RADIOLOGICAL PATTERN RECOGNITION OF OVARIAN MASSES | ||||
| ALEXMED ePosters | ||||
| Article 1, Volume 5, Issue 1, January 2023, Page 52-53 | ||||
| Document Type: Preliminary preprint short reports of original research | ||||
| DOI: 10.21608/alexpo.2023.202293.1595 | ||||
 View on SCiNiTO | ||||
| Authors | ||||
Mahmoud ElSayed Meleis1; Mervat Aly ELsersy2; Ahmed Samy El Agwany 1; Abdallah Fankupi Mzee  1
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| 1Department of Obstetrics and Gynecology, Faculty of Medicine, Alexandria University | ||||
| 2Department of Obstetrics and Gynecology, Faculty of Medicine, University of Alexandria. | ||||
| Abstract | ||||
| INTRODUCTION: The majority of ovarian lesions are benign and have spontaneous resolution2.On the other hand, they may be malignant which is more serious and even fatal3. In Egypt ovarian cancer is the 12th cause of cancer deaths amongst all cancer cases. Ovarian cancer incidence rises dramatically in cases like endometriosis, primary infertility, early menarche, nulliparity, late menopause and postmenopause. There are 2 kinds of epithelial ovarian cancer.Type I cancers due to neoplastic transformation of ovarian surface and epithelium and Type II which originates in the epithelium of the fallopian tube. Early-stage ovarian cancer patients have few distinct symptoms, but they frequently have nonspecific symptoms thus screening studies have been carried out with the goal of diagnosing the disease in its early stages Ultrasound assessment is believed to be the best method of diagnosis for adnexal masses The pattern recognition approach to ovarian tumors based on sonographic morphology and Doppler vascularity assessment has been demonstrated to be more accurate than other methods. | ||||
| Keywords | ||||
| PATTERN; RECOGNITION; OVARIAN MASSES | ||||
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