Assessment of Diagnostic Accuracy of IOTA - ADNEX Model in Detecting the Risk of Malignancy in Ovarian Carcinomas

Srinidhi, Cherukuri and Jajoo, Shubhada S. (2021) Assessment of Diagnostic Accuracy of IOTA - ADNEX Model in Detecting the Risk of Malignancy in Ovarian Carcinomas. Journal of Pharmaceutical Research International, 33 (64A). pp. 373-380. ISSN 2456-9119

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Abstract

Background: Ovarian cancer has become a major public health issue which stood in 10th rank of mortality within India. 2.4 % is the annual new cases of ovarian cancer in overall India. In 2008 it was the seventh leading cause of cancer deaths in women worldwide. 70% of cases are diagnosed with poor prognosis at an advanced stage. Ovarian malignancy death rate is of 70% within 2 yrs and 90% within five years. It’s a tough task for a gynecologist to identify ovarian cancer correctly .Ovarian malignancy is initially detected as adnexal mass. Exploratory laparotomy or laparoscopy with histopathology is a specific diagnostic procedure for adnexal mass. This study aims to study and analyse the diagnostic accuracy of IOTA - ADNEX model in detecting the risk of malignancy in ovarian carcinomas.

Objectives: To make pre-operative diagnosis of adnexal masses and conserve the in menstruating women with less aggressive management.

Methodology: This prospective study will be conducted in Obstetrics & Gynaecology department of AVBRH, Wardha from September 2020 to July 2022. This will be conducted on 50 females presenting with adnexal mass. Patients will undergo transvaginal ultrasonography with HERA W10 ultra sound system with an endovaginal EA2-11B probe. The ultra sound evaluation we will include IOTA –ADNEX Model. The mass with the most complex structure will be chosen for analysis for ultrasound imaging to know the chances of being malignant.

Expected Results: Positive correlation between the IOTA –ADNEX model and histopathological report.

Conclusion: IOTA-ADNEX model to be incorporated for ovarian malignancy diagnostic protocol.

Item Type: Article
Subjects: STM Academic > Medical Science
Depositing User: Unnamed user with email support@stmacademic.com
Date Deposited: 21 Feb 2023 10:20
Last Modified: 22 Feb 2024 04:03
URI: http://article.researchpromo.com/id/eprint/188

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