STUDIES TO IMPROVE THE IN VIVO MEASUREMENT OF STRONTIUM BY X-RAY FLUORESCENCE
Notice bibliographique
Résumé
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.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».