Design and validation of an MRI‐compatible mechatronic system for needle delivery to localized prostate cancer
Bibliographic record
Abstract
PURPOSE: Prostate cancer is the most common non-cutaneous cancer among men in the United States and is the second leading cause of cancer death in American men. (Siegel et al. [2019] CA: A Cancer J Clin.69(1):7-34.) Focal laser ablation (FLA) has the potential to control small tumors while preserving urinary and erectile function by leaving the neurovascular bundles and urethral sphincters intact. Accurate needle guidance is critical to the success of FLA. Multiparametric magnetic resonance images (mpMRI) can be used to identify targets, guide needles, and assess treatment outcomes. The purpose of this work was to design and evaluate the accuracy of an MR-compatible mechatronic system for in-bore transperineal guidance of FLA ablation needles to localized lesions in the prostate. METHODS: The mechatronic system was constructed entirely of non-ferromagnetic materials, with actuation controlled by piezoelectric motors and optical encoders. The needle guide hangs between independent front and rear two-link arms, which allows for horizontal and vertical translation as well as pitch and yaw rotation of the guide with a 6.0 cm range of motion in each direction. Needles are inserted manually through a chosen hole in the guide, which has been aligned with the target in the prostate. Open-air positioning error was evaluated using an optical tracking system (0.25 mm RMS accuracy) to measure 125 trajectories in free space. Correction of systematic bias in the system was performed using 85 of the trajectories, and the remaining 40 were used to estimate the residual error. The error was calculated as the horizontal and vertical displacement between the axis of the desired and measured trajectories at a typical needle insertion depth of 10 cm. MR-compatibility was evaluated using a grid phantom to assess image degradation due to the presence of the system, and induced force, heating, and electrical interference in the system were assessed qualitatively. In-bore positioning error was evaluated on 25 trajectories. RESULTS: . The system was found to be compatible with the MR environment under the specified gradient-echo sequence parameters used in this study. CONCLUSION: A complete system for delivering needles to localized prostate tumors was developed and described in this work, and its compatibility with the MR environment was demonstrated. In-bore MRI positioning error was sufficiently small for targeting small localized prostate tumors.
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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 | 0.002 |
| 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".