Pilot study using virtual 4-D tracking electromagnetic navigation bronchoscopy in the diagnosis of pulmonary nodules: a single center prospective study
Bibliographic record
Abstract
BACKGROUND: Electromagnetic navigation bronchoscopy (ENB) is a navigation technology intended to improve the diagnostic yield of pulmonary nodules. However, nodule displacement due to respiratory motion may compromise the accuracy of the navigation guidance. The Veran SPiNDrive ENB system employs respiratory-gating (4D-tracking) to compensate for this motion. The aim of the present study was to evaluate the diagnostic performance and safety of the Veran SPiNDrive system for biopsy of pulmonary nodules. METHODS: Adult patients with pulmonary nodules of ≥1 cm were enrolled at a single center. Both conventional bronchoscopy and 4D-tracking ENB were performed in one procedure session under general anesthesia, with the procedure order being randomly assigned. Radial probe endobronchial ultrasound and fluoroscopy were used in both groups. The diagnostic performance, safety, total procedure time, and total fluoroscopy time of the ENB phase were compared to the corresponding conventional bronchoscopy phase. RESULTS: The study was terminated due to poor accrual; a total of eleven patients were enrolled. The mean size of pulmonary nodules was 2.1 cm. The sensitivity for malignancy was 67% (6/9) and 56% (5/9) with conventional bronchoscopy and with 4D-tracking ENB, respectively. Two cases developed minor bleeding after conventional bronchoscopy, while no complications were observed after 4D-tracking ENB. The mean procedure time was 16.1 and 21.7 min (P=0.090), and the mean duration time for fluoroscopy use was 77 and 44 sec (P=0.056) for the conventional bronchoscopy and the 4D-tracking ENB phases, respectively. CONCLUSIONS: The diagnostic performance of the Veran SPiNDrive 4D-tracking ENB did not exceed that of conventional bronchoscopy for pulmonary nodules. No complications were seen during 4D-tracking ENB. A study with a larger number of participants is required for further assessment.
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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".