1. Optimisation of Irradiation Directions in IMRT Planning Rick Johnston Matthias Ehrgott Department of Engineering Science University of Auckland M. Ehrgott, R. Johnston Optimisation of Irradiation Directions in IMRT Planning, OR Spectrum 25(2):251-264, 2003
21. Comparison Objective 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 Problem 1 3 heads Problem 1 4 heads Problem 2 3 heads Problem 2 4 heads Problem 3 3 heads Set Covering LP relaxation Local Search Mixed Integer
22. Objective vs. Time Objective 0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0 2000 4000 6000 8000 10000 12000 Time (s) Local search improvement Set Covering Local Search LP relaxation Mixed Integer
Hinweis der Redaktion
Welcome. Name, supervisor, conjunction with Auckland Hospital.
Contrary public opinion, radiotherapy nothing do with radios. Three Treatments for cancer, local to area. Successful 60%, non-metastastised localised cancers. What going talk about today
Starship Enterprise. Machine, bed interaction. Gantry turns. Number of Irradiation Directions. Auckland Hospital; welcome! Long setup times.
Represents 2-d version what just saw. Bixels â intensity across the beam. Voxels, break up body into homogeneous segments. LP formulation, specify maximum dose to healthy organs, min dose tumour
Creates linear problem from high-dimensional multi-extremal non-linear optimisation. (CLICK) Number of positions used picked by planners (say three). Large no. of LPs. Better approach than other papers in field.
Two main approaches.
MIP: each possible angle has a boo var associated. Allow only fixed number of boo variables be âonâ then solve. Problems. Very slow improve on initial solution. Failed find feasible integer solution in difficult problems. Priority list, improved search techniques (no time)
Set is the volume of the tumour, aim to cover tumour with radiation. Aim: replicate planner decision strategies. Aim for gaps. Results: good for low number of insertion points. Generalised SC and Distribution methods.
Phase 1: allow irradiation from any number of directions Phase 2: use heuristics to consider only a few of these directions. Includes Local Search