Validation of an integrated dermoscopic scoring method in an European teledermoscopy web platform: the iDScore project for early detection of melanoma.


Journal

Journal of the European Academy of Dermatology and Venereology : JEADV
ISSN: 1468-3083
Titre abrégé: J Eur Acad Dermatol Venereol
Pays: England
ID NLM: 9216037

Informations de publication

Date de publication:
Mar 2020
Historique:
received: 25 04 2019
accepted: 07 08 2019
pubmed: 30 8 2019
medline: 5 1 2021
entrez: 30 8 2019
Statut: ppublish

Résumé

Although live and teledermoscopic examination has been successfully used to achieve non-invasive diagnosis of melanocytic skin lesions (MSLs), early melanoma (EM) and atypical nevi (AN) continue to be a challenge, and none of the various algorithms proposed have been sufficiently accurate. We designed a scoring classifier diagnostic method, the iDScore that combines clinical data of the patient with dermoscopic features of the MSL. To test the accuracy of the iDScore in differentiating EM from AN in a teledermoscopy setting and to compare it with intuitive diagnosis, the ABCD rule and the seven-point checklist. A dedicated teledermoscopy web platform was designed. This involved the following: (i) collecting a large integrated clinical-historical-dermoscopic data set of difficult MSLs from eight European dermatology centres; (ii) online testing, education and training in using the iDScore. A total of 904 images were combined with age, sex, lesion diameter and body site data and evaluated on the platform by 111 participants with four levels of skill in dermoscopy. Each testing session consisted of 30 blind cases to examine consecutively by the above four methods. 'Management decisions' and personal participant data were also recorded. iDScore-aided diagnosis achieved satisfactory diagnostic accuracy for all lesions, irrespective of centre of affiliation, showing an average AUC of 0.776 in all participant testing sessions. All skill groups improved their accuracy by 10-16% with respect to intuitive diagnosis and the other methods, showing high concordance and avoiding wrong management decisions. We demonstrated the validity of the iDScore method for managing suspicious MSLs in a large multicentric data set and a teledermoscopic setting. The platform designed for the iDScore project provides ready support for physicians of any dermoscopy skill level and is useful for education and training.

Sections du résumé

BACKGROUND BACKGROUND
Although live and teledermoscopic examination has been successfully used to achieve non-invasive diagnosis of melanocytic skin lesions (MSLs), early melanoma (EM) and atypical nevi (AN) continue to be a challenge, and none of the various algorithms proposed have been sufficiently accurate. We designed a scoring classifier diagnostic method, the iDScore that combines clinical data of the patient with dermoscopic features of the MSL.
OBJECTIVE OBJECTIVE
To test the accuracy of the iDScore in differentiating EM from AN in a teledermoscopy setting and to compare it with intuitive diagnosis, the ABCD rule and the seven-point checklist.
MATERIALS AND METHODS METHODS
A dedicated teledermoscopy web platform was designed. This involved the following: (i) collecting a large integrated clinical-historical-dermoscopic data set of difficult MSLs from eight European dermatology centres; (ii) online testing, education and training in using the iDScore. A total of 904 images were combined with age, sex, lesion diameter and body site data and evaluated on the platform by 111 participants with four levels of skill in dermoscopy. Each testing session consisted of 30 blind cases to examine consecutively by the above four methods. 'Management decisions' and personal participant data were also recorded.
RESULTS RESULTS
iDScore-aided diagnosis achieved satisfactory diagnostic accuracy for all lesions, irrespective of centre of affiliation, showing an average AUC of 0.776 in all participant testing sessions. All skill groups improved their accuracy by 10-16% with respect to intuitive diagnosis and the other methods, showing high concordance and avoiding wrong management decisions.
CONCLUSION CONCLUSIONS
We demonstrated the validity of the iDScore method for managing suspicious MSLs in a large multicentric data set and a teledermoscopic setting. The platform designed for the iDScore project provides ready support for physicians of any dermoscopy skill level and is useful for education and training.

Identifiants

pubmed: 31465600
doi: 10.1111/jdv.15923
doi:

Types de publication

Comparative Study Journal Article Multicenter Study Validation Study

Langues

eng

Sous-ensembles de citation

IM

Pagination

640-647

Informations de copyright

© 2019 European Academy of Dermatology and Venereology.

