Efficient Outcomes-Driven IMRT Treatment Planning Using Commercial Treatment Planning Systems. Radiobiological Planning in Eclipse

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1 Efficient Outcomes-Driven IMRT Treatment Planning Using Commercial Treatment Planning Systems Radiobiological Planning in Eclipse Mayo Clinic Rochester, MN MO-A-204B-2 Monday 7:30 am 7:25 am Room 204B

2 Disclosure Work supported by a grant from Varian Medical Systems

3 Objectives Understand what tools are available Planning strategies Many more variables now. Can we gain some insight into their interactions to get a view of recipes that might work reliably? Experiment to test ability of tools to give advantage Does this simplify planning? Will the tools produce plans with better radiobiological indicies?

4 Basic Information Optimization and Evaluation carried out with third party plug-ins from Ray Search Laboratories CT, structure, plan and dose (in evaluation) are transferred to the plug in. For optimization, the Eclipse optimizer is not used, instead a Ray Search optimizer is used. Then fluence information is passed back to Eclipse, where the usual dose calculation algorithm (PBC, AAA) is used.

5 Basic Information Does not support RapidArc Does support inclusion of a base dose plan Example of including a base dose plan

6 Radbio Model Library A library of user definable models is available in the Admin section Models are available both in the optimizer and in the evaluation. This saves a lot of time and simplifies standardization of parameters to use in the clinic.

7 Radiobiological Optimizer Physical Constraints (100% weighting) Min/Max Dose Min/Max Dose at Volume Target Conformance: Dose fall off Min/Max/Target EUD Uniformity Constraint: Dose Homogeneity

8 Radiobiological Optimizer Biological Constraints Can specify as constraint with weighting Must define at least one for optimizer to work NTCP Poisson-LQ TCP Poisson-LQ NTCP Lyman

9 Radiobiological Evaluation Tabs to look at DVH LQ scaled DVH Biological Response (What if dose is scaled?) Can do comparisons of multiple plans

10 Radiobiological Evaluation - Fractionation Fractionation Tab Intended to allow consideration of effect of changing fractionation schedule if repair/repopulation is used in NTCP/TCP models For this talk, just noting that capability exists and is interesting. Evaluation of accuracy is much further down the road.

11 Test Optimization Approaches on a Head and Neck Treatment Plan (54 Gy/60 Gy) Compare to conventional plan to see if addition of radbiooptimization makes a big change in indicies Is the DVH you get with a conventional optimization as good as that from a radbio optimization? The TCP/NTCP calculation doesn t care how arrive at the DVH. Look also at dose distributions to see if the overall characteristic of the dose distribution is improved clinically Try several optimization constraint / dose tuning structure sets to see what helps

12 Dose Sculpting Structures PTV 54 Gy PTV 60 Gy IMRT PTVs are cropped back from surface by 4 mm. Optimize to IMRT PTV Normalize/Evaluate PTV DLA: Defines intermediate dose region for dose reduction Buff: Specifies sub-region between target volumes to drive out hot spots

13 IMRT Reference Plan Typical manual approach Parotid: Push low dose portion of DVH Spinal Cord: Push cord max to reasonable level then push down volume on cord buffer structure near to cord.

14 Round 1 Small Constraint Set Bio Opt Bio Opt IMRT Min/Max dose on targets NTCPs on Parotids and Cord Isodose preferable for IMRT

15 Round 1 Small Constraint Set Evaluate Rad Bio Optimization IMRT R Parotid Mean 26.5 Gy 20.2 Gy R Parotid NTCP 1.84% 0.19 % L Parotid Mean 28.0 Gy 19.3 Gy L Parotid NTCP 2.8% 0.08% Cord Max 48.5 Gy 36.9 Gy Cord NTCP 1.3 % 0.03% CTV 54 Gy TCP 81.2% 79.3% PTV 54 Gy TCP 80.1 % 77.7% CTV 60 Gy TCP 88.0% 87.1% PTV 60 Gy TCP 86.6 % 85.1%

16 Round 2 : Use EUDs for target uniformity, dose fall off Bio Opt Bio Opt IMRT Add EUD constraints to improve dose heterogenity in low dose PTV and to improve dose fall off outside of PTV.

