title: Use of morphology to characterize and manage common adnexal masses.
abstract: The use of grey-scale ultrasound morphology to characterize a pelvic mass may also be called 'pattern recognition'. The grey-scale ultrasound image provides us with the same information as that obtained by the surgeon or pathologist when he or she cuts a surgical specimen to see what it looks like inside. Many pelvic masses have such a typical macroscopic appearance that a fairly confident diagnosis can be made on the basis of their macroscopic appearance alone, i.e. on the basis of their grey-scale ultrasound image. This is true of most dermoid cysts, endometriomas, corpus luteum cysts, hydrosalpinges and peritoneal pseudocysts, and of many paraovarian cysts and benign solid ovarian tumours, for example, fibromas, fibrothecomas, thecofibromas, thecomas and Brenner tumours. A mass with irregularities should always evoke suspicion of malignancy. A mass that is completely smooth is almost certainly benign. Papillary projections--considered a strong sign of malignancy--are more common in borderline tumours than in invasive cancers but may also be seen in benign tumours, for example, in adenofibromas. They explain many false-positive ultrasound diagnoses of malignancy. Pattern recognition is superior to all other ultrasound methods (e.g. simple classification systems, scoring systems, mathematical models for calculating the risk of malignancy) for discrimination between benign and malignant extrauterine pelvic masses. Today's often too liberal use of transvaginal ultrasound gives clinicians problems. Many adnexal masses that probably would have remained undetected before the ultrasound era are now found incidentally at transvaginal ultrasound examination in women without symptoms of an adnexal tumour. The natural history of incidentally detected pelvic masses with benign ultrasound morphology is not known. Therefore, the optimal management of such tumours is also unknown.
authors.affiliation: Department of Obstetrics and Gynaecology, University Hospital, Malmö, SE-205 02 Malmö, Sweden. lil.valentin@obst.mas.lu.se
authors.forename: Lil
authors.initials: L
authors.lastname: Valentin
mesh_terms: D000291:Adnexal Diseases / Q000000981:diagnostic imaging* / Q000473:pathology; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods; D010051:Ovarian Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D010363:Pattern Recognition, Automated; D014463:Ultrasonography