Patient-specific collision zones for 4π trajectory optimized radiation therapy.
collision detection
extracranial stereotactic/SBRT
noncoplanar VMAT
patient-specific
Journal
Medical physics
ISSN: 2473-4209
Titre abrégé: Med Phys
Pays: United States
ID NLM: 0425746
Informations de publication
Date de publication:
Mar 2022
Mar 2022
Historique:
revised:
19
11
2021
received:
12
08
2021
accepted:
16
12
2021
pubmed:
14
1
2022
medline:
11
3
2022
entrez:
13
1
2022
Statut:
ppublish
Résumé
The 4π methodology determines optimized noncoplanar subarcs for stereotactic radiation therapy that minimize dose to organs-at-risk. Every combination of treatment angle is examined, but some angles are not appropriate as a collision would occur between the gantry and the couch or the gantry and the patient. Those combinations of couch and gantry angles are referred to as collision zones. A major barrier to applying 4π to stereotactic body radiation therapy (SBRT) is the unknown shape of the collision zones, which are significant as patients take up a large volume within the 4π sphere. This study presents a system that determines patient-specific collision zones, without additional clinical steps, to enable safe and deliverable noncoplanar treatment trajectories for SBRT patients. To augment patient's computed tomography (CT) scan, full body scans of patients in treatment position were acquired using an optical scanner. A library of a priori scans (N = 25) was created. Based on the patients' treatment position and their body dimensions, a library scan is selected and registered to the CT scan of the patient. Next, a model of the couch and immobilization equipment is added to the patient model. This results in a patient model that is then aligned with a model of the treatment LINAC in a "virtual treatment room," where both components can be rotated to test for collisions. To test the collision detection algorithm, an end-to-end test was performed using a cranial phantom. The registration algorithm was tested by comparing the registered patient collision zones to those generated by using the patient's matching scan. The collision detection algorithm was found to have a 97.80% accuracy, a 99.99% sensitivity, and a 99.99% negative predictive value (NPV). Analysis of the registration algorithm determined that a 6 cm buffer was required to achieve a 99.65% mean sensitivity, where a sensitivity of unity is considered to be a requirement for safe treatment delivery. With a 6 cm buffer, the mean accuracy was 86.70% and the mean NPV was 99.33%. Our method of determining patient-specific collision zones can be accomplished with minimal user intervention based on an a priori library of body surface scans, thus enabling the safe application of 4π SBRT.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
1407-1416Subventions
Organisme : Atlantic Canada Opportunities Agency
Organisme : Brainlab AG
Informations de copyright
© 2022 American Association of Physicists in Medicine.
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