Anterior Interhemispheric Approach for 100 Tumors in and Around the Anterior Third Ventricle
Bibliographic record
Abstract
OBJECTIVE: We report our experience with anterior interhemispheric approach for tumors in and around the anterior third ventricle, including surgical technique, instrumentation, pre- and postoperative hormonal disturbances, and resection rate. METHODS: One hundred patients with 46 craniopharyngiomas, 12 hypothalamic gliomas, 12 meningiomas, 6 hypothalamic hamartomas, and 24 other lesions were operated on using an anterior interhemispheric approach with or without opening of the lamina terminalis. This surgical approach involves no frontal sinus opening; a narrow (approximately 15-20 mm in width) access between the bridging veins, which is sufficient to remove the tumor totally; and sparing of the anterior communicating artery. Specially designed long bipolar forceps and scissors are necessary for this approach, and concomitant use of angled instruments (endoscope, aspirator, and microforceps) is required frequently. The postsurgical follow-up period varied from 4 months to 18 years. RESULTS: Total removal of the neoplasm was accomplished in 37 of 46 patients with craniopharyngiomas (80.4%), whereas subtotal resection was performed in hypothalamic gliomas. No significant differences in pre- and postoperative hormonal disturbances were observed in 37 craniopharyngiomas and 10 hypothalamic gliomas. There was no operative mortality. Visual acuity was preserved or improved in 68 of 75 patients assessed. The Karnofsky Performance Scale score did not deteriorate in 72 of 75 patients tested. CONCLUSION: The minimally invasive anterior interhemispheric approach, with or without opening of the lamina terminalis, is useful for removal of tumors in and around the anterior third ventricle, such as craniopharyngiomas and hypothalamic gliomas.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.002 | 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".