Gross and microscopic changes of liver neoplasms and background hepatic structures following neoadjuvant therapy
Bibliographic record
Abstract
Liver transplantation is a surgical option with curative intent used in the management of some cases of hepatocellular carcinoma and cholangiocarcinoma (hilar, rarely intrahepatic). A number of different therapeutic modalities including ablative techniques, arterially directed therapies, radiation and chemotherapy are used in the neoadjuvant setting prior to liver transplantation with the goals of preventing tumour progression, decreasing post-transplant recurrence and possibly downstaging patients with tumour burden beyond what is acceptable by current transplant criteria. Pathologists evaluating hepatic explants must be aware of these neoadjuvant therapies and the alterations induced by them in both tumourous and non-tumourous tissue. In this review, we discuss common neoadjuvant therapies used in in this setting, as well as the gross and microscopic changes induced by these presurgical treatments within hepatic neoplasms as well as the background hepatic parenchyma and nearby structures. Select secondary tumours involving the liver which are pretreated will also be discussed. Finally, proper reporting of these changes will be mentioned.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".