Negative Predictive Value of Contrast‐Enhanced Ultrasound in Differentiating Avascular Solid‐Appearing From Vascularized Masses: A Retrospective Consecutive Study
Bibliographic record
Abstract
OBJECTIVES: To determine the negative predictive value (NPV) of contrast-enhanced ultrasound (CEUS) to establish the lack of vascularity in a mass. METHODS: This work was an Institutional Review Board-approved, Health Insurance Portability and Accountability Act-compliant retrospective study. Acquisition of consent was waived. We included all CEUS examinations performed for tissue characterization between 2004 and 2014 that reported showing no vascularity in a mass. Contrast-enhanced ultrasound findings were considered true-negative when there was stability on imaging for at least 1 year or no evidence of a solid mass, if biopsied, and false-negative if there was lesion growth on imaging within 12 months or an indication of a solid mass on the pathologic examination, if biopsied. One author reviewed all of the reports and follow-up examinations. We conducted a consensus review of all false-negative findings mixed with an equal number of true-negative findings by 2 reviewers, who were blinded to the final results. RESULTS: The study population consisted of 97 CEUS examinations in 97 patients, including 48 women and 49 men (mean age ± SD, 65 ± 14 years). Examinations were performed for lesion characterization in the liver (n = 23), pancreas (n = 17), kidney (n = 54), 1 gallbladder, 1 adnexa, and 1 peritoneal lesion. The overall false-negative rate on the official prospective review was 2% (2 of 97). Two false-negative findings were correctly identified on the consensus review. The NPV of CEUS was 97.9% (95 of 97; 95% confidence interval, 93%- 99%) on the official review. CONCLUSIONS: Contrast-enhanced ultrasound has a very high NPV to exclude the presence of flow in a mass, and it can be used to exclude the presence of a solid mass.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".