Parenteral ferumoxytol interaction with magnetic resonance imaging: a case report, review of the literature and advisory warning
Bibliographic record
Abstract
BACKGROUND: Ferumoxytol is a safe and effective parenteral therapy used for the treatment of iron deficiency anaemia that has recently been approved for use in North America and in Europe. METHODS: Ferumoxytol consists of a superparamagnetic iron oxide (SPIO) core, which causes T1, T2 and T2* shortening effects, and a carbohydrate shell, which results in a prolonged intravascular half life. RESULTS: These properties are under-reported and not well recognised. They can interfere with MRI interpretation, potentially masking enhancement and rendering examinations non-diagnostic or simulating pathologic disease states. Both radiologists and non-radiologist physicians must consider the potential interaction of ferumoxytol with MRI when interpreting and prescribing MRI examinations in their patients. MAIN MESSAGES: • Ferumoxytol has recently been approved for the treatment of iron deficiency anaemia. • Ferumoxytol is a small iron oxide particle with prolonged intravascular half life and T1, T2 and T2* shortening effects. • Administration of ferumoxytol can mask enhancement, rendering MRI studies potentially non-diagnostic. • Ferumoxytol can mimic diseases such as haemosiderosis, haemochromatosis and superficial siderosis. • Ferumoxytol interactions with MRI must be recognised by radiologists and non-radiologist physicians.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".