Cirrhotic liver: What's that nodule? The LI‐RADS approach
Bibliographic record
Abstract
The Liver Imaging Reporting and Data System (LI-RADS) is an American College of Radiology (ACR)-endorsed diagnostic system of standardized terminology, interpretation, and reporting for imaging examinations of the liver in patients at high risk for hepatocellular carcinoma (HCC). LI-RADS assigns a category to observations in the liver indicating the likelihood of benignity or HCC. LI-RADS categories include LR-1: Definitely Benign, LR-2: Probably Benign, LR-3: Intermediate Probability for HCC, LR-4: Probably HCC, LR-5: Definite HCC, LR-5V: Definite HCC with Tumor in Vein, LR-Treated: Treated HCC, LR-M Probable Malignancy, not specific for HCC. This article reviews the types of nodules seen in the cirrhotic liver, examines core LI-RADS concepts and definitions, and utilizes the LI-RADS v2014 algorithm to categorize representative observations depicted at magnetic resonance imaging in a case-based approach.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".