Two-phase survey on the frequency of use and safety of MRI for hearing implant recipients
Bibliographic record
Abstract
PURPOSE: Magnetic resonance imaging (MRI) is often used to visualize and diagnose soft tissues. Hearing implant (HI) recipients are likely to require at least one MRI scan during their lifetime. However, the MRI scanner can interact with the implant magnet, resulting in complications for the HI recipient. This survey, which was conducted in two phases, aimed to evaluate the safety and performance of MRI scans for individuals with a HI manufactured by MED-EL (MED-EL GmbH, Innsbruck, Austria). METHODS: A survey was developed and distributed in two phases to HEARRING clinics to obtain information about the use of MRI for recipients of MED-EL devices. Phase 1 focused on how often MRI is used in diagnostic imaging of the head region of the cochlear implant (CI) recipients. Phase 2 collected safety information about MRI scans performed on HI recipients. RESULTS: 106 of the 126 MRI scans reported in this survey were performed at a field strength of 1.5 T, on HI recipients who wore the SYNCHRONY CI or SYNCHRONY ABI. The head and spine were the most frequently imaged regions. 123 of the 126 scans were performed without any complications; two HI recipients experienced discomfort/pain. One recipient required reimplantation after an MRI was performed using a scanner that had not been approved for that implant. There was only one case that required surgical removal of the implant to reduce the imaging artefact. CONCLUSION: Individuals with either a SYNCHRONY CI or SYNCHRONY ABI from MED-EL can safely undergo a 1.5 T MRI when it is performed according to the manufacturer's safety policies and procedures.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".