The Role of Stereotactic Cyst Aspiration for Glial and Metastatic Brain Tumors
Bibliographic record
Abstract
OBJECTIVE: To evaluate the role of stereotactic cyst aspiration in the context of multimodality management of cystic glial and metastatic tumors, we retrospectively reviewed our experience with 38 patients during a 10-year interval. METHODS: All 38 patients had one or more computed tomography or magnetic resonance imaging guided stereotactic cyst aspirations. Twenty-seven patients had glial neoplasms and 11 had metastatic brain tumors. Twenty-two patients underwent cyst aspiration as the initial treatment modality while 15 patients had cyst aspiration following previous treatments. RESULTS: In the immediate postoperative period, 19 of the 27 (70%) patients with gliomas and nine of the 11 (82%) patients with metastatic tumors experienced symptomatic improvement. No procedure-related morbidity was encountered. Twelve patients (31.5%) eventually required a catheter-reservoir system. Thirty-seven percent of patients with cystic glial neoplasms and 18% of patients with metastatic tumors had delayed cytoreductive surgery by craniotomy subsequent to stereotactic cyst aspiration. Reduction in tumor volume following aspiration facilitated Gamma knife radiosurgery in seven patients. CONCLUSION: Single stereotactic aspiration is a low risk procedure that provides immediate relief of symptoms in patients with cystic brain tumors. It appears to be valuable together with the use of other therapeutic strategies.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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".