Comparison of international guidelines for diagnosis of hepatocellular carcinoma and implications for transplant allocation in liver transplantation candidates with gadoxetic acid enhanced liver MRI versus contrast enhanced CT: a prospective study with liver explant histopathological correlation
Bibliographic record
Abstract
OBJECTIVES: To compare the diagnostic performance of international hepatocellular carcinoma (HCC) guidelines with gadoxetic acid-enhanced MRI (EOB-MRI) and contrast-enhanced Computed tomography (CECT) and their impact on liver transplant (LT) allocation in cirrhotic patients with explant histopathology correlation. METHODS: In this prospective single-centre ethics-approved study, 101 cirrhotic patients were consecutively enrolled with informed consent from the pre-LT clinic. They underwent CECT and EOB-MRI alternately at three monthly intervals until LT or removal from LT list. Two abdominal radiologists, blinded to explant histopathology, independently recorded liver lesions visible on CECT and EOB-MRI. Imaging-based HCC scores were assigned to non-treated liver lesions utilizing Liver Imaging Reporting and Data System (LI-RADS), European Association for the Study of the Liver (EASL), Asian-Pacific Association for the Study of the Liver (APASL) and Korean Liver Cancer Association-National Cancer Center (KLCA) guidelines. Liver explant histopathology was the reference standard. Simulated LT eligibility was assessed as per Milan criteria (MC) in reference to explant histopathology. RESULTS: One hundred and three non-treated HCC and 12 non-HCC malignancy were identified at explant histopathology in 34 patients (29 men, 5 women, age 55-73 years). Higher HCC sensitivities of statistical significance were observed with EOB-MRI for LI-RADS 4 + 5, APASL and KLCA compared to LI-RADS 5 and EASL with greatest sensitivity obtained for LIRADS 4 + 5 lesions. HCC sensitivities by all guidelines with both EOB-MRI and CECT were significantly lower if all histopathology-detected HCCs were included in the analysis, compared to imaging-visible lesions only. A significantly greater variation in HCC sensitivity was noted across the guidelines with EOB-MRI compared to CECT. No significant differences in simulated LT eligibility based on MC were observed across the HCC scoring guidelines with EOB-MRI or CECT. CONCLUSION: HCC sensitivities are variable depending on scoring guideline, lesion size and imaging modality utilised. Prior studies that included only lesions visible on pre-operative imaging overestimate the diagnostic performance of HCC scoring guidelines. Per-lesion differences in HCC diagnosis across these guidelines did not impact patient-level LT eligibility based on MC.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".