Diagnostic Per-Patient Accuracy of an Abbreviated Hepatobiliary Phase Gadoxetic Acid–Enhanced MRI for Hepatocellular Carcinoma Surveillance
Bibliographic record
Abstract
OBJECTIVE. The purpose of this study is to evaluate the per-patient diagnostic performance of an abbreviated gadoxetic acid-enhanced MRI protocol for hepatocellular carcinoma (HCC) surveillance. MATERIALS AND METHODS. A retrospective review identified 298 consecutive patients at risk for HCC enrolled in a gadoxetic acid-enhanced MRI-based HCC surveillance program. For each patient, the first gadoxetic acid-enhanced MRI was analyzed. To simulate an abbreviated protocol, two readers independently read two image sets per patient: set 1 consisted of T1-weighted 20-minute hepatobiliary phase and T2-weighted single-shot fast spin-echo (SSFSE) images; set 2 included diffusion-weighted imaging (DWI) and images from set 1. Image sets were scored as positive or negative according to the presence of at least one nodule 10 mm or larger that met the predetermined criteria. Agreement was assessed using Cohen kappa statistics. A composite reference standard was used to determine the diagnostic performance of each image set for each reader. RESULTS. Interreader agreement was substantial for both image sets (κ = 0.72 for both) and intrareader agreement was excellent (κ = 0.97-0.99). Reader performance for image set 1 was sensitivity of 85.7% for reader A and 79.6% for reader B, specificity of 91.2% for reader A and 95.2% for reader B, and negative predictive value of 97.0% for reader A and 96.0% for reader B. Reader performance for image set 2 was nearly identical, with only one of 298 examinations scored differently on image set 2 compared with set 1. CONCLUSION. An abbreviated MRI protocol consisting of T2-weighted SSFSE and gadoxetic acid-enhanced hepatobiliary phase has high negative predictive value and may be an acceptable method for HCC surveillance. The inclusion of a DWI sequence did not significantly alter the diagnostic performance of the abbreviated protocol.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.017 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".