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Morgado-Carrasco, X. Fustà-Novell, X. Bosch-Amate, P. Giavedoni" "autores" => array:4 [ 0 => array:4 [ "nombre" => "D." "apellidos" => "Morgado-Carrasco" "email" => array:1 [ 0 => "morgadodaniel8@gmail.com" ] "referencia" => array:1 [ 0 => array:2 [ "etiqueta" => "<span class="elsevierStyleSup">*</span>" "identificador" => "cor0005" ] ] ] 1 => array:2 [ "nombre" => "X." "apellidos" => "Fustà-Novell" ] 2 => array:2 [ "nombre" => "X." "apellidos" => "Bosch-Amate" ] 3 => array:2 [ "nombre" => "P." "apellidos" => "Giavedoni" ] ] "afiliaciones" => array:1 [ 0 => array:2 [ "entidad" => "Servicio de Dermatología, Hospital Clínic de Barcelona, Universitat de Barcelona, Barcelona, Spain" "identificador" => "aff0005" ] ] "correspondencia" => array:1 [ 0 => array:3 [ "identificador" => "cor0005" "etiqueta" => "⁎" "correspondencia" => "Corresponding author." ] ] ] ] "titulosAlternativos" => array:1 [ "es" => array:1 [ "titulo" => "FR - Nuevas tecnologías que prometen revolucionar el diagnóstico del melanoma cutáneo" ] ] "textoCompleto" => "<span class="elsevierStyleSections"><p id="par0005" class="elsevierStylePara elsevierViewall">The diagnosis of cutaneous melanoma is complex. Histopathology is the gold standard for diagnosis of melanocytic lesions, although its intraobserver concordance and interobserver concordance are low. In addition, it depends on the experience of the pathologist and can therefore be prone to diagnostic error.<a class="elsevierStyleCrossRef" href="#bib0035"><span class="elsevierStyleSup">1</span></a> It seems necessary to incorporate new tools for the evaluation of melanocytic lesions.</p><p id="par0010" class="elsevierStylePara elsevierViewall">Recently published studies on the use of artificial intelligence for the diagnosis of cutaneous lesions have generated much interest. In 2017, Esteva et al.<a class="elsevierStyleCrossRef" href="#bib0040"><span class="elsevierStyleSup">2</span></a> published the results of a revolutionary study in which they evaluated the ability to distinguish between benign melanocytic lesions and melanoma and between seborrheic keratosis and cutaneous carcinoma after training with 129 450 images of cutaneous lesions from a deep convolutional neural network (DCNN). The diagnostic accuracy of the approach was compared with that of 21 dermatologists. The reliability of both the DCNN and the dermatologists was comparable. Haenssle et al.<a class="elsevierStyleCrossRef" href="#bib0045"><span class="elsevierStyleSup">3</span></a> published the results of a study (“man vs machine”) in which they compared the diagnostic accuracy of the DCNN Google Inception-v4 (trained with >100 000 images) with that of 58 dermatologists, 30 of whom were experts in dermoscopy. The authors used a series of 100 dermoscopy images and worked in 2 stages: the first, with no clinical information; and the second, with additional clinical images and information. They measured sensitivity, specificity, and the area under the curve (AUC). The DCNN reached an average AUC that was significantly superior to the dermatologists in both phases of the study (0.86 vs 0.79; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>.01). In phase 2, the dermatologists improved their sensitivity, reaching 88.9%. Even so, the DCNN obtained greater specificity (82.5% versus 75.7%) and was superior to most dermatologists. One of the main drawbacks of the DCNN is the number of images necessary to “train” it (>100 000), which makes it difficult and costly. Fujisawa et al.<a class="elsevierStyleCrossRef" href="#bib0050"><span class="elsevierStyleSup">4</span></a> trained a DCNN to distinguish between 14 diagnoses using only 4860 images of benign and malignant cutaneous tumors and compared its diagnostic accuracy with that of 13 dermatologists and 9 dermatology residents. The DCNN had an accuracy of 92.4%, which was significantly higher than that of the dermatologists and residents (85.3% and 74.4%; <span class="elsevierStyleItalic">P</span><span class="elsevierStyleHsp" style=""></span><<span class="elsevierStyleHsp" style=""></span>.001).