Percutaneous Lung Ablation Combined with Video-Assisted Thoracic Surgery Guided by Three-Dimensional Reconstruction in the Treatment of Multiple Pulmonary Nodules
Bibliographic record
Abstract
Background: With the wide application of lung cancer screening, the detection rate of multiple pulmonary nodules (MPNs) has increased annually. However, the optimal therapeutic strategy for MPNs has not achieved a consensus. This study aims to report a novel hybrid technique for the treatment of MPNs. Methods: A total of 8 patients received CT-guided lung microwave ablation combined with video-assisted thoracic surgery from March 2020 to March 2023. Three-dimensional reconstruction was conducted to distinguish the precise localization, predict the resection extent, and conduct the optimal operation procedure for each lung nodule. The clinicopathological characteristics as well as surgical complications and short-term outcomes were recorded. Results: 8 patients with a total of 18 nodules were treated by our hybrid technique. Two patients had a FEV1％ Pred lower than 90％. The nodules treated by surgery were confirmed as malignant by pathological results with a median size of 9mm.The median size of the nodules treated by ablation was 6mm. The median ablation power used for the nodules was 45 W (range, 40–50W). The ablation time was 5min. The median distance between nodules to pleura was 31mm (range 19-56mm). This hybrid technique did not increase the rate of complication and prolonged hospital stay. During the short term of follow-up, no recurrence occurred in the patients. Conclusions: We present our experience of percutaneous lung ablation combined with video-assisted thoracic surgery guided by three-dimensional reconstruction in the treatment of multiple pulmonary nodules. This technique provides a minimally invasive and personalized therapy for patients with MPNs.
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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) | 0.001 | 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".