Contemporary Results of Percutaneous Biopsy of 100 Small Renal Masses: A Single Center Experience
Bibliographic record
Abstract
PURPOSE: Percutaneous biopsy of small renal tumors has not been historically performed because of concern about complications and accuracy. We reviewed our experience with percutaneous needle biopsy of small renal masses to assess the safety and accuracy of the procedure, the potential predictors of a diagnostic result and the role of biopsy in clinical decision making. MATERIALS AND METHODS: A total of 100 percutaneous needle biopsies of renal masses less than 4 cm were performed between January 2000 and May 2007 with 18 gauge needles and a coaxial technique under ultrasound and/or computerized tomography guidance. A retrospective chart review was performed to document the complication rate and the ability to obtain sufficient tissue for diagnosis. Tumor size, tumor type (solid vs cystic), image guidance, biopsy number and core length were assessed for the ability to predict a diagnostic biopsy. RESULTS: No tumor seeding or significant bleeding was observed. Of the core biopsies 84 (84%) were diagnostic for a malignant (66) or a benign (18) tumor. Larger tumor size and a solid pattern were significant predictors of a diagnostic result. Histological subtyping and grading were possible on core biopsies in 93% and 68% of renal cell carcinomas, respectively. A total of 20 patients underwent surgery after a diagnostic biopsy. The histological concordance of biopsies and surgical specimens was 100%. CONCLUSIONS: Percutaneous needle biopsy of renal masses less than 4 cm is safe and provides adequate tissue for diagnosis in most cases. Larger tumor size and a solid pattern are significant predictors of a successful biopsy. Renal tumor biopsy decreases the rate of unnecessary surgery for benign tumors and can assist the clinician with treatment decision making, especially in elderly and unfit patients.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".