
![]() |
|||||||||||||
WJPR Citation
|
| All | Since 2020 | |
| Citation | 8502 | 4519 |
| h-index | 30 | 23 |
| i10-index | 227 | 96 |
CLINICOPATHOLOGICAL EVALUATION OF BENIGN CYSTIC NEOPLASMS OF THE OVARIES IN BASRA CITY FROM 2019-2023
Sarah Ihsan Haider* and Jasim Al-Diab
. Abstract Background: Ovarian cysts are prevalent among women throughout their lives and are categorized into functional, benign, and malignant types. Benign cysts, which are the focus of this study, often require surgical management if symptomatic. Accurate diagnosis is challenging due to their asymptomatic nature, necessitating histopathological examination for definitive diagnosis and management. Aim of Study: To analyze the prevalence, histopathological characteristics and age distribution of benign cystic neoplasms of the ovaries in Basra, Iraq, over a five-year period. Methods: This prospective study included all patients with histopathologically confirmed benign cystic neoplasms of the ovaries, sourced from government and private laboratories in Basra, Iraq, between January 2019 and December 2023. Data were analyzed based on age, year of diagnosis, and histopathological type. Results: A total of 473 cases of benign cystic ovarian neoplasms were documented. The highest incidence was in 2021 (130 cases), with the lowest in 2020 (58 cases). The most common benign cystic neoplasm was the dermoid cyst (52.6%), followed by serous cystadenoma (26.8%) and mucinous cystadenoma (18.4%). Collectively, these three types represented 97.8% of cases. Less common neoplasms included serous cystadenofibroma (1.3%), struma ovarii (0.6%), and seromucinous cystadenoma (0.2%). The mean age of patients was 33 years, with a standard deviation of 13.7 years, ranging from 6 to 80 years. Conclusion: This study provides an overview of the prevalence and histopathological features of benign cystic ovarian neoplasms in Basra, Iraq. The results emphasize the importance of histopathological examination in the accurate diagnosis and management of these neoplasms and align with global findings on their distribution and characteristics. Keywords: . [Full Text Article] [Download Certificate] |
