This research project, funded by the Wellcome Foundation, is applying knowledge from Monte Carlo simulations of detectors used in High Energy Physics to the field of radiation biology, specifically to answer questions about normal tissue injury by radiation. GEANT is one of these software tools developed at CERN.
More precisely, we aim to use GEANT to simulate the deposition of radiation doses delivered to the patient body during a radiotherapy treatment plan.
Radiotherapy is used to treat cancerous tumours by firing particle beams at them, called treatment beams. The type of particle beam used depends on the location and size of the tumour to be treated. A complete radiotherapy plan can take several days and applies the treatment beams in several fractions. Medical imaging is used to follow the evolution of the tumour and its response to treatment, and this sometimes involves X-rays.
Although the integrated dose of a single X-ray (~ 0.1-5 cGy) is much smaller than the dose delivered by the treatment beam to the tumour area (~ 50-80 Gy, depending on the area treated), the treatment beam is much more localised, so the contribution of the doses accrued during the imaging sessions of the treatment must be taken into account as some areas of the patient body spared by the treatment beam will be affected by the X-ray imaging session.
Simulation of Radiotherapy machines
The project is a collaboration between the High Energy Physics and the Oncology groups of the University of Cambridge. The Oncology group, based at the Cambridge University Hospital of Addenbrooke's uses two radiotherapy machines for treatment and diagnostic:
- the Elekta "Agility" machine
- the TomoTherapy "Hi-Art" machine
Both machines are capable of producing both treatment beams and diagnostic X-rays in the MeV range. The Elekta "Agility" machine also provides a keV X-ray diagnostic arm, independent from the MeV beam apparatus.
Simulated Human Bodies (phantoms) and Dose Maps
We use full body CT scans from the patient to develop a realistic voxel model of his body. Each voxel is allocated the density and atomic composition of the body tissue it contains, using a conversion scale from Hounsfield Units from the CT scan to density values, then map the density to the related tissue. As one can see in Figure 1, the machine's bed is also contained in the CT scan, and is therefore part of the voxel model. A distinct list of materials is used to describe the bed voxels, which are identified by simple geometric considerations.