Références

Whiteman DC, Green AC, Olsen CM. The growing burden of invasive melanoma: projections of incidence rates and numbers of new cases in six susceptible populations through 2031. J Invest. Dermatol 2016; 136: 1161-1171.
Vestergaard ME, Macaskill P, Holt PE, Menzies SW. Dermoscopy compared with naked eye examination for the diagnosis of primary melanoma: a meta-analysis of studies performed in a clinical setting. Br J Dermatol 2008; 159: 669-676.
Chuchu N, Dinnes J, Takwoingi Y et al. Teledermatology for diagnosing skin cancer in adults. Cochrane Database Syst Rev 2018; 12: CD013193.
Friedman RJ, Rigel DS, Silverman MK et al. Malignant melanoma in the 1990s: the continued importance of early detection and the role of physician examination and self-examination of the skin. CA Cancer J Clin 1991; 41: 201-226.
Kittler H, Pehamberger H, Wolff K, Binder M. Diagnostic accuracy of dermoscopy. Lancet Oncol 2002; 3: 159-165.
Argenziano G, Soyer HP. Dermoscopy of pigmented skin lesions-a valuable tool for early diagnosis of melanoma. Lancet Oncol 2001; 2: 443-449.
Micali G, Verzì AE, Lacarrubba F. Alternative uses of dermoscopy in daily clinical practice: an update. J Am Acad Dermatol 2018; 79: 1117-1132.e1.
Menzies SW, Ingvar C, McCarthy WH. A sensitivity and specificity analysis of the surface microscopy features of invasive melanoma. Melanoma Res 1996; 6: 55-62.
Nachbar F. The ABCD rule of dermatoscopy. High prospective value in the diagnosis of doubtful melanocytic skin lesions. J Am Acad Dermatol 1994; 30: 551-559.
Argenziano G, Catricalà C, Ardigo M et al. Seven-point checklist of dermoscopy revisited. Br J Dermatol 2011; 164: 785-790.
Lallas A, Kyrgidis A, Koga H et al. The BRAAFF checklist: a new dermoscopic algorithm for diagnosing acral melanoma. Br J Dermatol 2015; 173: 1041-1049.
Carrera C, Marchetti MA, Dusza SW et al. Validity and reliability of dermoscopic criteria used to differentiate nevi from melanoma: a web-based international dermoscopy society study. JAMA Dermatol 2016; 152: 798-806.
Tognetti L, Cevenini G, Moscarella E et al. An integrated clinical-dermoscopic risk scoring system for the differentiation between early melanoma and atypical nevi: the iDScore. J Eur Acad Dermatol Venereol 2018; 32: 2162-2170.
Rubegni P, Nami N, Cevenini G et al. Geriatric teledermatology: store-and-forward vs. face-to-face examination. J Eur Acad Dermatol Venereol 2011; 25: 1334-1339.
Argenziano G, Soyer HP, Chimenti S et al. Dermoscopy of pigmented skin lesions: results of a consensus meeting via the internet. J Am Acad Dermatol 2003; 48: 679-693.
Dolianitis C, Kelly J, Wolfe R, Simpson P. Comparative performance of 4 dermoscopic algorithms by nonexperts for the diagnosis of melanocytic lesions. Arch Dermatol 2005; 141: 1008-1014.
Unlu E, Akay BN, Erdem C. Comparison of dermatoscopic diagnostic algorithms based on calculation: the ABCD rule of dermatoscopy, the seven-point checklist, the three-point checklist and the CASH algorithm in dermatoscopic evaluation of melanocytic lesions. J Dermatol 2014; 41: 598-603.
Carli P, Quercioli E, Sestini S et al. Pattern analysis, not simplified algorithms, is the most reliable method for teaching dermoscopy for melanoma diagnosis to residents in dermatology. Br J Dermatol 2003; 148: 981-984.
Lallas A, Longo C, Manfredini M et al. Accuracy of dermoscopic criteria for the diagnosis of melanoma in situ. JAMA Dermatol 2018; 154: 414-419.
Rajpara SM, Botello AP, Townend J, Ormerod AD. Systematic review of dermoscopy and digital dermoscopy/artificial intelligence for the diagnosis of melanoma. Br J Dermatol 2009; 161: 591-604.
Dreiseitl S, Binder M, Hable K, Kittler H. Computer versus human diagnosis of melanoma: evaluation of the feasibility of an automated diagnostic system in a prospective clinical trial. Melanoma Res 2009; 19: 180-184.
Rubegni P, Cevenini G, Barbini P et al. Quantitative characterization and study of the relationship between constitutive-facultative skin color and phototype in Caucasians. Photochem Photobiol 1999; 70: 303-307.
Rubegni P, Cevenini G, Sbano P et al. Evaluation of cutaneous melanoma thickness by digital dermoscopy analysis: a retrospective study. Melanoma Res 2010; 20: 212-217.
Rubegni P, Feci L, Nami N et al. Computer-assisted melanoma diagnosis: a new integrated system. Melanoma Res 2015; 25: 537-542.
Codella N, Nguyen QB, Pankanti S et al. Deep learning ensembles for melanoma recognition in dermoscopy images. IBM J Res Dev 2017; 61: 4/5.
Marchetti MA, Codella NFC, Dusza SW et al. Results of the 2016 International Skin Imaging Collaboration International Symposium on Biomedical Imaging challenge: comparison of the accuracy of computer algorithms to dermatologists for the diagnosis of melanoma from dermoscopic images. J Am Acad Dermatol 2018; 78: 270-277.e1.
Dick V, Sinz C, Mittlböck M, Kittler H, Tschandl P. Accuracy of computer-aided diagnosis of melanoma: a meta-analysis. JAMA Dermatol 2019. https://doi.org/10.1001/jamadermatol.2019.1375
Cevenini G, Furini S, Barbini P et al. Scoring systems in dermatology. IEEE International Symposium on Medical Measurements and Applications (MeMeA) 2016: 1-6.
Rubegni P, Tognetti L, Argenziano G et al. A risk scoring system for the differentiation between melanoma with regression and regressing nevi. J Dermatol Sci 2016; 83: 138-144.
Tognetti L, Cinotti E, Moscarella E et al. Impact of clinical and personal data in the dermoscopic differentiation between early melanoma and atypical nevi. Dermatol Pract Concept 2018; 8: 324-327.

