An ultra‐high field strength <scp>MR</scp> image‐guided robotic needle delivery system for in‐bore small animal interventions
Bibliographic record
Abstract
PURPOSE: The purpose of this study was to develop and validate an image-guided robotic needle delivery system for accurate and repeatable needle targeting procedures in mouse brains inside the 12 cm inner diameter gradient coil insert of a 9.4 T MR scanner. Many preclinical research techniques require the use of accurate needle deliveries to soft tissues, including brain tissue. Soft tissues are optimally visualized in MR images, which offer high-soft tissue contrast, as well as a range of unique imaging techniques, including functional, spectroscopy and thermal imaging, however, there are currently no solutions for delivering needles to small animal brains inside the bore of an ultra-high field MR scanner. This paper describes the mechatronic design, evaluation of MR compatibility, registration technique, mechanical calibration, the quantitative validation of the in-bore image-guided needle targeting accuracy and repeatability, and demonstrated the system's ability to deliver needles in situ. METHODS: Our six degree-of-freedom, MR compatible, mechatronic system was designed to fit inside the bore of a 9.4 T MR scanner and is actuated using a combination of piezoelectric and hydraulic mechanisms. The MR compatibility and targeting accuracy of the needle delivery system are evaluated to ensure that the system is precisely calibrated to perform the needle targeting procedures. A semi-automated image registration is performed to link the robot coordinates to the MR coordinate system. Soft tissue targets can be accurately localized in MR images, followed by automatic alignment of the needle trajectory to the target. Intra-procedure visualization of the needle target location and the needle were confirmed through MR images after needle insertion. RESULTS: The effects of geometric distortions and signal noise were found to be below threshold that would have an impact on the accuracy of the system. The system was found to have negligible effect on the MR image signal noise and geometric distortion. The system was mechanically calibrated and the mean image-guided needle targeting and needle trajectory accuracies were quantified in an image-guided tissue mimicking phantom experiment to be 178 ± 54 μm and 0.27 ± 0.65°, respectively. CONCLUSIONS: An MR image-guided system for in-bore needle deliveries to soft tissue targets in small animal models has been developed. The results of the needle targeting accuracy experiments in phantoms indicate that this system has the potential to deliver needles to the smallest soft tissue structures relevant in preclinical studies, at a wide variety of needle trajectories. Future work in the form of a fully-automated needle driver with precise depth control would benefit this system in terms of its applicability to a wider range of animal models and organ targets.
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How this classification was reachedexpand
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 | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".