Assessing global and regional iron content in deep gray matter as a function of age using susceptibility mapping
Bibliographic record
Abstract
PURPOSE: To investigate the correlation of non-heme iron content in deep gray matter nuclei as a function of age using quantitative susceptibility mapping (QSM) from both whole-structural and regional perspectives. MATERIALS AND METHODS: We studied a group of 174 normal subjects ranging from 20 to 69 years old and measured the magnetic susceptibility of seven subcortical gray matter nuclei. SWI (susceptibility-weighted imaging) phase images were used to generate the susceptibility maps, which were acquired on a 1.5T scanner. The 3D whole-structural measurements were used to determine age-related thresholds, which were applied to calculate the local iron deposition (RII: portion of the structure that contains iron concentration larger than the structure threshold). Age-susceptibility correlation was reported for each measured structure for both the whole-region and two-region (low iron and high iron content regions) analysis. RESULTS: For the local high iron content region, a strong age-susceptibility correlation was found in the caudate nucleus (CN,R = 0.9), putamen (PUT,R = 0.9), red nucleus (RN,R = 0.8), globus pallidus (GP,R = 0.7), substantia nigra (SN,R = 0.5), and pulvinar thalamus (PT,R = 0.5); for the global iron content, a strong age-susceptibility correlation was found in CN(R = 0.6), PUT(R = 0.7), and RN(R = 0.6). Overall, for each structure analyzed in this study, regional analysis showed higher correlation coefficient and higher slope comparing to the whole-region analysis. Further, we found the quantitative conversion factor between magnetic susceptibility and iron concentration to be 1.03 ± 0.03 ppb per μg iron/g wet tissue. CONCLUSION: We conclude that the age-susceptibility correlation can serve as a quantitative magnetic susceptibility baseline as a function of age for monitoring abnormal global and regional iron deposition. A regional analysis has shown a tighter age related behavior, providing a reliable and sensitive reference for what can be considered normal iron content for studies of neurodegenerative diseases. J. Magn. Reson. Imaging 2016;44:59-71.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".