Cytologic features and diagnostic value of PeriView FLEX transbronchial needle aspiration targeting pulmonary nodules
Bibliographic record
Abstract
BACKGROUND: Transbronchial needle aspiration (TBNA) of peripheral lung nodules can be difficult with conventional devices due to their limited flexibility. A promising new technology for accessing these lesions is the PeriView FLEX TBNA device, which has a flexible spiral-grooved needle. The present study reports the unique cytologic features, diagnostic value, and potential pitfalls of PeriView FLEX TBNA specimens. METHODS: This study retrospectively evaluates 113 consecutive cases of lung nodules sampled using the PeriView FLEX device with radial endobronchial ultrasound guidance. RESULTS: PeriView FLEX specimens were satisfactory for evaluation in 111 of 113 cases (98%). A diagnosis of malignancy was made on 64 specimens (57%), with 100% specificity and 70% sensitivity for malignancy. In 4 cases, the PeriView FLEX sample was the only specimen from bronchoscopy that was diagnostic of malignancy. Of the 64 PeriView FLEX specimens with malignant cells, 58 (91%) were adequate for immunohistochemistry and 44 (69%) were adequate for molecular genetic testing. Potential pitfalls were largely ameliorated through education regarding the unique features of PeriView FLEX samples, such as the expected abundance of anthracotic pigment and the paucity of lymphocytes. CONCLUSIONS: TBNA using the PeriView FLEX device to sample pulmonary nodules contributed to the diagnostic value of bronchoscopy and tended to provide sufficient tissue for ancillary studies. Many of the possible pitfalls may be avoided through consideration of the unique cytologic features associated with this novel sampling method.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".