Methods for Noninvasive Measurement of Tissue Iron in Cooley's Anemia
Bibliographic record
Abstract
To examine the relationship between myocardial storage iron and body iron burden, as assessed by hepatic storage iron measurements, we studied 22 patients with transfusion-dependent thalassemia syndromes, all being treated with subcutaneous deferoxamine, and 6 healthy subjects. Study participants were examined with a Philips 1.5-T Intera scanner using three multiecho spin echo sequences with electrocardiographic triggering and respiratory navigator gating. Myocardial and hepatic storage iron concentrations were determined using a new magnetic resonance method that estimates total tissue iron stores by separately measuring the two principal forms of storage iron, ferritin and hemosiderin. In a subset of 10 patients with beta-thalassemia major, the hepatic storage iron concentration had been monitored repeatedly for 12-14 years by chemical analysis of tissue obtained by liver biopsy and by magnetic susceptometry. In this subset, we examine the relationship between hepatic iron concentration over time and our current magnetic resonance estimates of myocardial iron stores. No significant relationship was found between simultaneous estimates of myocardial and hepatic storage iron concentrations. By contrast, in the subset of 10 patients with beta-thalassemia major, the correlation between the 5-year average of hepatic iron concentration and the current myocardial storage iron was significant (R = .67, P = .03). In these patients, myocardial storage iron concentrations seem to reflect the control of body iron over a period of years. Magnetic resonance methods promise to provide more effective monitoring of iron deposition in vulnerable tissues, including the liver, heart, and endocrine organs, and could contribute to the development of iron-chelating regimens that more effectively prevent iron toxicity.
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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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".