title: Ultrasound experience substantially impacts on diagnostic performance and confidence when adnexal masses are classified using pattern recognition.
abstract: OBJECTIVE
  To determine how accurately and confidently examiners with different levels of ultrasound experience can classify adnexal masses as benign or malignant and suggest a specific histological diagnosis when evaluating ultrasound images using pattern recognition.
  
  
  METHODS
  Ultrasound images of selected adnexal masses were evaluated by 3 expert sonologists, 2 senior and 4 junior trainees. They were instructed to classify the masses using pattern recognition as benign or malignant, to state the level of confidence with which this classification was made and to suggest a specific histological diagnosis. Sensitivity, specificity, accuracy and positive and negative likelihood ratios (LR+ and LR-) with regard to malignancy were calculated. The area under the receiver operating characteristic curve (AUC) of pattern recognition was calculated by using six levels of diagnostic confidence.
  
  
  RESULTS
  166 masses were examined, of which 42% were malignant. Sensitivity with regard to malignancy ranged from 80 to 86% for the experts, was 70 and 84% for the 2 senior trainees and ranged from 70 to 86% for the junior trainees. The specificity of the experts ranged from 79 to 91%, was 77 and 89% for the senior trainees and ranged from 59 to 83% for the junior trainees. The experts were uncertain about their diagnosis in 4-13% of the cases, the senior trainees in 15-20% and the junior trainees in 67-100% of the cases. The AUCs ranged from 0.861 to 0.922 for the experts, were 0.842 and 0.855 for the senior trainees, and ranged from 0.726 to 0.795 for the junior trainees. The experts suggested a correct specific histological diagnosis in 69-77% of the cases. All 6 trainees did so significantly less often (22-42% of the cases).
  
  
  CONCLUSIONS
  Expert sonologists can accurately classify adnexal masses as benign or malignant and can successfully predict the specific histological diagnosis in many cases. Whilst less experienced operators perform reasonably well when predicting the benign or malignant nature of the mass, they do so with a very low level of diagnostic confidence and are unable to state the likely histology of a mass in most cases.
authors.affiliation: Department of Obstetrics and Gynaecology, University Hospitals Leuven, Belgium. caroline.van.holsbeke@skynet.be
authors.forename: Caroline
authors.initials: C
authors.lastname: Van Holsbeke
authors.forename: Anneleen
authors.initials: A
authors.lastname: Daemen
authors.forename: Joseph
authors.initials: J
authors.lastname: Yazbek
authors.forename: Tom K
authors.initials: TK
authors.lastname: Holland
authors.forename: Tom
authors.initials: T
authors.lastname: Bourne
authors.forename: Tinne
authors.initials: T
authors.lastname: Mesens
authors.forename: Lore
authors.initials: L
authors.lastname: Lannoo
authors.forename: Anne-Sophie
authors.initials: AS
authors.lastname: Boes
authors.forename: Annelies
authors.initials: A
authors.lastname: Joos
authors.forename: Arne
authors.initials: A
authors.lastname: Van De Vijver
authors.forename: Nele
authors.initials: N
authors.lastname: Roggen
authors.forename: Bart
authors.initials: B
authors.lastname: de Moor
authors.forename: Eric
authors.initials: E
authors.lastname: de Jonge
authors.forename: Antonia C
authors.initials: AC
authors.lastname: Testa
authors.forename: Lil
authors.initials: L
authors.lastname: Valentin
authors.forename: Davor
authors.initials: D
authors.lastname: Jurkovic
authors.forename: Dirk
authors.initials: D
authors.lastname: Timmerman
mesh_terms: D002288:Adenocarcinoma, Mucinous / Q000000981:diagnostic imaging / Q000453:epidemiology / Q000473:pathology; D000291:Adnexal Diseases / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology; D016208:Databases, Factual; D005260:Female; D006176:Gynecology / Q000193:education / Q000592:standards*; D006801:Humans; D015233:Models, Statistical; D009369:Neoplasms / Q000000981:diagnostic imaging / Q000453:epidemiology / Q000473:pathology; D010051:Ovarian Neoplasms / Q000000981:diagnostic imaging* / Q000453:epidemiology / Q000473:pathology; D010363:Pattern Recognition, Automated / Q000592:standards*; D012372:ROC Curve; D015203:Reproducibility of Results; D012307:Risk Factors; D012680:Sensitivity and Specificity; D018615:Ultrasonography, Doppler, Color / Q000592:standards*