Safety and Efficacy of Modified Preoperative Lung Nodule Microcoil Localization Without Pleural Marking
Bibliographic record
Abstract
PURPOSE: The purpose of this pilot study was to evaluate the safety and efficacy of preoperative computed tomography (CT)-guided percutaneous microcoil lung nodule localization without pleural marking compared with the established technique with pleural marking. MATERIALS AND METHODS: Sixty-three consecutive patients (66.7% female, mean age 61.6±11.4 y) with 64 lung nodules resected between October 2008 and January 2014 were retrospectively evaluated. Of the nodules, 29.7% (n=19) had microcoil deployment with pleural marking (control group) and 70.3% (n=45) had microcoil deployment without pleural marking (pilot group). Clinical, pathologic, and imaging characteristics, radiation dose, CT procedure and operating room time, and complete resection and complication rates were compared between the pilot and control groups. RESULTS: There was no significant difference in nodule size (P=0.552) or distance from the pleural surface (P=0.222) between the pilot and control groups. However, mean procedure duration (53.6±18.3 vs. 72.8±25.3 min, P=0.001) and total effective radiation dose (5.1±2.6 vs. 7.1±4.9 mSv, P=0.039) were significantly lower in the pilot group compared with the control group. CT procedure-related complications (P=0.483) [including pneumothoraces (P=0.769) and pulmonary hemorrhage (P=1.000)], operating room time (P=0.926), complete resection rates (P=0.520), intraoperative complications (P=0.549), and postoperative complications (P=1.000) were similar between the pilot and control groups. CONCLUSIONS: Preoperative CT-guided lung nodule microcoil localization performed without visceral pleural marking appears to decrease the CT procedure time and radiation dose while maintaining equivalent complete resection rates and procedural and surgical complications, when compared with microcoil localization performed with pleural marking.
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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 | 0.004 |
| 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 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".