Temporal separation of Cerenkov radiation and scintillation using artificial neural networks in Clinical LINACs

• DOI: 10.1016/j.ejmp.2018.10.007
• Publication Date: 2018-10-10T14:14:59Z
• Authors: Levi Madden; James Archer; Enbang Li; Dean Wilkinson; Anatoly Rosenfeld
• Keywords: Time Factors; Science and Technology Studies; 03 medical and health sciences; Engineering; 0302 clinical medicine; Humans; Scintillation Counting; Neural Networks, Computer; Particle Accelerators; Radiometry; Optical Fibers; Software

The irradiation of scintillator-fiber optic dosimeters by clinical LINACs results in the measurement of scintillation and Cerenkov radiation. In scintillator-fiber optic dosimetry, the scintillation and Cerenkov radiation responses are separated to determine the dose deposited in the scintillator volume. Artificial neural networks (ANNs) were trained and applied in a novel single probe method for the temporal separation of scintillation and Cerenkov radiation. Six dose profiles were measured using the ANN, with the dose profiles compared to those measured using background subtraction and an ionisation chamber. The average dose discrepancy of the ANN measured dose was 2.2% with respect to the ionisation chamber dose and 1.2% with respect to the background subtraction measured dose, while the average dose discrepancy of the background subtraction dose was 1.6% with respect to the ionisation chamber dose. The ANNs performance was degraded when compared with background subtraction, arising from an inaccurate model used to synthesise ANN training data.