Assessment of skill translation of intrathecal needle insertion using real-time needle tracking with an augmented reality display
Bibliographic record
Abstract
PURPOSE: Current lumbar puncture simulators lack visual feedback of the needle path. We propose a lumbar puncture simulator that introduces a visual virtual reality feedback to enhance the learning experience. This method incorporates virtual reality and a position tracking system. We aim to assess the advantages of the stereoscopy of virtual reality (VR) on needle insertion skills learning. METHODS: We scanned and rendered spine models into three-dimensional (3D) virtual models to be used in the lumbar puncture simulator. The motion of the needle was tracked relative to the spine model in real-time using electromagnetic tracking, which allows accurate replay of the needle insertion path. Using 3D Slicer and SlicerVR, we created a virtual environment with the tracked needle and spine. In this study, 23 medical students performed a traditional lumbar puncture procedure using the augmented simulator. The participants’ insertions were tracked and recorded, allowing them to review their procedure afterwards. Twelve students were randomized into a VR group; they reviewed their procedure in VR, while the Control group reviewed their procedures on computer monitor. Students completed a standard System Usability Survey (SUS) about the system, and a self-reported confidence scale (1-5) in performing lumbar puncture. RESULTS: We integrated VR visual feedback in a traditional lumbar puncture simulator. The VR group gave an average 70.4 on the System Usability Survey (SUS) vs. 66.8 of the Control group. The only negative feedback on VR was that students felt they required technical assistance to set it up (SUS4). The results show a general affinity for VR and its easeof- use. Furthermore, the mean confidence level rose from 1.6 to 3.2 in the VR group, vs. 1.8 to 3.1 in the Control group (1.6 vs. 1.3 improvement). CONCLUSION: The VR-augmented lumbar puncture simulator workflow incorporates visual feedback capabilities and accurate tracking of the needle relative to the spine model. Moreover, VR feedback allow for a more comprehensive spatial awareness of the target anatomy for improved learning.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".