Thesis (Ph.D.) - Cairo University - Faculty of Medicine - Department of Gynecology and Obstetrics

Background: Screening for and diagnosing ovarian neoplasms are a challenging process as most women with ovarian cancer are asymptomatic for long periods of time and when symptoms develop, they are often vague and nonspecific.Aim of work: to compare between the efficacy of IOTA simple rules and pattern recognition method in the differentiation between benign and malignant ovarian masses.Patient and methods: The study included 72 patients with ovarian masses candidate for surgical exploration and excision of the mass. All patients were examined by level II ultrasound (to apply IOTA simple rules) followed by level III ultrasound (to apply pattern recognition method). Following surgical exploration, all specimens were examined histopathologically and the results was compared with corresponding ultrasound reports.Results:IOTA simple rules were applicable in 53/72 cases (73.6%). Of them, the simple rules correctly classify 8/9 cases as malignant and 40/44 as being benign with a sensitivity and specificity of 88.89% and 90.91 %, respectively. Pattern recognition correctly classifies 15/17 cases as malignant and 51/55 as benign with a sensitivity and specificity of 88.24% and 92.73 %, respectively

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