Electromagnetic-Guided Interstitial Catheter Navigation for Gynecological Brachytherapy: a Phase I Trial (E-MINT)
Bibliographic record
Abstract
Catheter insertion for gynecological interstitial brachytherapy is a challenging surgical procedure due to the lack of real-time guidance available to Radiation Oncologists. To mitigate the limitations associated with catheter placement, electromagnetic navigation (EMN) was proposed as a solution to the current interstitial brachytherapy workflow. The sequence of events leading up to the completion of this project were as follows, the validation of the system and then the application of the EMN system in a clinical trial. Using a phantom-based validation method, submillimetric accuracy and jitter was characterized for the operational performance of an EMN system in a brachytherapy operating room environment. Following validation, the EMN system was used for catheter placement in 5 patients, in an ongoing prospective clinical study. The mean catheter deflection documented was 3.52 +/- 2.53 mm when adopting EMN as a form of real-time guidance compared to 5.48 +/- 3.63 mm when the standard clinical workflow (SCW) was employed. The mean catheter spacing when using EMN was 9.31 +/- 4.81 mm compared to 7.09 +/- 6.06 mm when the SCW was followed. Also, the mean intraoperative time was 50.00 +/- 18.80 minutes for EMN and 38.20 +/- 15.29 minutes for the SCW. The results of this project demonstrate that electromagnetic navigated interstitial catheter placement is promising as a real-time guidance option for the interstitial gynecological brachytherapy workflow.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".