Detecting the difference between a benign or malignant ovarian tumor can make all the difference for a patient. Ultrasound is the first-line tool to evaluate an ovarian lesion. From early detection to planning surgery, ultrasound provides the details needed to make informed treatment decisions. The International Ovarian Tumour Analysis (IOTA) group provides standardized terminology and guidance for differentiating and describing ovarian masses.
Clinicians can use IOTA's risk assessment models to guide transvaginal ultrasound exams for consistent, reproducible scans.
Risk Assessment Models
The IOTA group was formed in 1999 and has since applied its risk assessment models to thousands of patients in dozens of centers around the world. These models are widely used in clinical practice and recommended by leading gynecologic societies.
The group has three risk models for classifying tumors and adnexal masses to guide appropriate treatment. The risk assessment apps are no longer available for phone or web, but they're included in many ultrasound systems, such as GE HealthCare Voluson™ models.
Simple Rules
The most widely used model, the Simple Rules, differentiates between benign and malignant adnexal masses by classifying findings based on solidity, contents, blood flow, and other features. The Simple Rules describe five features of benign tumors (B-features) and five features of malignant tumors (M-features). Clinicians can classify the tumors as benign, malignant, or inconclusive based on which features are present on color Doppler transvaginal ultrasound.
This model aids in forming a pre-operative diagnosis of ovarian cancer and applies to about 80 percent of adnexal masses, according to a consensus statement published in the International Journal of Gynecological Cancer. In addition, a study in Case Reports in Obstetrics and Gynecology found that transvaginal ultrasound has a 93 percent sensitivity and 81 percent specificity characterizing adnexal masses before surgery when using the Simple Rules.
LR2 Risk Model
The LR2 Risk Model aims to diagnose ovarian cancer before surgery. The LR2 model is a logistic regression model based on the Simple Rules. IOTA designed this model for patients who have at least one ovarian tumor and who are recommended for surgery. The risk model uses an algorithm to create a percent probability of a tumor being malignant. It uses age along with five ultrasound predictors to develop the score.
ADNEX Risk Model
The ADNEX model uses nine predictors to estimate the percent probability that a tumor is malignant and sub-categorizes the tumor as borderline, stage I cancer, stage II-IV cancer, or secondary metastatic cancer. The consensus statement finds ultrasound-based diagnostic models with the Simple Rules or ADNEX superior to CA 125 level, HE4 level, or ROMA for distinguishing between benign and malignant ovarian tumors.
In addition, the ADNEX model has strong negative predictive value to help clinicians exclude malignancy, and it effectively distinguishes stages II-IV ovarian cancer from other tumor types, according to research in Cureus.
Using Risk Assessments in Practice
These risk models help clinicians provide timely answers for patients while avoiding radiation exposure. The models accompany transvaginal color Doppler ultrasound for evaluation of masses. Color Doppler shows the presence and direction of blood flow and is included as an M-feature in the Simple Rules.
Ultrasound is also cost-effective when compared with MRI. Ultrasound systems guide clinicians through each step of the assessments, and the group provides standardized terminology for common terms for describing ovarian lesions.
The answers gleaned from these exams allow clinicians to calculate a reliable risk of malignancy and tailor surgery to the patient's condition. Some common use cases for the Simple Rules include:
- Performing ovarian cancer screening
- Evaluating pelvic masses during routine OB/GYN exams
- Diagnosing ovarian lesions
- Classifying ovarian tumors
- Assessing complex versus simple ovarian cysts
Using the risk assessment models in the ultrasound system while performing patient exams can aid in early diagnosis and treatment planning. The ultrasound findings, combined with clinical features and biomarkers, add confidence to an ovarian cancer diagnosis.
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