</p><p id="par0015" class="elsevierStylePara elsevierViewall">The recently developed pigmented lesion assay (PLA) (<a class="elsevierStyleCrossRef" href="#tbl0005">Table 1</a>) is a noninvasive gene expression assay consisting of an adhesive patch that makes it possible to rule out cutaneous melanoma with a negative predictive value >99%, which is considerably higher than that of histology (83%). Given its high negative predictive value, the PLA reduces the number of lesions removed to diagnose a melanoma (usually between 8 and 20). Hornberger et al.<a class="elsevierStyleCrossRef" href="#bib0055"><span class="elsevierStyleSup">5</span></a> compared the costs of the PLA with those of a standard biopsy procedure, histologic diagnosis, medical supervision, and follow-up. With a cost of $500, the authors concluded that the PLA can reduce the costs associated with the diagnosis of a lesions suspected of being a melanoma by 47%. The PLA would reduce the number of surgical procedures, undiagnosed melanomas, and costs.</p><elsevierMultimedia ident="tbl0005"></elsevierMultimedia><p id="par0020" class="elsevierStylePara elsevierViewall">The diagnosis of melanocytic lesions is complex. New technological tools based on artificial intelligence and gene expression promise to simplify this process and reduce the number of diagnostic and therapeutic errors.</p></span>" "pdfFichero" => "main.pdf" "tienePdf" => true "PalabrasClave" => array:1 [ "en" => array:1 [ 0 => array:4 [ "clase" => "keyword" "titulo" => "Keywords" "identificador" => "xpalclavsec1237574" "palabras" => array:6 [ 0 => "Melanoma" 1 => "Melanocytic lesions" 2 => "Artificial intelligence" 3 => "Diagnosis" 4 => "Dermoscopy" 5 => "Gene expression" ] ] ] ] "NotaPie" => array:1 [ 0 => array:2 [ "etiqueta" => "☆" "nota" => "<p class="elsevierStyleNotepara" id="npar0015">Please cite this article as: Morgado-Carrasco D, Fustà-Novell X, Bosch-Amate X, Giavedoni P. FR - Nuevas tecnologías que prometen revolucionar el diagnóstico del melanoma cutáneo. Actas Dermosifiliogr. 2020;111:329–330.</p>" ] ] "multimedia" => array:1 [ 0 => array:8 [ "identificador" => "tbl0005" "etiqueta" => "Table 1" "tipo" => "MULTIMEDIATABLA" "mostrarFloat" => true "mostrarDisplay" => false "detalles" => array:1 [ 0 => array:3 [ "identificador" => "at1" "detalle" => "Table " "rol" => "short" ] ] "tabla" => array:3 [ "leyenda" => "<p id="spar0010" class="elsevierStyleSimplePara elsevierViewall">Abbreviations: <span class="elsevierStyleItalic">LINC00518</span>, long intergenic non–protein-coding RNA 518; <span class="elsevierStyleItalic">PRAME</span>, preferentially expressed antigen in melanoma.</p>" "tablatextoimagen" => array:1 [ 0 => array:2 [ "tabla" => array:1 [ 0 => """ <table border="0" frame="\n \t\t\t\t\tvoid\n \t\t\t\t" class=""><thead title="thead"><tr title="table-row"><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Mechanism of Action \t\t\t\t\t\t\n \t\t\t\t\t\t</th><th class="td" title="\n \t\t\t\t\ttable-head\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t" scope="col" style="border-bottom: 2px solid black">Detection of Expression of the Genes <span class="elsevierStyleItalic">LINC00518</span> and <span class="elsevierStyleItalic">PRAME</span> \t\t\t\t\t\t\n \t\t\t\t\t\t</th></tr></thead><tbody title="tbody"><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Sampling \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Noninvasive adhesive patch applied to the suspected melanocytic lesion \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Time to reading \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">72<span class="elsevierStyleHsp" style=""></span>h \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Negative predictive value \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">>99% \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Positive result detected \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">The lesion should be removed and sent for a histopathology workup \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Negative result detected \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Given the high negative