Optically Tracked Needle for Ultrasound-Guided Percutaneous Nephrolithotomy Puncture: A Preliminary Report
Bibliographic record
Abstract
Background and Aim: Precise needle puncture of the renal collecting system is an essential step for effective percutaneous nephrolithotomy (PCNL). The use of ultrasound for puncture is receiving increased attention. Ultrasound has recognized limitations related to poor observation of the needle tip. We aimed to assess whether an affordable open-source computerized needle navigation training system, using optically tracked ultrasonography, could improve performance of simulated PCNL puncture by urologic trainees, compared with conventional free hand manual sonographic puncture. Materials and Methods: This study describes a PCNL navigation system that can be recreated with any standard ultrasound machine using relatively inexpensive components. The system allows the needle tip to be precisely appreciated in the ultrasound image, its trajectory planned, and the appreciation of needle tip to target calix proximity sound effect. Eight participants (six trainees and two qualified urologists) assessed the PCNL training model. Alternating starting with freehand (control) and tracked needle (experimental) punctures were performed on a phantom kidney. Total procedure and the number of reinsertions required were recorded. Results: The mean time for freehand puncture was 89 seconds (range 13–173), whereas that of the optically tracked needle was 36 seconds (range 12–72). Thus, puncture time was significantly reduced by an average of 53 seconds (p = 0.045) in the experimental arm. The mean number of needle reinsertions was 3.3 with freehand compared with 1.3 in the optically tracked puncture (p = 0.005). The mean square root error of the optical tracking system was 1.8 mm (four calibrations averaged). Conclusion: This study demonstrates that affordable hardware and open-source software can be used to construct an optically tracked ultrasound navigation system for PCNL training. Statistically significant reduced puncture time and number of passes required for effective puncture are demonstrated. We feel that computerized needle tracking during PCNL puncture deserves further evaluation in a training and, potentially, in a clinical setting.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".