Minioptical Navigation System for CT-Guided Percutaneous Liver Procedures
Bibliographic record
Abstract
Purpose: To evaluate a new miniature optical navigation system for CT-guided liver interventions. Material and Methods: A two-center, prospective study was performed with four interventional radiologists. A total of 20 patients had CT-guided liver biopsy or ablation interventions utilizing the CT-Guide? navigation system (ActiViews Inc., Wakefield, MA) between July 2011 and December 2011. The navigation system consists of a self-adhesive patientsticker printed with coincident colored and radio-opaque reference markers, a miniature disposable video camera that clips on and off an interventional instrument, and software loaded on a computer to display the navigation information. The primary end point was the frequency of a satisfactory instrument position for the intended intervention. Results: The cohort consisted of 13 males and 7 females with an average age of 63.1 years (range of 38 to 80). Most of the patients, 70%, underwent CT-guided liver biopsy while the remainder had CT-guided ablation therapy. The average lesion size was 3.1 cm (range of 1.1 - 6.9 cm). All of the interventions, regardless of lesion size, met the primary end point of satisfactory instrument positioning. There were no device-related or unexpected adverse events recorded. Only one patient had a mild adverse event and it resolved without intervention. Conclusions: This study demonstrated the safety and effectiveness of the CT-Guide? navigation system for CT-guided liver interventions, for both biopsies and ablations. The targeting success rate for a satisfactory intervention was 100% with the system.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".