Development of a 3D ultrasound guidance system for permanent breast seed implantation
Bibliographic record
Abstract
PURPOSE: Pd seeds using needles inserted through a template and guided by two-dimensional (2D) ultrasound (US). However, operator dependence has been highlighted as a limitation of this procedure. Consequently, we propose and have developed an intraoperative guidance system using three-dimensional (3D) US and an instrumented mechanical arm to provide intraoperative 3D imaging and needle template tracking. METHODS: A mechatronic 3D US scanner reconstructs a 3D image from 150 2D images. A tracked mechanical arm mounted to the scanner locates four fiducial points on the template, registering the template to the 3D image. 3D reconstruction was validated for linear and volumetric measurement accuracy using phantoms of known geometry. In vivo breast US image quality was evaluated in a healthy volunteer. The encoded arm was calibrated and validated using a jig with divots at known locations relative to the scanner and the scanner registered to the 3D US image using intersecting strings in a fluid-filled test jig. Template registration accuracy was assessed using a machined test jig. Tracking accuracy was assessed in a liquid medium by comparing tracked and imaged needle tip positions. Finally, the system was used to guide a mock procedure in a patient-specific phantom and micro-CT imaging used to evaluate its accuracy. RESULTS: Geometric validation showed median distances within ±1.1% of expected values and volumetric validation showed differences of ≤4.1%. Tracking arm point measurements showed an average error of 0.43 mm and 3D US volume registration showed target registration error ≤0.9 mm. Mean template registration accuracy in each axis of translation/rotation was ≤1.3 mm/1.0°. Mean needle-targeting error was 2.5 mm and 1.6° for needle tips and trajectories, respectively. Mean needle tip and angular errors of the phantom procedure were 2.1 mm and 2.6°. Modeled seed displacement of the phantom procedure showed mean error of 2.6 mm and a maximum of 3.8 mm. CONCLUSIONS: A 3D US guidance system for PBSI has been developed. Benchtop performance and image quality in volunteer scans are satisfactory. A phantom PBSI procedure was successfully delivered using the system with maximum seed error within dosimetric benchmarks (<5 mm). Translation of the device into the clinic is forthcoming.
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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 | 0.001 | 0.001 |
| 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 | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".