Surgical results in patients with CNS lymphoma. Comparison of predictive value of intraoperative MRI and intraoperative histological examination for diagnostic biopsy yield
Bibliographic record
Abstract
Introduction: Central nervous system lymphoma poses significant diagnostic challenges, with stereotactic biopsy being the gold standard for diagnosis. Intraoperative magnetic resonance imaging and intraoperative histological examination are utilized to enhance biopsy yield, yet their comparative efficacy remains unclear. Research question: This study aims to compare the diagnostic yield of intraoperative magnetic resonance imaging and intraoperative histological examination in stereotactic brain biopsies for central nervous system lymphoma. Materials and methods: A retrospective analysis was conducted on 115 patients who underwent stereotactic brain biopsies for central nervous system lymphoma. Diagnostic accuracy, sensitivity, specificity, positive predictive value, and negative predictive value of intraoperative magnetic resonance imaging and intraoperative histological examination were assessed and compared. Results: Out of 125 surgeries, frameless biopsies were the most common, accounting for 74.4 percent. Intraoperative magnetic resonance imaging demonstrated a sensitivity of 80.00 percent and a specificity of 98.51 percent (AUC = 0.893, p = 0.004), whereas intraoperative histological examination showed a sensitivity of 66.67 percent and a specificity of 59.09 percent (AUC = 0.629, p = 0.459). Discussion and conclusions: The study emphasizes the critical role of intraoperative examinations, thus improving precision and diagnostic yield in the surgical management of central nervous system lymphoma. Intraoperative magnetic resonance imaging outperforms intraoperative histological examination in terms of sensitivity and specificity for confirming positive biopsy yields in central nervous system lymphoma, thereby reducing the need for additional surgeries. These findings support the routine use of intraoperative magnetic resonance imaging in the surgical strategy for central nervous system lymphoma to improve diagnostic accuracy and patient outcomes.
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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 | 0.009 |
| 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 | 0.000 | 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".