Tracked Ultrasonography Snapshots Enhance Needle Guidance for Percutaneous Renal Access: A Pilot Study
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Although ultrasonography-guided percutaneous nephrostomy is relatively safe, a number of factors make it challenging for inexperienced operators. A computerized needle navigation technique using tracked ultrasonography snapshots was investigated to determine whether performance of percutaneous nephrostomy by inexperienced users could be improved. METHODS: Ten operators performed the procedure on a phantom model with alternating needle guidance between conventional ultrasonography and tracked ultrasonography snapshots. The needle was reinserted until fluid backflow confirmed calyceal access. Needle trajectories were recorded using the real time needle navigation system for offline evaluation of operator performance. Recorded needle trajectories were used to measure needle motion path length inside the phantom tissue, number of reinsertions, total procedure time, and needle insertion time as end points of this study. RESULTS: Needle path length measured inside the phantom tissue was significantly lower with ultrasonography snapshots guidance (295.0±23.1 mm, average±standard error of the mean) compared with control procedures (977.9±144.4 mm, P<0.01). This was associated with a significantly lower number of needle insertion attempts with ultrasonography snapshots (average 1.27±0.10 vs 2.83±0.31, P<0.01). The total procedure time and the needle insertion time were also significantly lower with ultrasonography snapshots guidance. CONCLUSION: Tracked ultrasonography snapshots appear to improve the performance of percutaneous nephrostomy in these preliminary investigations, justifying further validation studies. The presented navigation system is reproducible because of commercially available hardware and open-source software components, facilitating its potential role in clinical practice.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.000 | 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".