Robust optimization strategies for lung SBRT

Travis McCaw, PhD, DABRNCCAAPM Spring Meeting

April 26, 2019

photon

Objectives

• Motivation for robust optimization• Approaches to robust optimization• Review of literature on applications of RayStation robust optimization• Phantom-based study of robust optimization in photon lung SBRT

Conventional radiation therapy workflow

• Simulation• Contouring• Treatment planning• Plan review and QA• Treatment

7-10 business days

Potentially > 8 weeks

Treatment uncertainties

• Target segmentation• Weight change• Mechanical uncertainty• Setup error• Intrafraction motion

Treatment uncertainties

• Target segmentation• Weight change• Mechanical uncertainty• Setup error• Intrafraction motion

Hong et al, Radiother Oncol 103, 2012

Treatment uncertainties

• Target segmentation• Weight change• Mechanical uncertainty• Setup error• Intrafraction motion

Templeton et al, Med Phys 42, 2015

Treatment uncertainties

• Target segmentation• Weight change• Mechanical uncertainty• Setup error• Intrafraction motion Addressed with PTV margin

Planning Target Volume

• ICRU 62– “The PTV is a geometrical

concept used for treatment planning, and it is defined to select appropriate beam sizes and beam arrangements, to ensure that the prescribed dose is actually delivered to the CTV.”

Static dose cloud approximation

• Assumption that spatial dose distribution is unperturbed by variation in patient position– Delivered dose given by

convolution of planned dose distribution with patient position PDF

– Invalid near heterogeneities (Craig et al, 2003)

Craig et al, Med Phys 30, 2003

Treatment planning with respiratory motion

• ITV and PTV treat all possible tumor positions– Inaccurate representation of treated patient anatomy

• Multiple anatomy optimization has potential to reduce normal tissue dose with equivalent target coverage

Watkins et al, Med Phys 41, 2014

Robust optimization

• Conventional optimization assumes static matrix mapping fluence to dose

• Robust planning addresses uncertainty in dose distribution from a given incident fluence

𝑘𝑘 ∈

Robust optimization techniques

• Stochastic programming– Minimizes expected value of objective

function

• Composite worst-case minimax

• Objective-wise worst-case minimax

• Voxel-wise worst-case minimax

Comparison of worst-case minimax techniques

• No difference between methods without target coverage/OAR sparing conflict• Composite

– Can disregard “easy” scenarios– Best worst-case objective values

• Voxelwise– Overly conservative interpretation of DVH objectives– Better for severe target coverage/OAR sparing conflict

Fredriksson and Bokrantz, Med Phys 41, 2014

Phantom-based comparison of planned and measured doses for several lung VMAT planning techniques

• Compared several planning strategies– ITV with PTV expansion– GTV with PTV expansion– ITV with PTV expansion on average dataset– Robust optimization using all 4DCT phases– Robust optimization using mid and extreme 4DCT phases– Robust optimization on single dataset with positioning offsets– ITV with PTV expansion using intermediate density override of ITV-GTV

• Evaluated all plans using recalculation on individual 4DCT phases

Archibald-Heeren et al, J Appl Clin Med Phys 18, 2017

Phantom-based comparison of planned and measured doses for several lung VMAT planning techniques

Archibald-Heeren et al, J Appl Clin Med Phys 18, 2017

Robust optimization for setup uncertainty

• Compared ITV planning using robust optimization to ITV planning with PTV margin– 20 lung patients– Median ITV: 10.39 cc (3.29-107.23 cc)– Tumor motion: 1.45 cm (0.54-3.4 cm)

• Prescribed to PTV (if present) or ITV D95

Zhang et al, J Appl Clin Med Phys 19, 2018

Robust optimization for setup uncertainty in lung SBRT

• Evaluated use of robust optimization for setup uncertainty– Compared ITV planning using robust optimization to ITV planning with

PTV margin– Investigated impact of tumor volume and motion amplitude– Phantom study + 10 SBRT lung patients– ITV: 4.65 cc (1.74-7.76 cc)– Motion amplitude: 0.5 cm (0.2-1.5 cm)

• No renormalization of plans for consistent target coverage

Liang et al, Prac Rad Oncol 9, 2019

Robust optimization for setup uncertainty in lung SBRT

• Robust plans: 2199 MU (1917-2615 MU)• PTV plans: 2219 MU (1997-2700 MU)

Liang et al, Prac Rad Oncol 9, 2019

Questions after review of literature

• Importance of planning scan selection?• How to normalize robustly optimized dose distributions for comparison

with conventional planning practice?• 4D robust optimization versus ITV planning for management of

respiratory motion?• Robust optimization versus PTV planning for management of setup

uncertainty?• How to evaluate quality of robust treatment plans?

