Ultrasound- Versus CT-Guided Subpleural Lung and Pleural Biopsy: An Analysis of Wait Times, Procedure Time, Safety, and Diagnostic Adequacy
Bibliographic record
Abstract
Purpose: To compare the wait times, safety, and diagnostic adequacy of computed tomography (CT)–guided percutaneous lung biopsies with ultrasound (US) guidance for subpleural lung and pleural lesions. Methods: Consecutive CT- and US-guided biopsies performed at our institution between January 2018 and January 2019 were retrospectively reviewed. Biopsy wait times, lesion size, degree of pleural contact, procedure duration, number of needle passes, complications, and pathologic diagnosis were recorded and compared. Results: A total of 158 biopsies of subpleural or pleural-based lesions were reviewed. Forty-three cases utilized US guidance, while 115 cases used CT, 41 with conventional CT (CCT), and 74 with cone-beam CT guidance (CBCT). Overall, the mean lesion maximum axial diameter and length of pleural contact for US-guided biopsies was greater than for CT (4.8 ± 2.6 cm vs 3.2 ± 1.9 cm and 4.0 ± 2.5 cm vs 2.6 ± 1.7 cm, respectively, P < .001). Wait times for US-guided biopsies were significantly shorter than CCT by 10.9 days on average while being equivalent to CBCT. Procedure time was shorter for lesions localized with US than CT (29.5 ± 16.4 minutes vs 37.6 ± 19.5 minutes, P = .007) despite CT using less needle passes per lesion (3.5 ± 1.1 vs 3.1 ± 0.8, P = .034). Sample adequacy was equivalent for both modalities (88% for US and 92% for CT). The frequency of pneumothoraces was similar between US (12%) and CT (15%). Conclusion: Ultrasound and CT guidance have similar safety and diagnostic adequacy for subpleural lung and pleural biopsies. Ultrasound guidance has shorter wait and procedure times.
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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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".