Quantitative PET Comparing Gated with Nongated Acquisitions Using a NEMA Phantom with Respiratory-Simulated Motion
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Résumé
UNLABELLED: This study evaluated the use of gated versus nongated PET acquisitions for absolute quantification of radioisotope concentration (RC) in a respiratory motion-simulated moving phantom filled with radioactive spheres and background for both 2-dimensional (2D) and 3-dimensional (3D) acquisitions. METHODS: An image-quality phantom with all 6 spheres filled with the same (18)F RC (range, 19-62 kBq/mL) was scanned with PET/CT at rest and in motion with and without gating. The background was filled with (18)F solution to yield sphere-to-background ratios of approximately 5, 10, 15, and 20 to 1. Both 2D and 3D acquisitions were used for all combinations. Respiratory motion was simulated by using a motor-driven plastic platform to move the phantom periodically with a displacement of 2 cm and a cycle time of 5.8 s. For gated acquisitions, the phantom was tracked using a real-time position management system. Images were reconstructed, and regions of interest with the same sizes as the actual spheres were manually placed on axial slices to determine maximum and mean pixel RC. A threshold method (70% and 94% for 2D and 3D modes) was also used to determine a mean voxel RC. All values were compared with the expected RC; percentage differences were calculated for each sphere. To reduce partial-volume effects, only data for the 4 largest spheres were analyzed. RESULTS: The mean pixel method was the only method with linear responses for all 3 scan types, enabling direct comparisons. The ranges of RC percentage differences were underestimated for all scan types (using the mean pixel method). The overall mean percentage differences were 37, 49, and 41 in 2D mode and 40, 51, and 41 in 3D mode for static, nongated, and gated acquisitions, respectively. Gated acquisitions improved quantification (by reducing underestimation) over nongated acquisitions by 8% and 10% for 2D and 3D modes. CONCLUSION: In the presence of motion, the use of gated PET acquisitions appears to improve quantification accuracy over nongated acquisitions, almost restoring the results to those observed when the phantom is static.
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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 | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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