Optimization problems in Radiation Therapy and Medical Imaging. Introduc*on
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1 Optimization problems in Radiation Therapy and Medical Imaging ì Introduc*on
2 Introduction Radia%on therapy Treatment planning and delivery
3 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. Images are registered 4. Tumor volume and radiosensi*ve organs are delineated 5. A radiotherapy treatment plan is created physician provides prescrip*on dose treatment planner chooses incident beam direc*ons determines radia*on fields calculates final dose distribu*on physician reviews/approves plan 6. Treatment plan is converted into machine parameters 7. Some QA is performed, dose measurements 8. Treatment starts
4 This class 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. Images are registered 4. Tumor volume and radiosensi*ve organs are delineated 5. A radiotherapy treatment plan is created physician provides prescrip*on dose treatment planner chooses incident beam direc*ons determine radia*on fields calculate final dose distribu*on physician reviews/approves plan 6. Treatment plan is converted into machine parameters 7. Some QA is performed, dose measurements 8. Treatment starts
5 1. Pa*ent is diagnosed 2. CT scan is performed Radiotherapy planning process
6 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) T1 weighted MRI CT
7 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. CT and MRI images are registered transla*on rota*on deforma*on
8 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. CT and MRI images are registered 4. Tumor volume and radiosensi*ve organs are segmented
9 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. CT and MRI images are registered 4. Tumor volume and radiosensi*ve organs are segmented some things can be automated e.g. Lung (great contrast on CT) many organs are hard
10 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. Images are registered 4. Tumor volume and radiosensi*ve organs are delineated 5. A radiotherapy treatment plan is created physician provides prescrip*on dose treatment planner chooses incident beam direc*ons determines radia*on fields calculates final dose distribu*on physician reviews/approves plan
11 Radiotherapy planning process Treatment planning for IMRT Intensity modulated radiotherapy
12 Radiotherapy planning process 1. Pa*ent is diagnosed 2. CT scan is performed (possibly MRI, PET in addi*on) 3. Images are registered 4. Tumor volume and radiosensi*ve organs are delineated 5. A radiotherapy treatment plan is created physician provides prescrip*on dose treatment planner chooses incident beam direc*ons determines radia*on fields calculates final dose distribu*on physician reviews/approves plan 6. Treatment plan is converted into machine parameters 7. Some QA is performed, dose measurements 8. Treatment starts
13 Radiotherapy treatment process 1. Pa*ent enters the treatment room 2. Pa*ent is posi*oned rela*ve to the treatment beam posi*on lasers X- ray imaging fixa*on devises
14 Radiotherapy treatment process 2. Pa*ent is posi*oned rela*ve to the treatment beam 3. Pa*ent is irradiated over 6 weeks / 30 frac*ons Linac
15 Radiotherapy treatment process Cyber knife
16 Adaptive radiotherapy Goal: account for geometric varia*ons of the pa*ent setup error internal inter- frac*on organ mo*on (prostate) intra- frac*on mo*on (respiratory mo*on, lung, liver) 1. Cone beam CT in treatment posi*on 2. Fast CT reconstruc*on 3. Registra*on to planning CT 4. (Automated segmenta*on) 5. Setup correc*on 6. (Treatment plan adapta*on) è ideally, every step should be real *me
17 This class Three blocks 1. CT reconstruc*on 2. Image registra*on and segmenta*on 3. Treatment plan op*miza*on
18 Syllabus 1. Introduc*on / planar CT reconstruc*on (analy*c method) 2. Cone beam CT reconstruc*on (analy*c method) 3. Image registra*on rigid, affine 4. Image registra*on mul*modality 5. Deformable image registra*on 1 6. Deformable image registra*on 2 7. Treatment plan op*miza*on 1 8. Treatment plan op*miza*on 2 9. Treatment planning system demo 10. Adap*ve planning 11. Biological planning 12. TBD
19 CT reconstruction is an inverse problem forward problem (DRR calcula*on) inverse problem (CT reconstruc*on) 3D CT image 2D X- ray images
20 Treatment planning can be viewed as an inverse problem 2D intensity profiles forward problem (dose calcula*on) inverse problem (IMRT planning) 3D dose distribu*on
21 Optimization Op%miza%on is common theme: minimize x f model of the observa*on " i ( f ( x, A ) i! y ) 2 i y observa*on / goal (given) x op*miza*on variables / parameters of the model (to be determined) A problem data (given)
22 Optimization CT reconstruc%on: minimize x f imaging model (physics) ( ) = A i! x f x, A i " i ( f ( x, A ) i! y ) 2 i x CT image (absorp*on coefficient for every voxel) y X- ray images (measured) A problem data (geometry)
23 Optimization Treatment planning: minimize x " i f Dose deposi*on model ( ) = A i! x f x, A i " = A ij! x j j x intensity of radia*on beams ( f ( x, A ) i! y ) 2 i y prescribed dose A pa*ent geometry, beam parameters
24 Optimization Image registra%on: minimize x f coordinate transforma*on func*on " i ( f ( x, A ) i! y ) 2 i x parameters of transforma*on matrix (rota*on, transla*on) y reference image A second image to be registered
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