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Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation Oncology Stanford University School of Medicine Stanford, CA 94305-5304

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Page 1: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Incorporating Prior Knowledge into IMRT Beam Orientation Optimization

Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation OncologyStanford University School of MedicineStanford, CA 94305-5304

Page 2: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

180o

300o

340o

20o

60o

100o

140o

260o

220o

9-field head and neck Treatment

Fixed gantry IMRT

C e n t e r

Page 3: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

• Number and incident directions of beams• Beam modality • Beamlet weights

Things need to be optimized

Page 4: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Beam orientation optimization

• Clinically, beam orientations are selected empirically.

• Excessive computational time is required for full beam orientation optimization.

20c

Nn

1n

(n)]D(n)[DrF −= ∑=

Dc(n) --- function of beamlet weights, beam orientation.

Page 5: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation
Page 6: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Beam orientation optimization

• More intelligent and less computationally intensive methods of beam orientation selection are needed.

Page 7: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Beam’s-Eye-View Dosemetrics (BEVD) for IMRT Beam Selection

• BEV volumetrics in conventional radiotherapy.

BE

V V

olum

etric

s

Gantry Angle

Only prior geometric information of the system is used.

Page 8: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

• We extend the original BEV to IMRT with consideration of

1. prior geometric and dosimetric information of the system, and

2. beam intensity modulation.

BEVD

Page 9: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Beam’s-Eye-View Dosemetrics (BEVD) for IMRT Beam Selection

• BEVD for IMRT.

90°270°

A Pugachev & L Xing, IJROPB 51, 1361-1370 (2001).

Maximum beam profile

Both prior geometric & dosimetric knowledge of the system are used.

Page 10: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

BEVD

• For each organ at risk (OAR), assign a tolerance dose.

• For every possible beam orientation, calculate single beam dose distribution that can be achieved without exceeding the tolerances of OARs and normal tissue.

Page 11: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

BEVD Calculation

• Divide a beam into bixel map.

• Introduce an empirical score function to evaluate the goodnessof each beamlet/beam.

• Obtain BEVD score for each incident beam direction.

• Select peaks of the BEVD score function, taking into account the principle of maximum beam separation.

• Perform beam intensity profile optimization.

m1 cm

1 cm

Page 12: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

BEVD ranking for an IMRT treatment of paraspinal tumor(Coplanar beam)

• Five beams with high BEVD score.• Selected gantry angles: 225°, 175°, 140°, 85°, 260°

Selectedbeams

Page 13: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

• Selected beams (gantry, table):(180,20) (180,-20) (230,20) (230,-20) (130,0)

Selectedbeams

BEVD ranking for an IMRT treatment of paraspinal tumor(Non-coplanar beam)

Page 14: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Liver

KidneyGTV

35%50%65%80%95%

PBEV Selected Beam Orientations

Beams(gantry,table): (180,20), (180,-20)(230,20), (230,-20) (10,0)

90°

180°

270°

Equiangular Beam Orientations

Gantry angles:40,110,180,255, 325

Page 15: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation
Page 16: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Beam orientation selection

225°(15MV), 180°(6MV), 140°(6MV), 85°(15MV), 260°(15MV)

Selectedbeams

Page 17: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Results

• Nasopharyngeal cancer– BEVD method applied to the selection of coplanar

beams

Page 18: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Cord

GTV35%50%65%80%95%

Dose distribution of two-stage optimization0°

90°

180°

270°

Page 19: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

(b)

(a)

Fig. 2

Page 20: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation
Page 21: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Results III

• Model cases – 2D.– Simplified dose model.– beam orientations are selected using BEVD

method.

Page 22: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

OAR3 OAR3

OAR1

OAR2

90°PTV

OAR1

OAR2

90°PTV

Dose distribution of five IMRT beams selected with BEVD

Tolerance: 0.8

0.1

0.3

Page 23: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Dose

Vol

ume,

%

PTVOAR3

EquiangularBEVD selected

Page 24: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

OAR

0° 0°

90°

PTV

OAR90°

PTV

Dose distribution of five IMRT beams selected with BEVD

Equally spaced five beams

Page 25: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

115 145 180 245215

Gantry angle

iS

Page 26: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Dose

Vol

ume,

%

PTV

OAR

EquiangularBEVD-selected

Page 27: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

BEVD-guided beam optimization for IMRT

• In IMRT, the quality of a beam direction can be measured by a BEVD score.

• Select beams with the highest BEVD score, taking into account the angular separation of the beams.

• BEVD is a computer assisting tool, not an automated tool. It can, however, be used as a priori knowledge of the system to improve the beam orientation calculation.

Page 28: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

(b)

(a)

Page 29: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Initial set of beam orientations

Vary a gantry angle randomly

Beam intensity profile optimization

Temperature low enough?

Reduce temperature

Optimized plan

No

Yes

Accept or reject the trial beam configuration based on SA probability

A. Simulated annealing (SA) optimization

Initial set of beam orientations

Vary a gantry angle randomly

Calculate probability of acceptance based on BEVD score

Optimized plan

Accept

RejectAccept or reject trial beam

configuration

B. BEVD-guided simulated annealing optimization

Beam intensity profile optimization

Accept or reject the trial beam configuration based on SA probability

Temperature low enough?

Reduce temperature

No

Yes

BEVD-Guided Beam Orientation Optimization

Page 30: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

95

Liver

GTV

70

Spinal cord Kidney

5030

270°

180°

90°

Page 31: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

BEVD-Guided Beam Orientation Optimization

T=0 With annealing

• Formalism is applicable for functional imaging-guided IMRT.

• BEVD-guided optimization improves convergence behavior of the system.

• Number of iterations is reduced by a factor of 10.

• Results are consistent with BEVD ranking.

• Speed depends weakly on the cooling schedule.

Page 32: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Conclusions

• A practical BEVD tool has been developed for beam orientation selection in IMRT.

• The technique allows one to select beam orientations without paying the excessive computing overhead of computer beam orientation optimization.

• The approach has considerable potential for simplifying the IMRT planning process to maximize the potential of IMRT.

Page 33: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

Conclusions

• Incorporation of prior knowledge significantly improves the calculation: speed and convergence.

• The methodology also applies to the optimization of other system parameters, like beamlet weights.

Page 34: Incorporating Prior Knowledge into IMRT Beam … · Incorporating Prior Knowledge into IMRT Beam Orientation Optimization Lei Xing, Ph.D. and Andrei Pugachev, M.S. Department of Radiation

ACKNOWLEDGEMENTS

S. Crooks, C. Cotrutz, S. Hunjan, J. Lian, D.Y. Yang, A Boyer, Q.T. Le, S.S. Donaldson, S. Hancock, C. King, A. Koong

This work was partially supported by grants from the American Cancer Society, Whitaker Foundation and Department of Defense.