Percutaneous transthoracic localization of pulmonary nodules under C-arm cone-beam CT virtual navigation guidance
Bibliographic record
Abstract
PURPOSE: We aimed to describe our initial experience with percutaneous transthoracic localization (PTL) of pulmonary nodules using a C-arm cone-beam CT (CBCT) virtual navigation guidance system. METHODS: From February 2013 to March 2014, 79 consecutive patients (mean age, 61±10 years) with 81 solid or ground-glass nodules (mean size, 12.36±7.21 mm; range, 4.8-25 mm) underwent PTLs prior to video-assisted thoracoscopic surgery (VATS) excision under CBCT virtual navigation guidance using lipiodol (mean volume, 0.18±0.04 mL). Their procedural details, radiation dose, and complication rates were described. RESULTS: All 81 target nodules were successfully localized within 10 mm (mean distance, 2.54±3.24 mm) from the lipiodol markings. Mean number of CT acquisitions was 3.2±0.7, total procedure time was 14.6±5.14 min, and estimated radiation exposure during the localization was 5.21±2.51 mSv. Postprocedural complications occurred in 14 cases (17.3%); complications were minimal pneumothorax (n=10, 12.3%), parenchymal hemorrhage (n=3, 3.7%), and a small amount of hemoptysis (n=1, 1.2%). All target nodules were completely resected; pathologic diagnosis included invasive adenocarcinoma (n=53), adenocarcinoma-in-situ (n=10), atypical adenomatous hyperplasia (n=4), metastasis (n=7), and benign lesions (n=7). CONCLUSION: PTL procedures can be performed safely and accurately under the guidance of a CBCT virtual navigation system.
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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".