A 3D printed modular phantom for quality assurance of image‐guided small animal irradiators: Design, imaging experiments, and Monte Carlo simulations
Notice bibliographique
Résumé
PURPOSE: The goal of this work was to develop and test a cylindrical tissue-equivalent quality assurance (QA) phantom for micro computed tomography (microCT) image-guided small animal irradiators that overcomes deficiencies of existing phantoms due to its mouse-like dimensions and composition. METHODS: The 8.6-cm-long and 2.4-cm-diameter phantom was three-dimensionally (3D) printed out of Somos NeXt plastic on a stereolithography (SLA) printer. The modular phantom consisted of four sections: (a) CT number evaluation section, (b) spatial resolution with slanted edge (for the assessment of longitudinal resolution) and targeting section, (c) spatial resolution with hole pattern (for the assessment of radial direction) section, and (d) uniformity and geometry section. A Python-based graphical user interface (GUI) was developed for automated analysis of microCT images and evaluated CT number consistency, longitudinal and radial modulation transfer function (MTF), image uniformity, noise, and geometric accuracy. The phantom was placed at the imaging isocenter and scanned with the small animal radiation research platform (SARRP) in the pancake geometry (long axis of the phantom perpendicular to the axis of rotation) with a variety of imaging protocols. Tube voltage was set to 60 and 70 kV, tube current was set to 0.5 and 1.2 mA, voxel size was set to 200 and 275 μm, imaging times of 1, 2, and 4 min were used, and frame rates of 6 and 12 frames per second (fps) were used. The phantom was also scanned in the standard (long axis of the phantom parallel to the axis of rotation) orientation. The quality of microCT images was analyzed and compared to recommendations presented in our previous work that was derived from a multi-institutional study. Additionally, a targeting accuracy test with a film placed in the phantom was performed. MicroCT imaging of the phantom was also simulated in a modified version of the EGSnrc/DOSXYZnrc code. Images of the resolution section with the hole pattern were acquired experimentally as well as simulated in both the pancake and the standard imaging geometries. The radial spatial resolution of the experimental and simulated images was evaluated and compared to experimental data. RESULTS: For the centered phantom images acquired in the pancake geometry, all imaging protocols passed the spatial resolution criterion in the radial direction (>1.5 lp/mm @ 0.2 MTF), the geometric accuracy criterion (<200 μm), and the noise criterion (<55 HU). Only the imaging protocol with 200-μm voxel size passed the criterion for spatial resolution in the longitudinal direction (>1.5 lp/mm @ 0.2 MTF). The 70-kV tube voltage dataset failed the bone CT number consistency test (<55 HU). Due to cupping artifacts, none of the imaging protocols passed the uniformity test of <55 HU. When the phantom was scanned in the standard imaging geometry, image uniformity and longitudinal MTF were satisfactory; however, the CT number consistency failed the recommended limit. A targeting accuracy of 282 and 251 μm along the x- and z-direction was observed. Monte Carlo simulations confirmed that the radial spatial resolution for images acquired in the pancake geometry was higher than the one acquired in the standard geometry. CONCLUSIONS: The new 3D-printed phantom presents a useful tool for microCT image analysis as it closely mimics a mouse. In order to image mouse-sized animals with acceptable image quality, the standard protocol with a 200-μm voxel size should be chosen and cupping artifacts need to be resolved.
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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,001 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 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 ».