Phantom-based study of robust optimization for lung SBRT

• 4DCT acquired of respiratory motion phantom– 3 cm diameter GTV, 2 cm

motion amplitude, 4 sec motion period

Evaluated robust optimization techniques

• Five separate treatment plans prepared using phantom CT datasets• Evaluation dose distributions

– All 4DCT phases + average reconstruction– Perturbed isocenter positions of 0.5 cm magnitude

• Normalization such that mean over 4DCT phases GTV D90 = 60 Gy/5 fxPlan 1 Plan 2 Plan 3 Plan 4 Plan 5

Planning scan AverageMid-exhalation

phaseEnd-exhalation

phaseMid-exhalation

phaseEnd-exhalation

phase

Target volume Composite GTV, PTV

GTV, PTV GTV, PTV GTV GTV

4DCT optimization No Yes Yes Yes YesIsocenter uncertainty None None None 0.5 cm isotropic 0.5 cm isotropic

Optimization objectives

Plan 1

Plans 2 & 3

Plans 4 & 5

Robust optimization settings

Plan evaluation

Comparison of robust optimized plans

Mean DVH metrics from recalculation of each treatment plan on all ten 4DCT phasesPlan 1 Plan 2 Plan 3 Plan 4 Plan 5

MU 1630 1678 1766 1693 1761GTV D98 (Gy) 58.37 (0.73) 57.36 (0.37) 57.38 (0.39) 57.47 (0.33) 56.81 (0.40)GTV D90 (Gy) 59.98 (0.75) 60.00 (0.38) 59.97 (0.47) 60.00 (0.33) 60.03 (0.48)GTV 0.4PITV 0.03 (0.00) 0.03 (0.00) 0.03 (0.00) 0.04 (0.00) 0.04 (0.00)GTV 0.5PITV 0.05 (0.00) 0.05 (0.00) 0.05 (0.00) 0.06 (0.00) 0.06 (0.00)GTV PITV 0.19 (0.00) 0.20 (0.00) 0.20 (0.00) 0.23 (0.00) 0.23 (0.00)PTV D95 (Gy) 49.27 (0.45) 47.65 (0.43) 47.53 (0.71) 44.16 (0.86) 43.88 (0.91)PTV Dmean (Gy) 59.11 (0.81) 59.18 (0.78) 59.43 (0.82) 58.20 (0.91) 58.38 (0.94)Mean DVH metrics from recalculation of each treatment plan with perturbed isocenter positions

Plan 2 Plan 3 Plan 4 Plan 5GTV D98 (Gy) 52.39 (3.17) 51.17 (2.68) 49.76 (3.92) 47.96 (3.38)GTV D90 (Gy) 57.56 (1.90) 56.33 (1.90) 57.20 (1.96) 55.30 (2.39)GTV 0.4PITV 0.03 (0.00) 0.03 (0.00) 0.04 (0.00) 0.04 (0.00)GTV 0.5PITV 0.05 (0.00) 0.05 (0.00) 0.06 (0.00) 0.06 (0.00)GTV PITV 0.20 (0.01) 0.20 (0.01) 0.22 (0.01) 0.22 (0.01)

Future work

• Robust plan evaluation– New evaluation tools in RayStation 8

• Voxel-wise min/max distributions, DVH clusters, clinical goal evaluation over all scenarios– Voxel-wise minimum CTV V95 highly correlated with PTV V95 (Korevaar et al,

2018)• Evaluate performance with nearby critical structure• Prospective identification of cases where robust planning is advantageous

– Robust planning vs motion management

Korevaar et al, Multi-scenario robustness evaluation; transition to a ‘proton proof’ alternative to PTV evaluation, ESTRO 2018

Summary

• Management of setup uncertainty with PTV assumes static dose cloud– Invalid near heterogeneities

• Multiple-anatomy optimization offers potential for improved normal tissue sparing

• Robust optimization minimizes max cost function over all input scenarios– Superior normal tissue sparing observed relative to ITV-based planning– Further investigation needed to determine appropriate clinical use