I have a medical physics problem - I want to maximise the dose absorbed by a brain tumour whilst minimising the dose in the rest of the brain, especially certain organs, such as the pituitary gland, optic nerves and cochlea (organs at risk, OAR).
The dose is delivered by syringes which have 3 different entry points, placing spheres of radiation within the tumour along their paths (imagine the syringes create a cylinder in which the spheres are placed, so I will have 3 cylinders containing spheres of radiation).
So, my goal function :
- a target absorbed dose and homogeneity for the tumour
- minimise absorbed dose for OAR (with an absolute upper limit)
- minimise absorbed dose for normal brain tissue (with upper limit that is lower than for the OAR)
And the variables I can change include:
- Entry points of syringes
- Directions of syringes
- Where to place spheres along the syringe's path (spacing along the cylinder)
- At some later point, I would like to implement variable sphere size between a minimum and maximum volume, but for now I'll keep it simple...
I am completely new to inverse problem solving algorithms and am at a complete loss as to where to start looking for answers. Any help or pointers towards good material to read would be greatly appreciated.
EDIT: I should have mentioned that the spheres emit almost purely beta radiation.