Standardizing SPECT/CT dosimetry following radioembolization with yttrium-90 microspheres
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Notice bibliographique
Résumé
BACKGROUND: Multiple post-treatment dosimetry methods are currently under investigation for Yttrium-90 ([Formula: see text]) radioembolization. Within each methodology, a variety of dosimetric inputs exists that affect the final dose estimates. Understanding their effects is essential to facilitating proper dose analysis and crucial in the eventual standardization of radioembolization dosimetry. The purpose of this study is to investigate the dose differences due to different self-calibrations and mass density assignments in the non-compartmental and local deposition methods. A practical mean correction method was introduced that permits dosimetry in images where the quality is compromised by patient motion and partial volume effects. METHODS: Twenty-one patients underwent [Formula: see text] radioembolization and were imaged with SPECT/CT. Five different self-calibrations (FOV, Body, OAR, Liverlung, and Liver) were implemented and dosimetrically compared. The non-compartmental and local deposition method were used to perform dosimetry based on either nominal- or CT calibration-based mass densities. A mean correction method was derived assuming homogeneous densities. Cumulative dose volume histograms, linear regressions, boxplots, and Bland Altman plots were utilized for analysis. RESULTS: Up to 270% weighted dose difference was found between self-calibrations with mean dose differences up to 50 Gy in the liver and 23 Gy in the lungs. Between the local deposition and non-compartmental methods, the liver and lung had dose differences within 0.71 Gy and 20 Gy, respectively. The local deposition method's nominal and CT calibration-based mass density implementations dosimetric metrics were within 1.4% in the liver and 24% in the lungs. The mean lung doses calculated with the CT method were shown to be inflated. The mean correction method demonstrated that the corrected mean doses were greater by up to [Formula: see text] Gy in the liver and lower by up to [Formula: see text] Gy in the lungs. CONCLUSIONS: The OAR calibration may be utilized as a potentially more accurate and precise self-calibration. The non-compartmental method was found more comparable to the local deposition method in organs that were more homogeneous in mass densities. Due to the potential for inflated lung mean doses, the non-compartmental and local deposition method implemented with nominal mass densities is recommended for more consistent dosimetric results. If patient motion and partial volume effects are present in the liver, our practical correction method will calculate more representative doses in images suboptimal for dosimetry.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 découle