Ocampo, Jeremy;
Heyes, Geoff;
Dehghani, Hamid;
Scanlon, Tim;
Jolly, Simon;
Gibson, Adam P;
(2024)
Determination of output factor for CyberKnife using scintillation dosimetry and deep learning.
Physics in Medicine & Biology
, 69
(2)
, Article 025024. 10.1088/1361-6560/ad1b69.
Preview |
PDF
Ocampo_2024_Phys._Med._Biol._69_025024.pdf - Published Version Download (3MB) | Preview |
Abstract
OBJECTIVE: Small-field dosimetry is an ongoing challenge in radiotherapy quality assurance especially for radiosurgery systems such as CyberKnifeTM. The objective of this work is to demonstrate the use of a plastic scintillator imaged with a commercial camera to measure the output factor of a CyberKnife system. The output factor describes the dose on the central axis as a function of collimator size, and is a fundamental part of CyberKnife quality assurance and integral to the data used in the treatment planning system. APPROACH: A self-contained device consisting of a solid plastic scintillator and a camera was build in a portable Pelicase. Photographs were analysed using classical methods and with convolutional neural networks to predict beam parameters which were then compared to measurements. MAIN RESULTS: Initial results using classical image processing to determine standard quality assurance parameters such as percentage depth dose were unsuccessful, with 34% of points failing to meet the Gamma criterion (which measures the distance between corresponding points and the relative difference in dose) of 2mm/2%. However, when images were processed using a convolutional neural network trained on simulated data and a green scintillator sheet, 92% of percentage depth dose curves agreed with measurements with a microdiamond detector to within 2mm/2% and 78% to 1%/1mm. The mean difference between the output factors measured using this system and a microdiamond detector was 1.1%. Confidence in the results was enhanced by using the algorithm to predict the known collimator sizes from the photographs which it was able to do with an accuracy of less than 1 mm. SIGNIFICANCE: With refinement, a full output factor curve could be measured in less than an hour, offering a new approach for rapid, convenient small-field dosimetry.
| Type: | Article |
|---|---|
| Title: | Determination of output factor for CyberKnife using scintillation dosimetry and deep learning |
| Location: | England |
| Open access status: | An open access version is available from UCL Discovery |
| DOI: | 10.1088/1361-6560/ad1b69 |
| Publisher version: | http://dx.doi.org/10.1088/1361-6560/ad1b69 |
| Language: | English |
| Additional information: | Original content from this work may be used under the terms of the CreativeCommons Attribution 4.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. |
| Keywords: | cyberknife, deep learning, output factor, photography, small field dosimetry, solid plastic scintillator |
| UCL classification: | UCL UCL > Provost and Vice Provost Offices > UCL BEAMS UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Med Phys and Biomedical Eng UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Maths and Physical Sciences > Dept of Physics and Astronomy |
| URI: | https://discovery.ucl.ac.uk/id/eprint/10186168 |
Archive Staff Only
 |
View Item |
