Cytomorphological and clinicopathological spectrum of pulmonary marginal zone lymphoma: the utility of immunophenotyping, <scp>PCR</scp> and <scp>FISH</scp> studies
Bibliographic record
Abstract
OBJECTIVE: To review cytomorphological criteria and clinicopathological findings in combination with ancillary tests for the specific diagnosis of pulmonary marginal zone lymphoma (MZL) in fine needle aspiration (FNA) specimens. METHODS: Cases of pulmonary MZL diagnosed using cytological specimens from 2005 to 2012 were retrieved and reviewed by three cytopathologists. Results of immunophenotypic analysis, interphase fluorescence in situ hybridization (FISH) and molecular assays were collated, together with clinical information and imaging data. Concurrent surgical biopsies were also retrieved. RESULTS: Fifteen lung FNA specimens were identified. The smears consisted predominantly of small centrocyte-like cells. Marked plasma cell differentiation was evident in 11 cases. All cases with slides available showed tissue fragments with lymphoid tangles (TFLTs). Multinucleated giant cells were present in nine cases, two of which showed granulomas. Immunophenotyping confirmed B-cell clonality in all cases. B-cell clonality was detected by polymerase chain reaction (PCR) in two samples. FISH identified MALT1 translocation in four of 10 cases tested and trisomy 3 in three of four cases. Concurrent surgical biopsies were diagnosed independently as MZL in seven cases. CONCLUSIONS: Cytology smears from lung FNA samples consisting of small lymphoid cells with a relative abundance of plasma cells or plasmacytoid cells and large TFLTs should prompt immunophenotyping and other ancillary studies, even if multinucleated giant cells and poorly formed granulomas are also identified. Specific diagnosis of pulmonary MZL in FNA samples can be rendered on the basis of morphological features coupled with the demonstration of B-cell clonality by immunophenotyping or PCR and cytogenetic abnormalities by FISH.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".