title: Pattern recognition of pelvic masses by gray-scale ultrasound imaging: the contribution of Doppler ultrasound.
abstract: OBJECTIVE
  To determine the extent to which Doppler ultrasound examination contributes to a correct specific diagnosis of a pelvic mass when the preliminary diagnosis is based on subjective evaluation of the gray-scale ultrasound image (pattern recognition).
  
  
  METHODS
  In 173 consecutive cases, women scheduled for surgery because of a pelvic mass judged clinically to be of adnexal origin underwent preoperative gray-scale and color Doppler ultrasound examination. On the basis of subjective evaluation of the gray-scale ultrasound image, the ultrasound examiner classified each tumor as probably benign or malignant. If possible, a specific diagnosis was made, e.g. 'endometriosis' or 'dermoid cyst'. The confidence with which the diagnosis was made was rated subjectively on a visual analog scale. The diagnosis based on gray-scale imaging was re-evaluated after color Doppler examination, the diagnostic confidence after Doppler examination also being rated on a visual analog scale. 'Malignancy' was not considered a specific diagnosis.
  
  
  RESULTS
  Pattern recognition of the gray-scale ultrasound image resulted in no unequivocal specific diagnosis in 51% (88/173) of cases, a correct specific diagnosis in 42% (72/173) and an incorrect specific diagnosis in 7% (13/173). Doppler examination added to a correct specific diagnosis in only 5% (8/173) of cases, either by changing an incorrect specific diagnosis to a (more) correct one (five tumors), or by increasing the confidence with which a correct specific diagnosis was made (three tumors). Doppler examination was misleading in one tumor.
  
  
  CONCLUSIONS
  By using pattern recognition of the gray-scale ultrasound image, a correct specific diagnosis can be made in almost half of adnexal tumors scheduled for surgery. Subjective assessment of the color content of the tumor scan contributed little to the specific diagnosis of pelvic tumors.
authors.affiliation: Department of Obstetrics and Gynecology, University Hospital, Malmö, Sweden.
authors.forename: L
authors.initials: L
authors.lastname: Valentin
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D003951:Diagnostic Errors; D005260:Female; D006801:Humans; D008875:Middle Aged; D010363:Pattern Recognition, Automated; D010386:Pelvic Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology / Q000601:surgery; D011300:Preoperative Care; D012307:Risk Factors; D012680:Sensitivity and Specificity; D018615:Ultrasonography, Doppler, Color / Q000295:instrumentation / Q000379:methods* / Q000706:statistics & numerical data