STUDIES TO IMPROVE THE IN VIVO MEASUREMENT OF STRONTIUM BY X-RAY FLUORESCENCE
Bibliographic record
Abstract
Strontium is a rare earth element, present in products such as pyrotechnics, medications, glass and certain pigments. Exposure of humans to strontium mainly comes through dietary means, through the consumption of food and water. While high levels of strontium have been shown to be toxic in animal studies, low levels may be beneficial, such as for the treatment of osteoporosis. Some women in Canada choose to self-supplement with strontium with the intention of preventing this bone disease. At present, there is no clinical tool to monitor strontium levels in these women. A technology that could montior women would be useful as it would allow the determination of whether the self-supplementation is indeed beneficial. To measure strontium in humans, a non-invasive, non-destructive technique called X-ray fluorescence (XRF) is used. This thesis describes work to develop improved technology for in vivo measurements of strontium in bone using XRF. A new XRF system for measuring strontium in bone was designed around a VITUS H150 Silicon Drift Detector (SDD) from KETEK GmbH, and used a 109Cd source in a 180º backscatter geometry. The system was calibrated against a series of anthropomorphic finger phantoms which were 3D printed with a strontium doped hydroxyapatite core and varying polylactic acid (PLA) thicknesses to simulate different thicknesses of soft tissue. Phantoms with a range range of strontium concentrations were created to test the system. It was determined that the new system was able to perform as well as previously tested radioisotope-based in vivo strontium XRF systems, with the system having the potential to perform significantly better if a significantly more active source could be employed. Calibration using the 3D printed phantoms was also found to perform extremely well, indicating that this phantom methodology is a viable way to make more anatomically correct calibration phantoms in the future. A Monte Carlo model was created in the EGS 5 code of the experimental geometry and the model performance was benchmarked against experimental data. This model was then used to test two separate issues. First, the model was used to determine the validity of coherent normalization for in vivo strontium measurements in the finger. Second, the model was used to determine if there was a radioisotope source that could result in better performance of the system. The coherent normalization was shown to not be valid in terms of correction for soft tissue attenuation, but may be valid as a correction method for errors in positioning or patient motion. In combination with a new Compton correlation method that can estimate the thickness of overlying soft tissue, the implementation of coherent normalization would reduce variability in the system’s measurements of the strontium signal. Finally, through the testing of alternative radioisotope sources, 103Pd was identified as a promising alternative source of fluorescing photons and it is recommended that an experimental XRF system employing this source be tested to verify this result.
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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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".