MR‐linac daily semi‐automated end‐to‐end quality control verification
Notice bibliographique
Résumé
PURPOSE: Adaptive radiation therapy (ART) on the integrated Elekta Unity magnetic resonance (MR)-linac requires routine quality assurance to verify delivery accuracy and system data transfer. In this work, our objective was to develop and validate a novel automated end-to-end test suite that verifies data transfer between multiple software platforms and quantifies the performance of multiple machine subcomponents critical to the ART process. METHODS: We designed and implemented a software tool to quantify the MR and megavoltage (MV) isocenter coincidence, treatment couch positioning consistency, isocenter shift accuracy for the adapted plan as well as the MLC and jaw position accuracy following the beam aperture adaptation. Our tool employs a reference treatment plan with a simulated isocenter shift generated on an MR image of a readily available phantom with MR and MV visible fiducials. Execution of the test occurs within the standard adapt-to-position (ATP) clinical workflow with MV images collected of the delivered treatment fields. Using descriptive statistics, we quantified uncertainty in couch positioning, isocentre shift as well as the jaw and MLC positions of the adapted fields. We also executed sensitivity measurements to evaluate the detection algorithm's performance. RESULTS: We report the results of 301 daily testing instances. We demonstrated consistent tracking of the MR-to-MV alignment with respect to the established value and to detect small changes on the order of 0.2 mm following machine service events. We found couch position consistency relative to the test baseline value was within 95% CI [-0.31, 0.26 mm]. For phantom shifts that form the basis for the plan adaptation, we found agreement between MV-image-detected phantom shift and online image registration, within ± 1.5 mm in all directions with a 95% CI difference of [-1.29, 0.79 mm]. For beam aperture adaptation accuracy, we found differences between the planned and detected jaw positions had a mean value of 0.27 mm and 95% CI of [-0.29, 0.82 mm] and -0.17 mm and 95% CI of [-0.37, 0.05 mm] for the MLC positions. Automated fiducial detected accuracy was within 0.08 ± 0.20 mm of manual localization. Introduced jaw and MLC position errors (1-10 mm) were detected within 0.55 mm (within 1 mm for 15/256 instances for the jaws). Phantom shifts (1.3 or 5 mm in each cardinal direction) from a reference position were detected within 0.26 mm. CONCLUSIONS: We have demonstrated the accuracy and sensitivity of a daily end-to-end test suite capable of detecting errors in multiple machine subcomponents including system data transfer. Our test suite evaluates the entire treatment workflow and has captured system communication issues prior to patient treatment. With automated processing and the use of a standard vendor-provided phantom, it is possible to expand to other Unity sites.
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 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 | 0,003 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 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 | 0,001 | 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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, 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 ».