Creating Low-Cost Phantoms for Needle Manipulation Training in Interventional Radiology Procedures
Bibliographic record
Abstract
Image-guided procedures play a critical role in the clinical practice of radiologists. Training radiology residents in these procedures, with early teaching of basic but fundamental skills, is therefore crucial to develop competence before they become autonomous and start their practice. It has been proposed in the literature that low-fidelity phantoms are appropriate to teach novice trainees. The authors propose a series of phantoms to teach the core skills necessary to perform procedures early in resident training. The phantoms described can be used to train skills necessary for performing US-guided biopsy, US-guided vascular puncture, cone-beam CT drainage, and fluoroscopy-guided lumbar puncture, as well as using the parallax effect to determine relative position at fluoroscopy. Phantoms are a valuable training tool, although it is important to consider the teaching audience when choosing or creating a model. For novices, a range of inexpensive low-fidelity gelatin-based phantoms can be used to train core skills in image-guided procedures. The online slide presentation from the RSNA Annual Meeting is available for this article. ©RSNA, 2021
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.043 | 0.013 |
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".