Cytokeratin 20 Positive with HepPar-1 Negative in Hepatocellular Carcinoma - A Potential Diagnostic Pitfall in the Pathological Interpretation of Needle Core Liver Biopsy
Bibliographic record
Abstract
Needle core biopsy of liver lesions in adults with a clinical query of metastases is commonly encountered in general surgical pathology practice. The presence of poorly differentiated malignant cells forming ill-formed glands favors a working pathological diagnosis of metastatic carcinoma. If metastatic, determination of the primary site of origin is the next diagnostic challenge that faces the pathologist. An algorithmic IHC approach using cytokeratins and lineage markers often narrows the diagnostic possibilities with definition of tumor type and assigns site of origin. However, aberrant staining patterns are major potential diagnostic pitfalls. We present the case of a needle core liver biopsy with a poorly differentiated pseudoglandular HCC component that showed diffuse Cytokeratin (CK) 20 positivity with absent CK7 and Hepatocyte Paraffin-1 (HepPar-1) staining that was initially misinterpreted as metastatic adenocarcinoma from the lower gastrointestinal tract. However, with systematic integration of complete clinical, endoscopic and radiological data with reevaluation of the surrounding ‘non-neoplastic’ liver, the pathological diagnosis confirmed the presence of hepatocellular carcinoma arising in a background of chronic hepatitis C related cirrhosis, with a poorly differentiated pseudo glandular component associated with loss of HepPar-1 staining and aberrant strong diffuse positivity with CK20 posing as a diagnostic pitfall in the interpretation of limited material on needle core biopsies of mass lesions in an adult liver. We conclude with key learning points in the diagnostic interpretation of needle core liver biopsies from mass lesions in an adult liver with an underlying caveat to “never diagnose liver biopsies in ‘pathological isolation”
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".