Practical Tips for Reporting Adnexal Lesions Using O-RADS MRI
Bibliographic record
Abstract
The Ovarian-Adnexal Reporting and Data System (O-RADS) MRI risk stratification system provides a standardized lexicon and evidence-based risk score for evaluation of adnexal lesions. The goals of the lexicon and risk score are to improve report quality and communication between radiologists and clinicians, reduce variability in the reporting language, and optimize management of adnexal lesions. The O-RADS MRI risk score is based on the presence or absence of specific imaging features, including the lipid content, enhancing solid tissue, number of loculi, and fluid type. The probability of malignancy ranges from less than 0.5% when there are benign features to approximately 90% when there is solid tissue with a high-risk time-intensity curve. This information can aid in optimizing management of patients with adnexal lesions. The authors present an algorithmic approach to the O-RADS MRI risk stratification system and highlight key teaching points and common pitfalls. © RSNA, 2023 Quiz questions for this article are available in the supplemental material.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".