Individualised connectomic-guided radiosurgical thalamotomy for chronic pain
Why this work is in the frame
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Bibliographic record
Abstract
INTRODUCTION: Radiosurgery targeting the thalamus has long been used to treat refractory pain, with medial thalamotomy as a key approach. Traditionally, targeting relied on indirect methods based on anatomical atlases, which do not account for individual variations in brain connectivity. Recent advances in connectomic-guided stereotactic radiosurgery have improved precision in the treatment of movement disorders, but their application to pain management remains underexplored. This study evaluates the feasibility of connectomic-guided radiosurgery for refractory pain using Brainlab Elements, integrating auto-segmentation and manual contouring for patient-specific planning. METHODS: We analysed the thalamic target's structural and functional connectivity using the FMRIB Software Library and Advanced Normalisation Tools. The region of interest (ROI) was mapped using diffusion tensor imaging and functional magnetic resonance imaging to assess connectivity with pain-processing structures, including the periventricular grey (PVG) and ventroposteromedial (VPM) nucleus. Connectivity analysis was performed with Brainlab Elements and validated against independent connectomic studies. Dose-volume relationships for PVG and VPM were retrospectively assessed in patients treated with radiosurgery for chronic pain. RESULTS: Connectivity analysis showed that fibres within the ROI extend to primary motor (M1) and sensory (S1) cortices, while descending fibres reach the periaqueductal gray (PAG). Functional connectivity linked the ROI to key pain-processing regions, including the prefrontal cortex, insula, amygdala, and cerebellum. Retrospective dose-volume (DVs) analysis revealed clear differences between the volumes receiving more than 20 Gy in the original vs connectomic-based target. . The integration of Brainlab Elements facilitated connectomic-guided targeting, enabling a patient-specific approach to radiosurgery. CONCLUSION: Connectomic-guided radiosurgery is a feasible approach that enables precise, patient-specific targeting pain management. Auto-segmentation of PVG and VPM allows dose-volume assessment, potentially correlating with clinical outcomes. Standardising connectomic-guided planning may enhance radiosurgical precision and support future clinical research in refractory pain.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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) | 0.000 | 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 it