Magnetic resonance imaging in preseptal ferromagnetic foreign bodies
Bibliographic record
Abstract
OBJECTIVE: To review the literature on safety of magnetic resonance imaging (MRI) in patients with preseptal ferromagnetic foreign bodies. METHODS: We describe 3 cases of MRI in patients with preseptal ferromagnetic foreign bodies (FFBs) from our institution. RESULTS: The FFBs were all preseptal, adjacent to the medial canthus (n = 2) and lateral canthus (n = 1). None of the patients had any ocular complications post-MRI. The literature review identified an additional 7 cases with intraocular and preseptal FFBs that underwent MRI. The FFBs ranged in size from 1.0 mm to 3.5 mm. The FFBs were intraocular (n = 6), or preseptal (n = 1). The MRI field strength ranged from 0.35 T to 1.5 T. Five (83.3%) of the patients with intraocular FFBs had ocular complications, which included hyphema (n = 2), cataract (n = 3), vitreous haemorrhage (n = 1), and corneal scar (n = 1). The patient with preseptal FFB did not have post-MRI complications. CONCLUSIONS: There is some evidence to suggest that patients with preseptal FFBs may be less likely to experience complications post-MRI compared to intraocular FFBs. Various factors affect the safety of MRIs, including FFB location, size, proximity to visually-significant structures, and MRI field strength.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".