2020 MR Safety for Cardiac Devices: An Update for Radiologists
Bibliographic record
Abstract
Magnetic resonance imaging (MRI) is a unique and powerful diagnostic tool that provides images without ionizing radiation and, at times, can be the only modality to properly assess and diagnose some pathologies. Although many patients will need an MRI in their lifetime, many of them are still being unjustly denied access to it due to what were once considered absolute contraindications, including MR nonconditional pacemakers and implantable cardioverter-defibrillators. However, there are a number of large studies that have recently demonstrated that MRI can safely be performed in these patients under certain conditions. In addition, there are an increasing number of novel cardiac devices implanted in patients who may require an MRI. Radiologists need to familiarize themselves with these devices, identify which patients with these devices can safely undergo MRI, and under which conditions. In this article, we will review the current literature on MR safety and cardiac devices, elaborate on how to safely image patients with cardiac devices, and share the expertise of our tertiary cardiac institute.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.003 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.003 |
| Insufficient payload (model declined to judge) | 0.007 | 0.004 |
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".