Advancing neurosurgery with image-guided robotics
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Bibliographic record
Abstract
Robotic systems are being introduced into surgery to extend human ability. NeuroArm represents a potential change in the way surgery is performed; this is the first image-guided, MR-compatible surgical robot capable of both microsurgery and stereotaxy. This paper presents the first surgical application of neuroArm in an investigation of microsurgical performance, navigation accuracy, and Phase I clinical studies. To evaluate microsurgical performance, 2 surgeons performed microsurgery (splenectomy, bilateral nephrectomy, and thymectomy) in a rodent model using neuroArm and conventional techniques. Two senior residents served as controls, using the conventional technique only (8 rats were used in each of the 3 treatment groups; the 2 surgeons each treated 4 rats from each group). Total surgery time, blood loss, thermal injury, vascular injury, and animal death due to surgical error were recorded and converted to an overall performance score. All values are reported as the mean +/- SEM when normally distributed and as the median and interquartile range when not. Surgeons were slower using neuroArm (1047 +/- 69 seconds) than with conventional microsurgical techniques (814 +/- 54 seconds; p = 0.019), but overall performance was equal (neuroArm: 1110 +/- 82 seconds; microsurgery: 1075 +/- 136 seconds; p = 0.825). Using microsurgery, the surgeons had overall performance scores equal to those of the control resident surgeons (p = 0.141). To evaluate navigation accuracy, the localization error of neuroArm was compared with an established system. Nanoparticles were implanted at predetermined bilateral targets in a cadaveric model (4 specimens) using image guidance. The mean localization error of neuroArm (4.35 +/- 1.68 mm) proved equal to that of the conventional navigation system (10.4 +/- 2.79 mm; p = 0.104). Using the conventional system, the surgeon was forced to retract the biopsy tool to correct the angle of entry in 2 of 4 trials. To evaluate Phase I clinical integration, the role of neuroArm was progressively increased in 5 neurosurgical procedures. The impacts of neuroArm on operating room (OR) staff, hardware, software, and registration system performance were evaluated. NeuroArm was well received by OR staff and progressively integrated into patient cases, starting with draping in Case 1. In Case 2 and all subsequent cases, the robot was registered. It was used for tumor resection in Cases 3-5. Three incidents involving restrictive cable length, constrictive draping, and reregistration failure were resolved. In Case 5, the neuroArm safety system successfully mitigated a hardware failure. NeuroArm performs as well and as accurately as conventional techniques, with demonstrated safety technology. Clinical integration was well received by OR staff, and successful tumor resection validates the surgical applicability of neuroArm.
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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 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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