A Validation Method for EPID In Vivo Dosimetry Algorithms
| Title: | A Validation Method for EPID In Vivo Dosimetry Algorithms |
|---|---|
| Authors: | Marco Esposito, Livia Marrazzo, Eleonora Vanzi, Serenella Russo, Stefania Pallotta, Cinzia Talamonti |
| Source: | Applied Sciences, Vol 11, Iss 22, p 10715 (2021) |
| Publisher Information: | MDPI AG, 2021. |
| Publication Year: | 2021 |
| Collection: | LCC:Technology LCC:Engineering (General). Civil engineering (General) LCC:Biology (General) LCC:Physics LCC:Chemistry |
| Subject Terms: | in vivo dosimetry, EPID, end-to-end test, anthropomorphic phantom, Technology, Engineering (General). Civil engineering (General), TA1-2040, Biology (General), QH301-705.5, Physics, QC1-999, Chemistry, QD1-999 |
| More Details: | The aim of this study was to develop and apply an evaluation method for assessing the accuracy of a novel 3D EPID back-projection algorithm for in vivo dosimetry. The novel algorithm of Dosimetry Check (DC) 5.8 was evaluated. A slab phantom homogeneously filled, or with air and bone inserts, was used for fluence reconstruction of different squared fields. VMAT plans in different anatomical sites were delivered on an anthropomorphic phantom. Dose distributions were measured with radiochromic films. The 2D Gamma Agreement Index (GAI) between the DC and the film dose distributions (3%, 3 mm) was computed for assessing the accuracy of the algorithm. GAIs between films and TPS and between DC and TPS were also computed. The fluence reconstruction accuracy was within 2% for all squared fields in the three slabs’ configurations. The GAI between the DC and the film was 92.7% in the prostate, 92.9% in the lung, 96.6% in the head and the neck, and 94.6% in the brain. An evaluation method for assessing the accuracy of a novel EPID algorithm was developed. The DC algorithm was shown to be able to accurately reconstruct doses in all anatomic sites, including the lung. The methodology described in the present study can be applied to any EPID back-projection in vivo algorithm. |
| Document Type: | article |
| File Description: | electronic resource |
| Language: | English |
| ISSN: | 2076-3417 21734895 |
| Relation: | https://www.mdpi.com/2076-3417/11/22/10715; https://doaj.org/toc/2076-3417 |
| DOI: | 10.3390/app112210715 |
| Access URL: | https://doaj.org/article/a72670be21734895998a2df0978e1ed9 |
| Accession Number: | edsdoj.72670be21734895998a2df0978e1ed9 |
| Database: | Directory of Open Access Journals |
| ISSN: | 20763417 21734895 |
|---|---|
| DOI: | 10.3390/app112210715 |
| Published in: | Applied Sciences |
| Language: | English |