SU-F-T-612: Investigation of Acoustic Neuroma Planning for Stereotactic Radiosurgery Utilizing Linac-Based Cone Collimators
Bibliographic record
Abstract
Purpose: To assess the feasibility of designing clinically-acceptable stereotactic radiosurgery (SRS) plans utilizing linac-based cone collimators for patients presenting with acoustic neuroma. Methods: Five acoustic neuroma patients with gross tumour volumes (GTVs) of sizes from 1.3 to 2.7 cc were studied. The cranial-caudal extent of the GTVs range from 1.1 to 1.7 cm whereas the largest cross-sectional extent of the lesions varied from 2.0 to 2.4 cm. No PTV margin was added. The relevant organs-at-risk (OARs) were the brainstem, brain, lens, eyes and cochlea. The SRS planning system, ERGO (Elekta), was used to design treatment plans with non-coplanar arcs delivered using various stereotactic cone sizes on an Elekta Synergy unit. The prescription dose was 12 Gy to be delivered in a single fraction. The final dose distribution for each target was achieved with two to five isocenters, each consisting of up to five non-coplanar arcs. Results: The achieved GTV V12, V11.4, and V11 were 97.6–98.6%, 99.2– 99.8% and 99.6–100%, respectively. The penalty for using multiple isocenters for a single target was a relatively high maximum dose of up to 18 Gy, which equals 150% of the prescription dose. In all cases, the RTOG and Paddick conformity indices fell within the range 1.45–1.70 and 0.57–0.66, respectively. Point maximum dose to the brainstem varied from 12.4 to 14 Gy and its V12 was ≤0.12cc. The point maximum doses to the lens and eyes were ≤80 and ≤110cGy, respectively, and total body V10 was ≤6.2cc. Point maximum dose to ipsilateral cochlea was similar to the prescription dose. Conclusion: Clinically-acceptable and deliverable dose distributions for acoustic neuroma cases can be achieved with linac-based stereotactic cones system. Up to five isocenters per target are required for GTVs of sizes ≤3cc. The treatment plans meet RTOG protocol requirement on conformity index.
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 | 0.000 | 0.001 |
| 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) | 0.001 | 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".