predictive value, the diagnosis of melanoma can be ruled out and the lesion should not be removed \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Contribution to clinical practice \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Considerably reduced number of lesions to be removed in order to diagnose a melanoma<a class="elsevierStyleCrossRef" href="#tblfn0005"><span class="elsevierStyleSup">a</span></a>Reduced number of surgical procedures and waiting listsReduced costs associated with surgery, loss of productivity, complications, follow-up visits, dressings, and removal of stitches \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Cost \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">In theory, around $500 \t\t\t\t\t\t\n \t\t\t\t</td></tr><tr title="table-row"><td class="td-with-role" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t ; entry_with_role_rowhead " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Limitations \t\t\t\t\t\t\n \t\t\t\t</td><td class="td" title="\n \t\t\t\t\ttable-entry\n \t\t\t\t " align="left" valign="\n \t\t\t\t\ttop\n \t\t\t\t">Not useful in melanocytic lesions on the palms, soles, or mucous membranes \t\t\t\t\t\t\n \t\t\t\t</td></tr></tbody></table> """ ] "imagenFichero" => array:1 [ 0 => "xTab2307226.png" ] ] ] "notaPie" => array:1 [ 0 => array:3 [ "identificador" => "tblfn0005" "etiqueta" => "a" "nota" => "<p class="elsevierStyleNotepara" id="npar0005">The number of lesions to be removed for diagnosing a melanoma was between 8 and 30, depending on the series analyzed.</p> <p class="elsevierStyleNotepara" id="npar0010">Source: Gerami et al.<a class="elsevierStyleCrossRef" href="#bib0060"><span class="elsevierStyleSup">6</span></a></p>" ] ] ] "descripcion" => array:1 [ "en" => "<p id="spar0005" class="elsevierStyleSimplePara elsevierViewall">Characteristics of the Pigmented Lesion Assay.</p>" ] ] ] "bibliografia" => array:2 [ "titulo" => "References" "seccion" => array:1 [ 0 => array:2 [ "identificador" => "bibs0015" "bibliografiaReferencia" => array:6 [ 0 => array:3 [ "identificador" => "bib0035" "etiqueta" => "1" "referencia" => array:1 [ 0 => array:2 [ "contribucion" => array:1 [ 0 => array:2 [ "titulo" => "Pathologists’ diagnosis of invasive melanoma and melanocytic proliferations: observer accuracy and reproducibility study" "autores" => array:1 [ 0 => array:2 [ "etal" => true "autores" => array:6 [ 0 => "J.G. 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año/Mes | Html | Total | |
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2024 Noviembre | 4 | 6 | 10 |
2024 Octubre | 64 | 40 | 104 |
2024 Septiembre | 59 | 23 | 82 |
2024 Agosto | 86 | 64 | 150 |
2024 Julio | 63 | 29 | 92 |
2024 Junio | 54 | 27 | 81 |
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2024 Febrero | 56 | 34 | 90 |
2024 Enero | 50 | 36 | 86 |
2023 Diciembre | 37 | 15 | 52 |
2023 Noviembre | 50 | 24 | 74 |
2023 Octubre | 52 | 27 | 79 |
2023 Septiembre | 46 | 31 | 77 |
2023 Agosto | 22 | 11 | 33 |
2023 Julio | 37 | 33 | 70 |
2023 Junio | 34 | 17 | 51 |
2023 Mayo | 33 | 23 | 56 |
2023 Abril | 17 | 17 | 34 |
2023 Marzo | 47 | 27 | 74 |
2023 Febrero | 38 | 17 | 55 |
2023 Enero | 37 | 38 | 75 |
2022 Diciembre | 56 | 48 | 104 |
2022 Noviembre | 50 | 33 | 83 |
2022 Octubre | 41 | 19 | 60 |
2022 Septiembre | 67 | 46 | 113 |
2022 Agosto | 54 | 39 | 93 |
2022 Julio | 58 | 38 | 96 |
2022 Junio | 28 | 38 | 66 |
2022 Mayo | 24 | 59 | 83 |
2022 Abril | 38 | 22 | 60 |
2022 Marzo | 32 | 51 | 83 |
2022 Febrero | 44 | 38 | 82 |
2022 Enero | 52 | 38 | 90 |
2021 Diciembre | 43 | 30 | 73 |
2021 Noviembre | 44 | 41 | 85 |
2021 Octubre | 41 | 38 | 79 |
2021 Septiembre | 20 | 34 | 54 |
2021 Agosto | 25 | 25 | 50 |
2021 Julio | 14 | 23 | 37 |
2021 Junio | 19 | 26 | 45 |
2021 Mayo | 28 | 39 | 67 |
2021 Abril | 37 | 41 | 78 |
2021 Marzo | 25 | 30 | 55 |
2021 Febrero | 25 | 22 | 47 |
2021 Enero | 20 | 17 | 37 |
2020 Diciembre | 19 | 10 | 29 |
2020 Noviembre | 19 | 14 | 33 |
2020 Octubre | 26 | 16 | 42 |
2020 Septiembre | 26 | 12 | 38 |
2020 Agosto | 33 | 16 | 49 |
2020 Julio | 49 | 19 | 68 |
2020 Junio | 77 | 45 | 122 |
2020 Mayo | 60 | 22 | 82 |
2020 Abril | 1 | 0 | 1 |