An Algorithm Based Approach To Ovarian Neoplasms

Abstract

Introduction: Cancer of the ovaries is the 2 nd most common gynaecological malignancy and has the highest mortality rate among all gynaecological malignancies with an overall 5 year survival rate of 46%. A large number of the lesions are incidentally detected, for which imaging plays a vital role in treatment planning by characterizing these masses. Identifying benign lesions accurately may obviate unnecessary surgery, where as indeterminate or malignant lesions will require surgery with or without radio/chemotherapy. Aim:To inform the readers the imaging patterns of common and rarely encountered ovarian neoplasms and to provide an algorithm based approach to these ovarian lesions, which will not only aid in the management of these conditions but also obviate unnecessary investigations and surgeries. Materials and Methods:This was a prospective study conducted over a period of one year from January 2014 to January 2015 at the Department of Radiology, Father Muller Medical College, Mangalore, India. Data were collected from 82 patients who presented with ovarian cystic lesions on ultrasound and were either followed up by USG or underwent further evaluation by CT. Diagnosis was confirmed by histopathology. Statistical analysis involved percentage frequency.