Auteurs

L Tognetti (L)

Dermatology Unit, Department of Medical, Surgical and Neurosciences, University of Siena, Siena, Italy.
Department of Medical Biotechnologies, University of Siena, Siena, Italy.

G Cevenini (G)

Department of Medical Biotechnologies, University of Siena, Siena, Italy.

E Moscarella (E)

Dermatology Unit, University of Campania Luigi Vanvitelli, Naples, Italy.

E Cinotti (E)

Dermatology Unit, Department of Medical, Surgical and Neurosciences, University of Siena, Siena, Italy.

F Farnetani (F)

Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy.

A Lallas (A)

First Department of Dermatology, Aristotele University, Thessaloniki, Greece.

D Tiodorovic (D)

Dermatology Clinic, Medical Faculty, Nis University, Nis, Serbia.

C Carrera (C)

Dermatology Clinic, Medical Faculty, Nis University, Nis, Serbia.

S Puig (S)

Dermatology Clinic, Medical Faculty, Nis University, Nis, Serbia.
Melanoma Unit, Department of Dermatology, University of Barcelona, Barcelona, Spain.

J L Perrot (JL)

Dermatology Unit, University Hospital of St-Etienne, Saint Etienne, France.

C Longo (C)

Department of Dermatology, University of Modena and Reggio Emilia, Modena, Italy.
Centro Oncologico ad Alta Tecnologia Diagnostica, Azienda Unità Sanitaria Locale - IRCCS di Reggio Emilia, Reggio Emilia, Italy.

G Argenziano (G)

Dermatology Unit, University of Campania Luigi Vanvitelli, Naples, Italy.

G Pellacani (G)

First Department of Dermatology, Aristotele University, Thessaloniki, Greece.

E Smargiassi (E)

Department of Medical Biotechnologies, University of Siena, Siena, Italy.

G Cataldo (G)

Department of Medical Biotechnologies, University of Siena, Siena, Italy.

A Cartocci (A)

Department of Medical Biotechnologies, University of Siena, Siena, Italy.

A Balistreri (A)

Department of Medical Biotechnologies, University of Siena, Siena, Italy.

P Rubegni (P)

Dermatology Unit, Department of Medical, Surgical and Neurosciences, University of Siena, Siena, Italy.

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