Verification of the Collapsed Cone algorithm using a 3D printed phantom with varying densities

Abstract

The purpose of the study was to test the feasibility of using 3D printing technology to create an inhomogeneous phantom for the verification of the Collapsed Cone algorithm. Using software and CT images of a patient, a soft-tissue model of a thorax was designed and then printed using a 3D printer. To represent vertebra, spinal cord and lung tissue, modelling clay, wax and foam were used, respectively. A lung tumour was replicated by using a ball of wax placed in the lung close to the heart. CT images of the phantom showed that the materials used created the desired density profile of soft-, bone- and lung-tissue. The phantom was CT scanned and dose plans were deigned, which were then delivered to the phantom using 6 MV photon beam. The delivered dose was measured using Gafchromic EBT3 film. The plans were constructed using the Pencil Beam (PB) algorithm and then recalculated using the same monitor units with the Collapsed Cone (CC) algorithm. Using gamma analysis it was shown that the CC algorithm was more accurate at calculating the dose delivered to the phantom then the PB algorithm. Therefore, the study showed that is possible to use 3D printed material for creating an inhomogeneous phantom for dosimetric verification of radiotherapy treatment planning systems. With further work in 3D printed phantom construction it would be possible to use patient specific 3D printed phantoms for end-to-end testing and be designed to hold dosimeters specified by the medical physic. The purpose of the study was to test the feasibility of using 3D printing technology to create an inhomogeneous phantom for the verification of the Collapsed Cone algorithm. Using software and CT images of a patient, a soft-tissue model of a thorax was designed and then printed using a 3D printer. To represent vertebra, spinal cord and lung tissue, modelling clay, wax and foam were used, respectively. A lung tumour was replicated by using a ball of wax placed in the lung close to the heart. CT images of the phantom showed that the materials used created the desired density profile of soft-, bone- and lung-tissue. The phantom was CT scanned and dose plans were deigned, which were then delivered to the phantom using 6 MV photon beam. The delivered dose was measured using Gafchromic EBT3 film. The plans were constructed using the Pencil Beam (PB) algorithm and then recalculated using the same monitor units with the Collapsed Cone (CC) algorithm. Using gamma analysis it was shown that the CC algorithm was more accurate at calculating the dose delivered to the phantom then the PB algorithm. Therefore, the study showed that is possible to use 3D printed material for creating an inhomogeneous phantom for dosimetric verification of radiotherapy treatment planning systems. With further work in 3D printed phantom construction it would be possible to use patient specific 3D printed phantoms for end-to-end testing and be designed to hold dosimeters specified by the medical physic.