Clinical practice of image-guided spine radiosurgery - results from an international research consortium
Bibliographic record
Abstract
BACKGROUND: Spinal radiosurgery is a quickly evolving technique in the radiotherapy and neurosurgical communities. However, the methods of spine radiosurgery have not been standardized. This article describes the results of a survey about the methods of spine radiosurgery at five international institutions. METHODS: All institutions are members of the Elekta Spine Radiosurgery Research Consortium and have a dedicated research and clinical focus on image-guided radiosurgery. The questionnaire consisted of 75 items covering all major steps of spine radiosurgery. RESULTS: Strong agreement in the methods of spine radiosurgery was observed. In particular, similarities were observed with safety and quality assurance playing an important role in the methods of all institutions, cooperation between neurosurgeons and radiation oncologists in case selection, dedicated imaging for target- and organ-at-risk delineation, application of proper safety margins for the target volume and organs-at-risk, conformal planning and precise image-guided treatment delivery, and close clinical and radiological follow-up. In contrast, three major areas of uncertainty and disagreement were identified: 1) Indications and contra-indications for spine radiosurgery; 2) treatment dose and fractionation and 3) tolerance dose of the spinal cord. CONCLUSIONS: Results of this study reflect the current practice of spine radiosurgery in large academic centers. Despite close agreement was observed in many steps of spine radiosurgery, further research in form of retrospective and especially prospective studies is required to refine the details of spinal radiosurgery in terms of safety and efficacy.
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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 | 0.033 | 0.076 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".