Prediction of Force and Image Artifacts Under MRI for Metals Used in Medical Devices
Bibliographic record
Abstract
Selection of compatible materials for magnetic resonance imaging (MRI) is a challenging task as severe restrictions are imposed on materials used in and around the scanner due to the static and dynamic magnetic fields involved. Much of the data available for MRI-compatible materials are scattered throughout the literature and are often too device specific. This paper focuses on engineering materials with sufficient strength and stiffness, and with low enough susceptibility to be used in this environment. Experimental results of generic test specimens are used to give comparable performance indicators for candidate materials. As expected, the force varies linearly with susceptibility with good correlation with the theoretical predictions except for brass 360. It is believed the susceptibility for brass 360 in the literature was mistakenly recorded, and our results suggest a value of 112 ppm. The image artifacts were compared based on the radius of the affected area in the image. The theory greatly overpredicts the affected area; however, the trends in terms of susceptibility seem fairly accurate. The size of the artifact increases with susceptibility, echo time, and the use of turbo spin echo over gradient echo sequences. However, the experimental data contradicted the theory by showing no appreciable effect due to bandwidth.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".