Neoplasms

Urinary Tract, Sexual Organs, and Pregnancy Conditions

Gland and Hormone Related Diseases

All Conditions

Symptoms and General Pathology

Rare Diseases

Ovarian Neoplasms

Carcinoma, Ovarian Epithelial

Cysts

Ovarian Cysts

Ovarian Cancer

Ovarian Epithelial Cancer

The ADNEX model includes nine parameters; Age, CA-125 level, Oncology center (yes/no), and 6 ultrasound features which are maximal diameter of the lesion, maximal diameter of the largest solid part, more than 10 locules (yes/no), number of papillary projections (0/1/2/3/more than 3), acoustic shadow, and ascites

Assesment of Different NEoplasias in the adenexa model

The RMI was measured as follows; Menopausal status (score is 3 as all patients were postmenopausal X Ultrasound score is based on assessment of 5 features and with the presence of one feature, the score is 1 while if more than one feature is present, the score is 3; the five ultrasound features are the presence of solid components, multilocularity, bilaterality, ascites, and metastases X CA - 125 level

Risk of malignancy index

Histopathologic examination of all excised specimens was done as this is the gold standard test for detecting ovarian malignancy

Histopathologic examination

Amr H El-Shalakany, M.D.

Kareem M Labib, M.D.

Hassan Morsi, PhD

Mortada Elsayed, M.D.

Ovarian cancer is the second most common gynecologic malignancy. In 2008, it was the seventh leading cause of cancer deaths in women worldwide. Estimating the risk of malignancy is essential in the management of adnexal masses and several mathematical models and scoring systems have been developed to be used for discrimination between benign and malignant adnexal masses. Knowledge of the specific type of adnexal pathology before surgery is likely to improve patient triage with high accuracy, and it also makes it possible to optimize treatment. The correct identification of stage I cancer is particularly important

Ovarian cancer (OC) is the third most common gynecological malignancy worldwide and carries the highest mortality. OC has an incidence of 11.7 - 12.1 per 100,000 in the USA and Europe, with slightly lower rates of disease in Asia and the Middle East. Most patients (60%) are diagnosed with advanced disease which is associated with significant mortality. The most important factor for survival is the stage at diagnosis and nowadays there isn't a proven effective screening strategy. It is necessary to identify the best tool to detect early-stage disease. To reduce the diagnostic dilemma between benign and malignant ovarian masses, a formula-based scoring system known as the risk of malignancy index (RMI) was introduced in 1990, which was termed RMI 1. RMI is a combined parameter that is simple, specific, and highly sensitive for the evaluation of adnexal masses. It is a product of ultrasound findings (U), the menopausal status (M), and serum CA-125 levels (RMI = U X M XCA-125). The original RMI (RMI-1) was modified in 1996 as (RMI 2) and again in 1999 known as (RMI 3), and the last modification was in 2009 by adding the tumor size (S) to the equation and calling it RMI 4. A systematic review of diagnostic studies concluded that the RMI I was the most effective for women with suspected ovarian malignancy.

Malignant tumors benefit from management in specialized oncology centers, but borderline malignancies, stage I primary invasive tumors, and advanced primary invasive tumors might require different surgical approaches. To optimize patient triage without operating on all masses, diagnostic models can be used to estimate the likelihood of malignancy and hence to plan treatment for patients. The International Ovarian Tumor Analysis Group (IOTA) has developed a multi-tumor prediction model, Assessment of Different NEoplasias in the adneXa (ADNEX) model, which is used to describe in detail the characteristics of adnexal masses. ADNEX model can not only distinguish the probability of benign and malignant AMs, but also distinguish between borderline ovarian tumors, stage I ovarian cancer, stage II-IV ovarian cancer, and secondary metastatic ovarian cancers, which includes three clinical features and six ultrasound features

Screening for Ovarian Malignancy

Assessment of Different Neoplasias in the Adenxa Model Versus Risk of Malignancy Index as a Tool for Predicting Ovarian Malignancy in Postmenopausal Ovarian Cysts

The diagnostic performance of the ADNEX model for differentiating between benign and malignant ovarian tumors was assessed at a threshold of 10%. The diagnostic performance was expressed as Area Under Receiver Operating Characteristic Curve (AUC)

Spots Global Cancer Trial Database for early detection of ovarian cancer