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Studies of optimization methods for dose delivery
with a beam scanning system
Alexei Trofimov, Thomas BortfeldNortheast Proton Therapy Center
MGH, Boston
Alexei Trofimov XXXVI PTCOG
Beam scanning at the NPTC
First tests have been conducted in collaboration with IBA last week
Use the IBA scanning system for delivery
Inverse treatment planning with KonRad (DKFZ)
Alexei Trofimov XXXVI PTCOG
Treatment planning and delivery
For each layer w/in target, treatment planning system generates a discrete beam weight map for regularly spaced pencil beam spots Scanning within a layer is continuous Fluence variation along
the path is achieved by simultaneously varying the beam current and scanning speed
Alexei Trofimov XXXVI PTCOG
Example: plan for a NPTC patient (medulloblastoma, 3D plan with 2cm-FWHM
beam)
boost
sp.cord
target
hypoth.
cochlea
Alexei Trofimov XXXVI PTCOG
Example: plan for a NPTC patient (RPO field, spot spacing = = 8.5 mm)
beam weight map dose distribution at B.p. range
Alexei Trofimov XXXVI PTCOG
Converting a discrete spectrum into a continuous one
vector approximation Triangular approximation
Alexei Trofimov XXXVI PTCOG
Difference between planned and delivered doses
Along a scanning path element, delivered dose has pseudo-gaussian profile, different from the planned gaussian spot
Alexei Trofimov XXXVI PTCOG
Calculated dose difference (vector approximation)
Alexei Trofimov XXXVI PTCOG
Difference between the planned and delivered doses
The discrepancy is maximal in the regions of sharp dose gradient
(rim of the target, boost) Size of the discrepancy depends on TPS spot spacing (, range of variation in the weight map, scanning path. Generally, smaller for finer / values
Alexei Trofimov XXXVI PTCOG
Spot weight optimizationPlanned dose (conv. of TPS weight map with a gaussian)
DTPS = WTPS g()Iteration #i: Delivered dose (convolution with a pseudo-gaussian)
Di = Wi [ g() f() ]; f= or Optimized beam weight map for spots at (x,y):
Wi+1 (x,y) = Wi(x,y)*[DTPS(x,y)/Di(x,y)]
Alexei Trofimov XXXVI PTCOG
Results of the optimizationstart 1 iteration
10 iterations
100 iterations
Alexei Trofimov XXXVI PTCOG
Results of the optimization
f(i)= (x,y) [ ( Di - DTPS)2 / DTPS ]
Alexei Trofimov XXXVI PTCOG
Optimization for a quasi-continuous path:
W0 = WTPS f(); f = or
Iteration # i:
Delivered dose: Di = Wi g()Optimized beam weight for a quasi-continuous set of
points (x,y) along the scanning path:
Wi+1 (x,y) = Wi(x,y)*[DTPS(x,y)/Di(x,y)]
Alexei Trofimov XXXVI PTCOG
Results of the optimization
For a quasi-continuous weight variation along the path
20 iterations
start
Alexei Trofimov XXXVI PTCOG
Optimization results for one scanning line
Alexei Trofimov XXXVI PTCOG
Another example: PA field
-vector approximation optimized (100 iterations)
Alexei Trofimov XXXVI PTCOG
Another example: LPO field
-vector approximation optimized (100 iterations)
Alexei Trofimov XXXVI PTCOG
Another example: spacing
1.5*
-vector approximation optimized (100 iterations)
Alexei Trofimov XXXVI PTCOG
Results of the optimization
Spot
spacing ()
Maximal dose difference (%)
Before optimization
Optimized
on target penumbra
0.5 * < 1 0.1 0.3
0.75 * 1.5 0.3 0.7
1.0 * 2.5 0.5 1.2
1.25 * 3.5 1 2.5
1.5 * 6 1.5 4
2.0 * 10 4 8
Alexei Trofimov XXXVI PTCOG
Summary
Simulation shows that a good dose conformity can be achieved by optimizing the TPS beam weight maps discrepancy reduced 3-fold on the target, 2-
fold in the penumbra (from 1-6%) no need to use finer grid
Plan to verify the results with the beam