Diagnostic Yield and Complication Rate in Percutaneous Needle Biopsy of Renal Hilar Masses With Comparison With Renal Cortical Mass Biopsies in a Cohort of 195 Patients
Bibliographic record
Abstract
OBJECTIVE: The objective of this study was to compare diagnostic yield and complication rate in needle biopsy (NB) of renal hilar and cortical masses. MATERIALS AND METHODS: With institutional review board approval, we retrospectively studied 195 patients (120 men, 75 women; mean age ± SD, 67 ± 13 years old) who underwent ultrasound-guided renal mass NB between January 2013 and December 2017. Operator years of experience, biopsy technique (coaxial or successive), needle gauge (22-gauge fine-needle aspiration, 18-gauge core-needle, or both), number of passes, postprocedural complication, and histopathologic diagnoses were recorded. A radiologist who was blinded to histopathologic diagnoses recorded mass location (upper pole, interpolar region, lower pole) and percentage of hilar involvement. Comparisons were performed using independent t and chi-square tests. RESULTS: Of the masses biopsied, 5.6% (11/195) were 100% hilar (mean hilar involvement, 20.8% ± 29.8%; range, 0-100%). Mean lesion size was 44 ± 27 mm (range, 12-157 mm). NB diagnosis was established in 84.6% (165/195) of masses, and 15.4% (30/195) of biopsies were inconclusive, with no association with size (p = 0.55) or percentage of hilar involvement (p = 0.756). In the purely hilar masses, diagnosis was established in 72.7% (8/11) compared with 85.3% (157/184) with any cortical involvement (p = 0.265). There was no association between diagnosis and operator years of experience, biopsy technique, needle gauge, or number of passes (p > 0.05). Bleeding occurred after biopsy in 7.7% (15/195) of cases, was associated with percentage of hilar involvement (39.3% ± 44.9% vs 19.3% ± 27.8%; p = 0.012), and was more common in purely hilar masses (36.4% [4/11] vs 5.6% [11/195]; p < 0.001). Complications were not associated with any other feature (p > 0.05). CONCLUSION: Percutaneous biopsy of renal hilar masses is technically feasible with diagnostic yield similar to that of cortical masses but with postprocedural bleeding more often than what is seen with cortical masses.
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 | 0.001 | 0.008 |
| 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 | 0.000 |
| 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".