P.137 Use of intravenous fluorescein for intra-operative localization of an intramedullary spinal cord tumour; a technical note
Bibliographic record
Abstract
Background: Localization of intramedullary spine tumors can be difficult. Various intraoperative aids have previously been described, but have limited use due to expense, complexity, and time. Intravenous fluorescein is an inexpensive and safe drug that may be useful in the localization of such tumors. We describe a technical description of the intra-operative use of fluorescein as an aid in the localization of a intramedullary spine tumour. Methods: In this technical report, the authors present a case example of a 56 year old man presenting with a intramedullary tumor at the level of C5/6. Intra-operatively intravenous Fluorescein was administered and the Pentero microscope BLUE™ 400 feature was used to accurately identify the lesion. Multiple biopsies of the fluorescent tissue were taken. Results: After 10 cardiac cycles the fluorescent coloring was isolated to what was thought to be the intramedullary lesion. Our myelotomy was made based on the uptake of this fluorescent coloring and multiple biopsies were taken. Final pathology confirmed this tissue was consistent with a high grade glioma. Conclusions: The use of intravenous fluorescein was a valuable aid in localizing the lesion and minimizing the size of our myelotomy. The use of intravenous fluorescein to localize high grade intramedullary spinal cord tumours appears to be safe, accurate, and inexpensive.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.004 |
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".