O-RADS US Risk Stratification and Management System: Case-based Learning Approach for Daily Practice
Abstract
The full digital presentation is available online.
TEACHING POINTS
■ O-RADS US can be used to promote the use of consistent descriptors, help provide a risk of malignancy, and propose management strategies.
■ Using O-RADS US can improve communication among imagers, health care providers, and patients.
■ MRI has higher specificity than that of US in some scenarios owing to better tissue characterization with the use of contrast material and the larger field of view. Occasionally, imaging features between MRI and US may contradict each other, resulting in different O-RADS scores; it is always prudent to use the highest score.
US is the initial imaging modality for most ovarian and adnexal lesions and is performed to establish an accurate risk of malignancy assessment to direct appropriate individualized patient management. There is recognized heterogeneity in US reporting that can lead to miscommunication between imagers and clinicians, unnecessary surgical procedures, “overimaging” in women with low-risk lesions, and poor survival outcomes in women with high-risk lesions that are not promptly recognized and who are not expediently referred to an oncology center. The use of vague terms such as complex cyst is a paramount example of how ambiguous terminology can hinder accurate risk assessment, as this description can apply to benign hemorrhagic cysts, which will spontaneously resolve (Fig 1), and to ovarian carcinomas (Fig 2), which require rapid referral to a gynecologic oncologist for best survival outcomes.
Figure 1. Hemorrhagic cyst. US image shows the the typical features of a retractile clot with concave margins and a reticular pattern of fine intersecting lines.
Figure 2. High-grade serous cystadenoma. US image shows a multilocular cyst with solid components demonstrating very strong flow (O-RADS color score 4, O-RADS risk category 5).
Several standardized imaging assessment systems have been proposed to address the lack of standardization in US reporting of ovarian-adnexal lesions, with varying degrees of adoption. The most recent system is the Ovarian-Adnexal Reporting and Data System (O-RADS) US, which was developed by an international group of multidisciplinary specialists and multisociety representatives to address the lack of standardized terminology, risk assessment methods, and management pathways for patients with ovarian lesions. O-RADS US combines a descriptor-based lexicon with evidence-based assessment data to assign an O-RADS risk of malignancy category of 1–5 for each lesion.
The risk of malignancy values are as follows: 0% for O-RADS 1, less than 1% for O-RADS 2, 1% to less than 10% for O-RADS 3, 10% to less than 50% for O-RADS 4, and 50% or more for O-RADS 5. Each O-RADS risk of malignancy category has a paired management recommendation to help facilitate clear communication between the reporting physician and the managing clinician. There are several published validation studies of the O-RADS US system that show a high ability to predict benign versus malignant ovarian-adnexal lesions and high interreader reliability for the O-RADS risk category.
Despite success shown in early validation studies, some reporting physicians may not feel comfortable or confident using the system in practice given that it is relatively new. To effectively determine the O-RADS risk category of a lesion, users need to be familiar with the basic lexicon and be able to follow an algorithmic approach to simplify the process. This online presentation details how to use the O-RADS US by reviewing the governing principles and applying the lexicon descriptors to cases with lesions ranging the spectrum of O-RADS categories 1–5. We emphasize key descriptors that have the potential to change the O-RADS risk category, identify technical pitfalls, and provide technical pearls. Guidance on what to include in the imaging report is also provided.
Disclosures of conflicts of interest.—L.S. Royalties from Elsevier for book chapters; honoraria for lectures from World Class CME. R.F.A. Speaker payment from Philips Healthcare. P.J. Honorarium from World Class CME Society of Radiologists in Ultrasound UC Davis; participation on a data safety monitoring board or advisory board for and payment for expert testimony from Donahue, Durham and Noonan, P.C. C.L. Collaborative research agreement with IBM Watson Health. All other authors have disclosed no relevant relationships.Recipient of a Magna Cum Laude award for an education exhibit at the 2021 RSNA Annual Meeting.
Suggested Readings
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Article History
Received: Apr 8 2022Revision requested: May 16 2022
Revision received: June 3 2022
Accepted: June 8 2022
Published online: Feb 23 2023
