Investigation of combined <scp>kV</scp>/<scp>MV CBCT</scp> imaging with a high‐<scp>DQE MV</scp> detector
Notice bibliographique
Résumé
PURPOSE: Combined kV-MV cone-beam tomography (CBCT) imaging has been proposed for two potentially important image-guided radiotherapy applications: (a) scan time reduction (STR) and (b) metal artifact reduction (MAR). However, the feasibility of these techniques has been in question due to the low detective quantum efficiencies (DQEs) of commercially available electronic portal imagers (EPIDs). The goal of the work was to test whether a prototype high DQE MV detector can be used to generate acceptable quality pretreatment CBCT images at acceptable dose levels. METHODS: 6MV and 100 kVp projection data were acquired on a Truebeam system (Varian, Palo Alto, CA). The MV data were acquired using a prototype EPID containing two scintillators (a) a standard copper-gadolinium oxysulfide (Cu-GOS) screen having a zero-frequency DQE (DQE(0)) value of 1.4%, and (b) a prototype-focused cadmium tungstate (CWO) pixelated "strip" with a DQE(0) = 22%. The kV data were acquired using the standard onboard imager (DQE(0) = 70%). The angular spacing of the MV projections was 0.81° and the source output was 0.03 MU/projection while the kV projections were acquired with an angular spacing of 0.4° at 0.3 mAs/projection. Image quality was evaluated using (a) an 18-cm diameter electron density phantom (CIRS, Norfolk, VA) with nine contrast inserts and (b) the resolution section of the 20-cm diameter Catphan phantom (The Phantom Laboratory, Greenwich, NY). For the MAR studies, two opposing CIRS phantom inserts were replaced by steel rods. The reconstruction methods were based on combining MV and kV data into one sinogram. The MAR reconstruction utilized mostly kV raw data with only those rays corrupted by metal requiring replacement with MV data (total absorbed dose = 0.7 cGy). For the STR study, projections from partially overlapping 105°kV and MV acquisitions were combined to create a complete dataset that could have been acquired in 18 sec (absorbed dose = 2.5 cGy). MV-only (4.3 cGy) and kV-only (0.3 cGy) images were also reconstructed. RESULTS: The average signal-to-noise ratio (SNR) of the inserts in the MV-only CWO and GOS CIRS phantom images were 0.62× and 0.12× the SNR of the inserts in kV-only image, respectively. The limiting spatial resolutions in the MV-only GOS, MV-only CWO, and kV-only Catphan images were 3, 6, and 8 lp/cm, respectively. In the combined kV/CWO STR reconstruction, all contrast inserts were visible while only two were detectable in the kV/Cu-GOS image due to high levels of noise (average SNRs of kV/CWO and kV/GOS inserts were 0.97× and 0.18× the SNR of the kV-only inserts, respectively). In the kV-MV MAR reconstructions, streaking artifacts were substantially reduced with all inserts becoming clearly visible in the kV/CWO image while only two were visible in the kV/Cu-GOS image (average SNRs of the kV/CWO and kV/Cu-GOS CIRS with metal inserts were 0.94× and 0.35× the SNRs of the kV-only CIRS without metal inserts). CONCLUSIONS: We have demonstrated that a high-DQE MV detector can be applied to generating high-quality combined kV-MV images for SRT and MAR. Clinically acceptable doses were utilized.
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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 | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 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 ».