Designing and Evaluating a 109Cd based XRF System For Skin Iron Measurements: A Validation Study in Normal and Iron Overload Conditions
Bibliographic record
Abstract
The health impact of iron (Fe) deficiency or excess on the human body can be severe. Existing clinical methods for assessing body Fe levels have limitations. This thesis focuses on the potential of measuring skin Fe concentrations using X-ray Fluorescence (XRF) to assess body Fe levels. A portable XRF instrument based on a silicon drift detector has been developed. The instrument was calibrated using water-based phantoms, achieving a minimum detection limit of 1.35 ± 0.35 ppm (Fe) with a measurement time of 1800 s and a radiation dose of 1.1 ± 0.1 mSv to the skin surface. The system accuracy was tested by measuring the skin Fe concentrations in 10 pig skin samples that were not loaded with Fe. The measured pig skin Fe ranged from approximately 8 to 14 ppm with an average value of 11 ppm. The XRF measurements were found to compare well with the results from Inductively Coupled Plasma Mass Spectroscopy (ICP-MS) analysis of the same skin samples. The mean difference between the Fe levels as assessed by XRF and ICP-MS was not significant, measuring at 2.5 ± 4.6 ppm. Synchrotron µXRF mapping of 25 μm thick pig skin sections at a spatial resolution of 20 µm revealed Fe ‘hot spots’ through the skin, predominantly in the dermis, that were attributed to small blood vessels. The synchrotron map also showed that the Fe distribution in the skin peaks near the outer skin surface. Measurements by the system of this skin distribution were modelled using the Monte Carlo code EGS5 and indicated that if a highly elevated Fe layer is present at the surface, correction factors may be necessary for accurate estimation of skin surface Fe levels by the XRF system. The performance of the system was tested using rat skin samples obtained from animals dosed in vivo with varying amounts of Fe. The system was able to distinguish between skin samples from normal rats and rats dosed with 80 mg Fe2+ and between rats dosed with 80 mg Fe2+ and 160 mg Fe2+ (p = 0.001 and p=0.002, respectively). The instrument also exhibited a significant linear relationship between the measured rat skin Fe concentration and rat Fe dose (R2 = 0.84, p < 0.0001). Furthermore, the measurements were validated against a laboratory XRF system, a bulk tissue measurement system (R2 = 0.85, p < 0.0001). Overall, the work in this thesis highlights the promise of using portable XRF for precise and non-intrusive measurement of skin Fe levels in both Fe overload and Fe deficiency conditions.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 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) | 0.002 | 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".