 · 1.27 Impact Factor
European journal of dermatology: EJD 08/2014; 24(5). DOI:10.1684/ejd.2014.2407 · 1.95 Impact Factor