Biological consequences of MLC calibration errors in IMRT delivery and QA
Notice bibliographique
Résumé
PURPOSE: The purpose of this work is threefold: (1) to explore biological consequences of the multileaf collimator (MLC) calibration errors in intensity modulated radiotherapy (IMRT) of prostate and head and neck cancers, (2) to determine levels of planning target volume (PTV) and normal tissue under- or overdose flagged with clinically used QA action limits, and (3) to provide biologically based input for MLC QA and IMRT QA action limits. METHODS: Ten consecutive prostate IMRT cases and ten consecutive head and neck IMRT cases were used. Systematic MLC offsets (i.e., calibration error) were introduced for each control point of the plan separately for X1 and X2 leaf banks. Offsets were from - 2 to 2 mm with a 0.5 mm increment. The modified files were imported into the planning system for forward dose recalculation. The original plan served as the reference. The generalized equivalent uniform dose (gEUD) was used as the biological index for the targets, rectum, parotid glands, brainstem, and spinal cord. Each plan was recalculated on a CT scan of a 27 cm diameter cylindrical phantom with a contoured 0.6 cc ion chamber. Dose to ion chamber and 3D gamma analysis were compared to the reference plan. QA pass criteria: (1) at least 95% of voxels with a dose cutoff of 50% of maximum dose have to pass at 3 mm/3% and (2) dose to chamber within 2% of the reference dose. RESULTS: For prostate cases, differences in PTV and rectum gEUD greater than 2% were identified. However, a larger proportion of plans leading to greater than 2% difference in prostate PTV gEUD passed the ion chamber QA but not 3D gamma QA. A similar trend was found for the rectum gEUD. For head and neck IMRT, the QA pass criteria flagged plans leading to greater than 4% differences in PTV gEUD and greater than 5% differences in the maximum dose to brainstem. If pass criteria were relaxed to 90% for gamma and 3% for ion chamber QA, plans leading to a 5% difference in PTV gEUD and a 5%-8% difference in brainstem maximum dose would likely pass IMRT QA. A larger proportion of head and neck plans with greater than 2% PTV gEUD difference passed 3D gamma QA compared to ion chamber QA. CONCLUSIONS: For low modulation plans, there is a better chance to catch MLC calibration errors with 3D gamma QA rather than ion chamber QA. Conversely, for high modulation plans, there is a better chance to catch MLC calibration errors with ion chamber QA rather than with 3D gamma QA. Ion chamber and 3D gamma analysis IMRT QA can detect greater than 2% change in gEUD for PTVs and critical structures for low modulation treatment plans. For high modulation treatment plans, ion chamber and 3D gamma analysis can detect greater than 2% change in gEUD for PTVs and a 5% change in critical structure gEUD since either QA methods passes the QA criteria. For gEUD changes less than those listed above, either QA method has the same proportion of passing rate.
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 | 0,000 | 0,000 |
| 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 | 0,000 | 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 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 ».