Current updates on the molecular genetics and magnetic resonance imaging of focal nodular hyperplasia and hepatocellular adenoma
Bibliographic record
Abstract
UNLABELLED: Focal nodular hyperplasia (FNH) and hepatocellular adenomas (HCAs) constitute benign hepatic neoplasms in adults. HCAs are monoclonal neoplasms characterised by an increased predilection to haemorrhage and also malignant transformation. On the other hand, FNH is a polyclonal tumour-like lesion that occurs in response to increased perfusion and has an uneventful clinical course. Recent advances in molecular genetics and genotype-phenotype correlation in these hepatocellular neoplasms have enabled a new classification system. FNHs are classified into the typical and atypical types based on histomorphological and imaging features. HCAs have been categorised into four subtypes: (1) HCAs with HNF-1α mutations are diffusely steatotic, do not undergo malignant transformation, and are associated with familial diabetes or adenomatosis. (2) Inflammatory HCAs are hypervascular with marked peliosis and a tendency to bleed. They are associated with obesity, alcohol and hepatic steatosis. (3) HCAs with β-catenin mutations are associated with male hormone administration and glycogen storage disease, frequently undergo malignant transformation and may simulate hepatocellular carcinoma on imaging. (4) The final type is unclassified HCAs. Each of these except the unclassified subtype has a few distinct imaging features, often enabling reasonably accurate diagnosis. Biopsy with immunohistochemical analysis is helpful in difficult cases and has strong implications for patient management. TEACHING POINTS: • FNHs are benign polyclonal neoplasms with no risk of haemorrhage or malignancy. • HCAs are benign monoclonal neoplasms classified into four subtypes based on immunohistochemistry. • Inflammatory HCAs show an atoll sign with a risk of bleeding and malignant transformation. • HNF-1α HCAs are steatotic HCAs with minimal complications and the best prognosis. • β-Catenin HCA shows variable MRI features and a high risk of malignancy.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.011 | 0.005 |
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".