Non-invasive imaging criteria for the diagnosis of hepatocellular carcinoma in non-cirrhotic patients with chronic hepatitis B
Bibliographic record
Abstract
BACKGROUND & AIMS: Criteria defined by the European Association for the Study of the Liver (EASL) and Liver Imaging Reporting and Data System (LI-RADS) enable hepatocellular carcinoma (HCC) diagnosis based on imaging in cirrhosis. Non-cirrhotic patients require biopsy given the lower pre-test probability of HCC. The objective of our study was to assess the performance of EASL and LI-RADS criteria for the diagnosis of HCC in non-cirrhotic patients with chronic HBV infection. METHODS: This was a cross-sectional study performed at a referral center. We included all patients with HBV without cirrhosis with focal liver lesions who underwent contrast-enhanced CT or MRI at our clinic between 2005-2018. Studies were reviewed by 2 radiologists blinded to the diagnosis. RESULTS: We included 280 patients, median age was 56.8 (IQR 48.2-65.45) years and 223 (80%) were male. In 191 (79%) cases the lesion was found as a result of screening. Cirrhosis was excluded based on pathology in 252 (90%) cases. We assessed 338 nodules: 257 (76%) HCC, 40 (12%) non-HCC malignant lesions, and 41 (12%) benign lesions. EASL criteria and LR-5/LR-tumor-in-vein (TIV) categories had a 100% agreement in categorizing lesions as HCC, and 226 nodules (67%) were classified as HCCs. The sensitivity, specificity, positive predictive value, and negative predictive value were 82.1 (76.9-86.6), 81.5 (71.3-89.2), 93.4 (89.3-96.2), and 58.9 (49.2-68.1), respectively. When the pre-test probability of HCC is >70%, estimated as a PAGE-B score above 9, and EASL or LR-5/LR-TIV criteria are met, post-test probability would be >90%. CONCLUSIONS: EASL criteria and LR-5/LR-TIV categories show a positive predictive value in patients with HBV without cirrhosis that is comparable to that seen in patients with cirrhosis. These criteria can be used when the pre-test probability of HCC is >70%. LAY SUMMARY: Current guidelines recommend performing a biopsy to confirm the diagnosis of presumed hepatocellular carcinoma (HCC) in patients without cirrhosis. We showed that specific imaging criteria had a 100% agreement for categorizing lesions as HCC, with a positive predictive value of 93.4%. These imaging criteria could be used to diagnose HCC in HBV patients without cirrhosis with a pre-test probability of HCC of ≥70%, avoiding the need for a liver biopsy.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".