Cytopathology and ultrastructure identification of primary hepatic acinar cell carcinoma
Bibliographic record
Abstract
INTRODUCTION: A primary acinar cell carcinoma (ACC) of the liver was incidentally diagnosed in a clinically asymptomatic 80-year-old man. This study aimed to delineate critical diagnostic characteristics of an ACC originating uniquely from the liver to improve its future identification. PRESENTATION OF CASE: Enhanced MRI revealed a heterogenous, cystic 7.7 × 11.1 × 10.4 cm tumour occupying hepatic segments II and III. The mass demonstrated mild diffuse enhancement in hepatic arterial phase with minimal portal venous washout in a liver without cirrhotic features. A central stellate T2-hyperintense necrotic scar and outer capsule were apparent. No primary lesion or metastasis outside the liver was discernable. Post-left hepatic lobectomy, the tumour immunophenotype was atypical for presumptive diagnoses of hepatocellular carcinoma (HCC) or cholangiocarcinoma. Extensive morphologic workup on electron microscopy definitively diagnosed primary hepatic ACC by establishing presence of secretory zymogen-like granules, intracytoplasmic microvilli and acinar cell differentiation. Cytopathology revealed cellular lumen expressing PAS-positive diastase-resistant granular cytoplasmic contents. DISCUSSION: This case showcased the novel utility of electron microscopy that was crucial in yielding the definitive diagnosis. The previous literature on hepatic ACC was compiled here in context of the present case. The mechanism of hepatic acinar cell localization was also discussed. CONCLUSION: Primary hepatic ACC may easily be confused for other lesions due to nonspecific imaging patterns. Specifically, the presence of a central scar without risk factors for HCC can favour a diagnosis of benign entities such as focal nodular hyperplasia (FNH). Electron microscopy presents an important tool to identify primary hepatic ACC and may improve future patient outcomes.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".