Design of a teleoperated needle steering system for MRI-guided prostate interventions
Bibliographic record
Abstract
Accurate needle placement plays a key role in success of prostate biopsy and brachytherapy. During percutaneous interventions, the prostate gland rotates and deforms which may cause significant target displacement. In these cases straight needle trajectory is not sufficient for precise targeting. Although needle spinning and fast insertion may be helpful, they do not entirely resolve the issue. We propose robot-assisted bevel-tip needle steering under MRI guidance as a potential solution to compensate for the target displacement. MRI is chosen for its superior soft tissue contrast in prostate imaging. Due to the confined workspace of the MRI scanner and the requirement for the clinician to be present inside the MRI room during the procedure, we designed a MRI-compatible 2-DOF haptic device to command the needle steering slave robot which operates inside the scanner. The needle steering slave robot was designed to be integrated with a previously developed pneumatically actuated transperineal robot for MRI-guided prostate needle placement. We describe design challenges and present the conceptual design of the master and slave robots and the associated controller.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".