Bibliographic record
Abstract
Introduction and Objective:The management of small renal masses represents a challenge in that there are a significant number of masses that may be benign.With the increasing use of imaging modalities, there have been greater numbers of incidental renal masses detected.In the 1970's, 10% of tumors were identified incidentally, compared to 1995 where 61% of tumors were detected incidentally.Recent data shows approximately 20% are benign and do not require treatment.Treatments such as cryoablation, radiofrequency ablation (RFA), and surveillance are gaining popularity.Historically, the accuracy of renal biopsy was lower than 50%, but recent publications indicate that the accuracy is higher and approaching 90%.We attempt to ascertain the utility of image-guided biopsy to guide the management of these patients.Materials and Methods: Under computed tomography (CT) guidance, 61 patients with solid renal masses underwent 18-gauge core biopsy.The patients were observed if the pathology was benign and underwent intervention if the pathology was malignant.The group who underwent intervention; final surgical pathology was compared to biopsy pathology.Results: Mean patient age was 61.9 yrs (range: 32 -86yrs), mean tumor size was 3.4cm (range: 2.2 -4.8 cm).The non diagnostic rate was 5% (3/61).Pathology was compared of patients who underwent biopsy and subsequent nephretomy/ partial nephrectomy.The pathology of the biopsy specimen was compared to the final surgical specimen, There was 100% (24/24) concordance between biopsy pathology and final surgical pathology in the nephrectomy/partial nephrectomy group.Fuhrman grade was correctly predicted in 89.4% (17/19) and the correct histologic subtype was identified in all specimens.Oncocytomas and other benign pathology were found in 36.1% (22/61) of patients and were followed on imaging confirming the benign nature of their pathology.Sixteen percent (10/61) of patients underwent nephrectomy, 23% (14/61) had partial nephrectomies, 18% (11/61) had cryoablation, 5% (3/61) had RFA and 37.7% (23/61) were observed for at least 18 months with no progression of their masses.CT-guided biopsy allowed 37.7% of patients to be spared of intervention.Complications included 3 small perirenal hematomas which resolved with bedrest and no intervention.Conclusions: CT-guided percutaneous renal tumor biopsy was found to have a high diagnostic accuracy in predicting malignancy and spared approximately one-third of patients from unnecessary invasive intervention.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.561 | 0.275 |
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".