title: Adnexal masses: accuracy of detection and differentiation with multidetector computed tomography.
abstract: OBJECTIVE
  The aim of our study was to evaluate the accuracy of multidetector computed tomography (MDCT) on a 16-row CT scanner in the detection and differentiation of adnexal masses.
  
  
  METHODS
  We prospectively examined 102 consecutive women with clinically or sonographically detected adnexal masses. Preoperative CT examination was performed, including scanning of the abdomen during the portal phase, using a detector collimation of 16 x 0.75 mm and a pitch of 1.2. Multiplanar reformatted images were evaluated for the presence of an adnexal mass and differentiation between benign and malignant ones, using the surgical and pathologic results as standard of reference. CT findings used to diagnose malignancy were: diameter greater than 4 cm, presence of masses bilaterally, cystic-solid mass, necrosis in a solid lesion, cystic lesion with thick, irregular walls or septa and/or with papillary projections. Presence of ascites, peritoneal metastases and lymphadenopathy was used to confirm malignancy. Multiple logistic regression analysis of the MDCT findings was performed to determine those more predictive of malignancy.
  
  
  RESULTS
  Histopathologic examination demonstrated 143 adnexal mass lesions, 96 (67%) of which were benign and 47 (33%) malignant. Multidetector CT detected 129 (90%) of the 143 adnexal masses, with an overall accuracy for the diagnosis of malignancy of 89.15%. The MDCT findings that found more predictive of malignancy were the presence of papillary projections in a cystic lesion, necrosis in solid mass and peritoneal metastases.
  
  
  CONCLUSIONS
  Multidetector computed tomography on a 16-row CT scanner proved accurate in the detection and characterization of adnexal masses.
authors.affiliation: Department of Clinical Radiology, University Hospital of Ioannina, Leoforos S. Niarchou, 45500, Ioannina, Greece. a_tsili@yahoo.gr
authors.forename: A C
authors.initials: AC
authors.lastname: Tsili
authors.forename: C
authors.initials: C
authors.lastname: Tsampoulas
authors.forename: A
authors.initials: A
authors.lastname: Charisiadi
authors.forename: John
authors.initials: J
authors.lastname: Kalef-Ezra
authors.forename: V
authors.initials: V
authors.lastname: Dousias
authors.forename: E
authors.initials: E
authors.lastname: Paraskevaidis
authors.forename: S C
authors.initials: SC
authors.lastname: Efremidis
mesh_terms: D000291:Adnexal Diseases / Q000000981:diagnostic imaging* / Q000473:pathology*; D000368:Aged; D003536:Cystadenocarcinoma / Q000000981:diagnostic imaging; D003937:Diagnosis, Differential; D005260:Female; D006801:Humans; D007091:Image Processing, Computer-Assisted; D007889:Leiomyoma / Q000000981:diagnostic imaging / Q000473:pathology; D008279:Magnetic Resonance Imaging; D010051:Ovarian Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology; D011446:Prospective Studies; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed; D014463:Ultrasonography; D014594:Uterine Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology