OBJECTIVE: To estimate the diagnostic accuracy of magnetic resonance in ovarian tumors. STUDY DESIGN: A quantitative systematic review was performed. Studies that compared magnetic resonance and paraffin sections within subjects for diagnosis of ovarian tumors were included. RESULTS: Fifteen primary studies were analyzed, which included 1267 ovarian masses. For borderline or malignant ovarian cancer vs benign ovarian lesions, the pooled likelihood ratio for the occurrence of a positive magnetic resonance result was 6.6 (95% confidence interval, 4.7-9.2) and the posttest probability for borderline or malignant diagnosis was 77% (95% confidence interval, 70-82). Because specificity and likelihood ratio positive were heterogeneous, a random effect model was used and a summary receiver operating characteristic curve was generated. For borderline or malignant ovarian cancer vs benign ovarian lesions, the area under curve was 0.9526. CONCLUSION: Magnetic resonance seems to be a useful preoperative test for predicting the diagnosis of pelvic masses.
OBJECTIVE: To estimate the diagnostic accuracy of magnetic resonance in ovarian tumors. STUDY DESIGN: A quantitative systematic review was performed. Studies that compared magnetic resonance and paraffin sections within subjects for diagnosis of ovarian tumors were included. RESULTS: Fifteen primary studies were analyzed, which included 1267 ovarian masses. For borderline or malignant ovarian cancer vs benign ovarian lesions, the pooled likelihood ratio for the occurrence of a positive magnetic resonance result was 6.6 (95% confidence interval, 4.7-9.2) and the posttest probability for borderline or malignant diagnosis was 77% (95% confidence interval, 70-82). Because specificity and likelihood ratio positive were heterogeneous, a random effect model was used and a summary receiver operating characteristic curve was generated. For borderline or malignant ovarian cancer vs benign ovarian lesions, the area under curve was 0.9526. CONCLUSION: Magnetic resonance seems to be a useful preoperative test for predicting the diagnosis of pelvic masses.
Authors: Patrick N Pereira; Luis O Sarian; Adriana Yoshida; Karla G Araújo; Ricardo H O Barros; Ana C Baião; Daniella B Parente; Sophie Derchain Journal: Diagn Interv Radiol Date: 2018 Mar-Apr Impact factor: 2.630