17 Round 2 : Use EUDs for target uniformity, dose fall off Evaluate Rad Bio Optimization IMRT R Parotid Mean 31.3 Gy 20.2 Gy R Parotid NTCP 9.4% 0.19 % L Parotid Mean 29.4 Gy 19.3 Gy L Parotid NTCP 4.6 % 0.08% Cord Max 28.4 Gy 36.9 Gy Cord NTCP 0.16% 0.03% CTV 54 Gy TCP 79.7% 79.3% PTV 54 Gy TCP 77.7% 77.7% CTV 60 Gy TCP 87.6% 87.1% PTV 60 Gy TCP 85.1% 85.1%

18 Round 3 Fake the D50 s on NTCP constraints Bio Opt Bio Opt IMRT Parotid D50 35 Gy -> 15 Gy Cord D Gy -> 36.5 Gy

19 Round 3 Fake the D50 s on NTCP Constraint Evaluate Rad Bio Optimization IMRT R Parotid Mean 18.2 Gy 20.2 Gy R Parotid NTCP 2.17% 0.19 % L Parotid Mean 18.7 Gy 19.3 Gy L Parotid NTCP 2.20% 0.08% Cord Max 38.9 Gy 36.9 Gy Cord NTCP 0.08% 0.03% CTV 54 Gy TCP 79.6 % 79.3% PTV 54 Gy TCP 77.7% 77.7% CTV 60 Gy TCP 87.6% 87.1% PTV 60 Gy TCP 85.1% 85.1%

20 Round 4 EUD to reduce dose Bio Opt Bio Opt IMRT Put NTCP D50 back to standard values, then add EUD constraints on Parotid and Cord This approach works well.

21 Round 4 EUD to reduce dose Evaluate Rad Bio Optimization IMRT R Parotid Mean 17.6 Gy 20.2 Gy R Parotid NTCP 0.03 % 0.19 % L Parotid Mean 18.3 Gy 19.3 Gy L Parotid NTCP 0.04 % 0.08% Cord Max 41.5 Gy 36.9 Gy Cord NTCP 0.04% 0.03% CTV 54 Gy TCP 79.7% 79.3% PTV 54 Gy TCP 77.7% 77.7% CTV 60 Gy TCP 87.9% 87.1% PTV 60 Gy TCP 85.4 % 85.1%

22 Round 5 Use TCP instead of minimum dose Bio Opt Bio Opt IMRT For normal tissues, we can successfully use EUD constraints.for PTV s, what about using TCP instead of minimum dose constraint? Not intuitive, less uniform.

23 Round 5 Use TCP instead of minimum dose Evaluate Rad Bio Optimization IMRT R Parotid Mean 21.4 Gy 20.2 Gy R Parotid NTCP 0.18 % 0.19 % L Parotid Mean 21.7 Gy 19.3 Gy L Parotid NTCP 0.18% 0.08% Cord Max 42.3 Gy 36.9 Gy Cord NTCP 0.21 % 0.03% CTV 54 Gy TCP 86.6% 79.3% PTV 54 Gy TCP 83.3% 77.7% CTV 60 Gy TCP 90.8% 87.1% PTV 60 Gy TCP 86.9% 85.1%

24 Round 6 Try EUD for minimum dose constraint on PTVs Bio Opt Bio Opt IMRT Coverage still not as uniform as for physical constraints

25 Round 6 Try EUD for minimum dose constraint on PTVs Evaluate Rad Bio Optimization IMRT R Parotid Mean 17.5 Gy 20.2 Gy R Parotid NTCP 2.17 % 0.19 % L Parotid Mean 18.1 Gy 19.3 Gy L Parotid NTCP 2.20 % 0.08% Cord Max 37.2 Gy 36.9 Gy Cord NTCP 0.08 % 0.03% CTV 54 Gy TCP 79.6% 79.3% PTV 54 Gy TCP 77.7% 77.7% CTV 60 Gy TCP 87.6% 87.1% PTV 60 Gy TCP 85.1% 85.1%

26 Lung Example NTCP Constraints Use Max/Min constraints to cover target Use NTCP constraints in Rad Bio Opt to spare normal tissues

27 Lung Example NTCP constraints RadBio (triangles) IMRT (squares) Rad Bio Opt was marginally faster with fewer constraints to modify. NTCP values are similar, slightly better for IMRT

28 Lung Example geud constraints Use Max/Min constraints to cover target Try EUD constraints instead in Rad Bio Opt to spare normal tissues

29 Lung Example geud Constraints RadBio (triangles) IMRT (squares) Rad Bio Opt was marginally faster with fewer constraints to modify. NTCP values are similar, slightly better for IMRT

30 Prostate Example Use Max/Min constraints to cover target Use NTCP constraints in Rad Bio Opt to spare normal tissues

31 Prostate Example DVHs are similar, with slighly lower dose for RadBio Optimization RadBio (squares) IMRT (triangles)

32 Summary If you are already thinking about implications of DVH shape on TCP/NTCP as you set your constraints, then you probably won t expect to see a dramatic gain. With practice, RadBio optimization may emerge as a bit faster than conventional. May choose to use more extreme ( fake ) parameter values in optimizer (e.g. TD50) and literature based values in evaluation Use of EUD constraints is more intuitive than TCP/NTCP constraints Radbio optimization doesn t eliminate need to use dose tuning structures or conventional constraints in achieving what is locally determined as a desirable dose distribution Constraints that operate on a volume weighted average (EUD, NTCP) have significant potential to simplify setting constraints