title: The diagnostic performance of expert dermoscopists vs a computer-vision system on small-diameter melanomas.
abstract: OBJECTIVE
  To evaluate the performance of dermoscopists in diagnosing small pigmented skin lesions (diameter </= 6 mm) compared with an automatic multispectral computer-vision system.
  
  
  METHODS
  Blinded comparison study.
  
  
  METHODS
  Dermatologic hospital-based clinics and private practice offices. Patients From a computerized skin imaging database of 990 small (</= 6-mm) pigmented skin lesions, all 49 melanomas from 49 patients were included in this study. Fifty randomly selected nonmelanomas from 46 patients served as a control.
  
  
  METHODS
  Ten dermoscopists independently examined dermoscopic images of 99 pigmented skin lesions and decided whether they identified the lesions as melanoma and whether they would recommend biopsy to rule out melanoma. Diagnostic and biopsy sensitivity and specificity were computed and then compared with the results of the computer-vision system.
  
  
  RESULTS
  Dermoscopists were able to correctly identify small melanomas with an average diagnostic sensitivity of 39% and a specificity of 82% and recommended small melanomas for biopsy with a sensitivity of 71% and specificity of 49%, with only fair interobserver agreement (kappa = 0.31 for diagnosis and 0.34 for biopsy). In comparison, in recommending biopsy to rule out melanoma, the computer-vision system achieved 98% sensitivity and 44% specificity.
  
  
  CONCLUSIONS
  Differentiation of small melanomas from small benign pigmented lesions challenges even expert physicians. Computer-vision systems can facilitate early detection of small melanomas and may limit the number of biopsies to rule out melanoma performed on benign lesions.
authors.affiliation: Department of Dermatology, New York University School of Medicine, New York, USA.
authors.forename: Robert J
authors.initials: RJ
authors.lastname: Friedman
authors.forename: Dina
authors.initials: D
authors.lastname: Gutkowicz-Krusin
authors.forename: Michele J
authors.initials: MJ
authors.lastname: Farber
authors.forename: Melanie
authors.initials: M
authors.lastname: Warycha
authors.forename: Lori
authors.initials: L
authors.lastname: Schneider-Kels
authors.forename: Nicole
authors.initials: N
authors.lastname: Papastathis
authors.forename: Martin C
authors.initials: MC
authors.lastname: Mihm
authors.forename: Paul
authors.initials: P
authors.lastname: Googe
authors.forename: Roy
authors.initials: R
authors.lastname: King
authors.forename: Victor G
authors.initials: VG
authors.lastname: Prieto
authors.forename: Alfred W
authors.initials: AW
authors.lastname: Kopf
authors.forename: David
authors.initials: D
authors.lastname: Polsky
authors.forename: Harold
authors.initials: H
authors.lastname: Rabinovitz
authors.forename: Margaret
authors.initials: M
authors.lastname: Oliviero
authors.forename: Armand
authors.initials: A
authors.lastname: Cognetta
authors.forename: Darrell S
authors.initials: DS
authors.lastname: Rigel
authors.forename: Ashfaq
authors.initials: A
authors.lastname: Marghoob
authors.forename: Jason
authors.initials: J
authors.lastname: Rivers
authors.forename: Robert
authors.initials: R
authors.lastname: Johr
authors.forename: Jane M
authors.initials: JM
authors.lastname: Grant-Kels
authors.forename: Hensin
authors.initials: H
authors.lastname: Tsao
mesh_terms: D001185:Artificial Intelligence; D001706:Biopsy; D002983:Clinical Competence; D046169:Dermoscopy / Q000295:instrumentation*; D003936:Diagnosis, Computer-Assisted / Q000295:instrumentation*; D003937:Diagnosis, Differential; D004416:Dysplastic Nevus Syndrome / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000295:instrumentation*; D008545:Melanoma / Q000175:diagnosis* / Q000473:pathology; D009361:Neoplasm Invasiveness / Q000473:pathology; D012680:Sensitivity and Specificity; D012867:Skin / Q000473:pathology; D012878:Skin Neoplasms / Q000175:diagnosis* / Q000473:pathology