Magnetically actuated dexterous tools for minimally invasive operation inside the brain
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Operating in the brain for deep-seated tumors or surgical targets for epilepsy is technically demanding and normally requires a large craniotomy with its attendant risk and morbidity. Neuroendoscopic surgery has the potential to reduce risk and morbidity by permitting surgical access through a small incision with burr hole and a narrow corridor through the brain. However, current endoscopic neurosurgical tools are straight and rigid and lack dexterity, hindering their adoption for neuroendoscopic procedures. We propose a class of robotic neurosurgical tools that have magnetically actuated wristed end effectors small enough to fit through a neuroendoscope working channel. The tools were less than 3.2 millimeters in overall diameter and contained embedded permanent magnets that allowed wireless actuation with magnetic fields. Three magnetic tools are presented: a two-degrees-of-freedom (DoFs) wristed gripper, a one-DoF pivoting scalpel, and a one-DoF twisted string-actuated forceps. This work evaluated the feasibility of these tools for completing minimally invasive neurosurgical resection and cutting tasks. Experimental tests on a silicone brain phantom showed that the tools could reach the ventricle area for simulated tumor removal and access a section of the corpus callosotomy for a simulated tissue-severing procedure in epilepsy treatment. Integration of the magnetic end effectors with a concentric tube robot as a hybrid steerable surgical robotic system enabled in vivo experiments on piglets. These experiments show that wireless magnetic tools could perform essential neurosurgical tasks, including gripping, cutting, and biopsy on living brain tissue, suggesting their potential for clinical applications.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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