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Comparison of Prospectively Generated Glioma Treatment Plans Clinically Delivered on Magnetic Resonance Imaging (MRI)-Linear Accelerator (MR-Linac) Versus Conventional Linac: Predicted and Measured Skin Dose
- Source :
- Technology in Cancer Research & Treatment, Vol 21 (2022)
- Publication Year :
- 2022
- Publisher :
- SAGE Publishing, 2022.
-
Abstract
- Introduction: Magnetic resonance imaging-linear accelerator radiotherapy is an innovative technology that requires special consideration for secondary electron interactions within the magnetic field, which can alter dose deposition at air–tissue interfaces. As part of ongoing quality assurance and quality improvement of new radiotherapy technologies, the purpose of this study was to evaluate skin dose modelled from the treatment planning systems of a magnetic resonance imaging-linear accelerator and a conventional linear accelerator, and then correlate with in vivo measurements of delivered skin dose from each linear accelerator. Methods: In this prospective cohort study, 37 consecutive glioma patients had treatment planning completed and approved prior to radiotherapy initiation using commercial treatment planning systems: a Monte Carlo-based algorithm for magnetic resonance imaging-linear accelerator or a convolution-based algorithm for conventional linear accelerator. In vivo skin dose was measured using an optically stimulated luminescent dosimeter. Results: Monte Carlo-based magnetic resonance imaging-linear accelerator plans and convolution-based conventional linear accelerator plans had similar dosimetric parameters for target volumes and organs-at-risk. However, magnetic resonance imaging-linear accelerator plans had 1.52 Gy higher mean dose to air cavities ( P
- Subjects :
- Neoplasms. Tumors. Oncology. Including cancer and carcinogens
RC254-282
Subjects
Details
- Language :
- English
- ISSN :
- 15330338
- Volume :
- 21
- Database :
- Directory of Open Access Journals
- Journal :
- Technology in Cancer Research & Treatment
- Publication Type :
- Academic Journal
- Accession number :
- edsdoj.3146416a09f4c51b306a2000491e375
- Document Type :
- article
- Full Text :
- https://doi.org/10.1177/15330338221124695