Resolution of indeterminate MRI with CEUS in patients at high risk for hepatocellular carcinoma
Bibliographic record
Abstract
PURPOSE: To show the contribution of CEUS to characterization of indeterminate MRI observations in high-risk patients for hepatocellular carcinoma (HCC). METHODS: From July to December 2015, 42 consecutive patients referred to CEUS with indeterminate MRI scans comprise our study cohort. There are 50 indeterminate nodule-like observations and 10 arterial phase hyperenhancing foci, suggesting pseudolesions/arterio-portal shunts. MRI and CEUS lesions are classified according to their enhancement features in all phases and Liver Imaging and Reporting Data System (LI-RADS) in a blind read format. Clinical pathologic correlation and 24 months follow-up are performed. RESULTS: A majority, 37/50 (74%), of indeterminate nodule-like observations have arterial phase enhancement without washout on MRI. CEUS further characterizes enhancement and shows washout in 14/37 (38%). In total, CEUS diagnoses 16 malignant lesions in 14 patients including 14 HCC and 2 ICC. 12/16 (75%) malignant lesions are confirmed by biopsy or follow-up. Ultrasound identification of a nodule differentiates real nodules from pseudolesions. Of the ten suspected arterial-portal shunts on MRI, two show a real nodule on ultrasound, confirmed as an HCC and a regenerative nodule. 15/42 (36%) patients have LI-RADS escalated from LR-3 or 4 on MRI to LR-4 or 5 on CEUS. Overall, the sensitivity of CEUS is (13/16) 81.3% and specificity is (37/37) 100% for malignant diagnosis. CONCLUSION: Grayscale ultrasound detects true nodules. Dynamic CEUS detects and characterizes washout, correctly predicting HCC. CEUS is complimentary to MRI and can serve as a problem-solving tool when MRI is indeterminate.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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".