Pleural Mesothelioma: Sensitivity and Incidence of Needle Track Seeding after Image-guided Biopsy versus Surgical Biopsy
Bibliographic record
Abstract
PURPOSE: To retrospectively compare the sensitivity of image-guided core-needle biopsy, thoracoscopy, and thoracotomy in the diagnosis of malignant pleural mesothelioma and to retrospectively determine the incidence of needle track seeding after these procedures. MATERIALS AND METHODS: Institutional review board approval was obtained, and informed consent was not required. The study included 100 consecutive patients (81 men, 19 women; average age, 65.8 years) with pathologically proved malignant pleural mesothelioma who were treated between 1994 and 2002. A total of 23 core-needle biopsies were performed in 22 patients, and 11 of these biopsies were coupled with fine-needle aspiration biopsy. A coaxial technique was used, and biopsy was performed with fluoroscopic (12 biopsies), computed tomographic (10 biopsies), or ultrasonographic (one biopsy) guidance. Sixty-nine patients underwent surgical biopsy in the form of thoracoscopy (n = 51) and/or thoracotomy (n = 21). Patients were followed up clinically for any evidence of needle track seeding after image-guided or surgical procedures. The sensitivity of diagnostic procedures and the incidence of needle track seeding as a result of intervention were calculated. RESULTS: Sensitivity was 86% for image-guided core-needle biopsy, 94% for thoracoscopy, and 100% for thoracotomy. The incidence of needle track seeding was 4% for image-guided core-needle biopsy and 22% for surgical biopsy. CONCLUSION: Image-guided core-needle biopsy in patients with malignant pleural mesothelioma has a lower incidence of needle track seeding than surgical biopsy and has a high sensitivity for diagnosis.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.018 |
| 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 | 0.001 | 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".